Nvidia has released a new 12GB version of its RTX 5070 mobile graphics card Nvidia has officially launched its 12GB RTX 5070 mobile GPU, upgrading its existing model with new 24Gb GDDR7 memory modules. This gives the new GPU 4GB more GDDR7 memory than its older 8GB counterpart. Nvidiaβs new RTX 5070 12GB will exist [β¦]
The post 50% memory upgrade! β Nvidia unveils new RTX 5070 12GB laptop GPU appeared first on OC3D.
While Crimson Desert's physical game sales in the US weren't enough to make major waves on the US sales charts for its launch month, it's a pretty sure bet that with its global physical and digital sales combined, it'll go down as one of the best-selling games of the year. It's already crossed 5 million copies sold, and a new report reveals that developer Pearl Abyss is sharing a bit of the wealth from its success with the entire development team. A report from Korean publication MTN claims that every single one of Pearl Abyss' employees were given a bonus [β¦]
Read full article at https://wccftech.com/pearl-abyss-reportedly-gives-every-employee-3400-bonus-for-crimson-desert-5-million-copies-sold/
Earlier today, a Final Fantasy VII Rebirth demo was released on Nintendo Switch 2 and Xbox Series X|S, allowing users to try out the first two chapters and carry over progress to the full game when it launches on June 3. Early footage of the Switch 2 port looked promising, but a more in-depth look reveals that the game's ambition may be, at times, too much for the system, as it struggles to maintain a steady 30 FPS framerate in certain scenarios despite visual cutbacks. A new comparison video shared on YouTube by GVG puts footage from the PlayStation 5 [β¦]
Read full article at https://wccftech.com/final-fantasy-vii-rebirth-switch-2-port-struggles-19-fps/
Korean memory manufacturer SK hynix has announced a yield improvement for its hybrid bonding packaging technology for high bandwidth memory (HBM) modules. Hybrid bonding enables memory chip manufacturers to bond memory layers with each other without relying on bumps. The direct contact enables higher speeds and improved efficiency through lower heat generation. SK Hynix's technical leader, Kim Jong-hoon, revealed the development at the Beyond HBM β Core Technologies of Advanced Packaging: From Next-Generation Substrates to Modules conference in South Korea, reports The Elec. Latest Packaging Technology To Come Into Play With Next-Generation HBM 4 Memory Chips High bandwidth memory is [β¦]
Read full article at https://wccftech.com/sk-hynix-verifies-12-die-hybrid-bonded-hbm-stack-but-wont-disclose-yield-figures-as-next-gen-hbm4-ai-memory-race-heats-up/
Amkor says that Glass Substrates, a packaging technology replacement for CoWoS spearheaded by Intel, is set for commercialization within 3 years. Intel-Partner, Amkor, Says Glass Substrates Will See First Commercialization Within Three Years Advanced Packaging is key to any major foundry business as chips are getting more and more complex to meet growing compute and memory demands. TSMC is the single-most important advanced packaging provider in the world thanks to its CoWoS 2.5D technology. Current chip requirements involve integration of HBM and logic chips in a single package & the number of HBM chips is expanding aggressively. Recently, OpenAI showcased [β¦]
Read full article at https://wccftech.com/intel-backed-glass-substrates-tech-will-be-commercilization-ready-within-three-years/
Greedfall developer Spiders will reportedly shut down "soon" after it filed for insolvency last month, as its parent company Nacon seemingly fails to find a buyer for the studio. After Nacon itself filed for insolvency due to financial issues with its major investor, it was reportedly looking to sell off two of its subsidiaries, Spiders and the motion capture studio, Nacon Tech. Now, according to a report from Origami, the publisher has been unable to find a buyer for Spiders, and the studio that has survived for nearly two decades after its founding in 2008 will have to close its [β¦]
Read full article at https://wccftech.com/greedfall-developer-spiders-will-reportedly-shut-down-soon-after-nacon-insolvency-filing/
FinalWire has released the updated AIDA64 software, offering support for next-gen CPUs such as AMD Zen 6 APUs & Intel Nova Lake. AMD Zen 6 "Ryzen" CPUs & Intel Nova Lake Get Early Support In AIDA64 v8.30 The latest AIDA64 release has some major updates. One of these is AIDA FPS, which expands the feature set of the software suite with a new module that captures real-time FPS data from DX11 and DX12 games. The data can be displayed across all existing outputs, including SensorPanel, OSD, tray icons, and logging. The full change log is listed below: New in AIDA64 [β¦]
Read full article at https://wccftech.com/aida64-v8-30-next-gen-amd-zen-6-apus-expo-1-2-intel-nova-lake-cpus-support/
Artificial Intelligence seems to have taken over every facet of our lives and homes, and yet, somehow, it's not really helping us in everyday life beyond the textual/visual Google Search-type help. Wearable technology itself has remained passive, simply counting steps, tracking heart rates, or sleep quality. But, not really being a true part of everyday routine, let alone helping us improve our lifestyle. Vastnaut aims to change that with its Vastnaut One 4x4, the world's first AI-powered exoskeleton, offering a fully integrated experience that mirrors human biomechanics, to improve your fitness and help you enjoy outdoor activities to the fullest. [β¦]
Read full article at https://wccftech.com/vastnaut-one-worlds-first-ai-powered-4x4-exoskeleton-promises-a-life-of-adventure/
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Every brand holds its claims, and somewhere in the archive of its digital life, thereβs proof to back them up.Β
The AI assistive engine (the systems behind ChatGPT, Perplexity, and Google AI Overviews) holds that proof too, scattered across its training data and retrieval index, alongside competitorsβ claims.Β
The audience has a need but no vocabulary to bridge the gap between what they want and what the brand or the engine already knows.
All three lack the same thing: a frame, the interpretive context that turns scattered information into a narrative worth transmitting (for the brand), citing (for AI), and acting on (for the user).
This is where the claim-frame-prove (CFP) process comes in. Claim and proof are mechanical, and frame is strategic.
Claim and prove are mechanical work the engine can verify. Frame is the strategic move only the brand can make.
CFP runs claim by claim, fact by fact. The brandβs full picture is built from many CFP cycles compounding: each claim framed and proven becomes a fact in the corpus, and the cumulative weight of those facts is what positions the brand to dominate.
AI can join known facts, but it canβt leap to a new one that benefits your brand. Given Facts A and B, AI can derive Conclusion C that follows logically. Thatβs standard inference, and the engines do it well.Β
What they canβt do reliably is the move a creative human makes constantly: looking at A and B, reaching to a non-obvious J thatβs commercially beneficial, and then constructing the logical bridge so the engine can use it.
From here, Iβll use the alphabet as the scale: C is the obvious commercial reach, J is the non-obvious, and Q is the most ambitious leap a brand can sensibly make.
Two examples from my own positioning make the difference concrete.
A + B β C
A + B β J
That second move β from A and B to J β is strategic claim bridging: selecting which non-obvious J benefits the brand from the space of derivable conclusions, and then constructing the logical connection from accepted facts to that chosen J so the engine transmits it as fact rather than as the brandβs opinion of itself.Β
Two operations packed into one move: the strategic part is choosing J, and the bridging part is making the inference watertight.
AI doesnβt choose the J thatβs good for your brand. You do. That choice, and the bridge that proves it, is the work AI has no commercial stake in, and a future (more capable) AI without your stake just produces a more sophisticated version of the same problem.
Whether AI can be creative is contested ground. The narrower claim holds regardless: even when AI produces a novel-looking output, it has no commercial intent guiding which J to derive. From the same A and B, an AI could just as easily produce a damaging J as a beneficial J. It has no skin in your commercial game.
A creative marketer does both things at once: reaches imaginatively to a non-obvious J, and chooses the J that serves the brand. Thatβs the move AI engines canβt reach, and itβs why the frame has to come from someone placing the information online (the brand, a client, or an independent source).
The disposition that lets you see this work is what Iβve been calling βempathy for the machine,β a phrase I started using in client consulting around 2011-2012 (originally as βempathy for the beast,β retired once I got more serious about the business side of digital marketing), and first published formally in 2019.Β
Itβs the discipline of stepping outside your own perspective to see what the machine actually struggles with. That advice applies to anything in SEO/AAO β in this case, specifically to when it grounds, attributes, and synthesizes claims about your brand.
Unfortunately, brands all too often produce material aimed at human readers and assume the machine will figure out the rest. With a little empathy for the machine, brands design material the machine can use as its own interpretation (feed the beast).
This produces three different levels of brand-AI communication, each one building on the previous.Β
Levels 1 and 2 are the foundations every brand needs in place, and Level 3 is where framing enters, and what this article is designed to change your thinking.
The SEO toolkit you know, plus the AI visibility data you need.
Proof exists, but thereβs nothing linking it to the claim. This is where most brands sit, and it leaves the engine to perform inference over whatever it can find.Β
The brand publishes Claim A on its website. Proof Z exists somewhere else: a conference program, an industry database, a Wikipedia citation, and a trade publication from four years ago. The brand assumes the engine will connect the two.
To connect them, the engine has to perform inference. Can it derive the conclusion that this brand is credible for this claim, given scattered premises across different domains, formats, and varying source authority?
Thereβs no copy stating the connection, no hyperlinks pointing from claim to proof, and no schema encoding the relationship.
That depends almost entirely on how confidently the machine already understands the entity, and that runs on three sub-levels.
If the machine has no confident understanding of the brand, and the proof isnβt explicitly linked, no connection happens. The proof might as well not exist.
If the machine has no confident understanding of the brand, but the proof is explicitly linked, the connection happens because the link does the work that the entity resolution couldnβt.
If the machine has a strong, confident understanding of the brand, the connection happens even without the link, because a well-resolved entity shortens the logical distance the machine has to traverse (linkless links, as Iβve called them).Β
The link still adds confidence (more than one path always does), but itβs no longer load-bearing as the entity carries the work.
The implication runs through the rest of the pipeline. Entity clarity in the knowledge graph isnβt a nice-to-have sitting alongside content work. Itβs the variable that decides whether your content work has to carry all the weight or almost none of it.Β
Any proof that isnβt explicitly linked is missed at sub-level one, caught at sub-level two, and confidently embedded at sub-level three.
When entity understanding is weak, the result is familiar to anyone tracking AI visibility: a meritorious brand appears occasionally, and when it does, the wording is hedged, and the brand sits mid-to-low-pack. The engine did the best inference it could, and, being a responsible probability engine, it hedged.Β
Worse, opportunities for inclusion are throttled across adjacent queries the fact should have pulled the brand into, because the fact was never connected to the proof that would have warranted the inclusion in the first place.
What happens when Level 1, scattered proof of claims, is done well? Brand X is infrequently mentioned, unconvincingly, as a provider of Y.
Here, the brand explicitly connects claim to proof through a combination of copy, hyperlinks, and schema. It also closes the inference gap by providing what the engine would otherwise have to figure out.Β
The brand publishes Claim A and explicitly connects it to Proof Z, with the logical thread stated in copy, anchored by hyperlinks to the proof, and encoded in schema: a fact with a significant number of supporting pieces of evidence joined to it three ways, leaving nothing for the engine to infer.
Connected proof of claims is a spectrum, not a switch. At the low end, youβve connected some of your proof, which already beats Level 1 because the engine no longer has to figure out the connections youβve made, but itβs still figuring out the ones you havenβt.Β
If your competition has connected more of theirs, youβre still losing the comparison on the proof you left scattered. At the high end, youβve connected all of it: every claim joined to every piece of supporting evidence, nothing scattered, and nothing left for the engine to guess at.
Most brands sit somewhere between scattered and connected simply because theyβve connected only the most obvious proof, and the AI may well have already figured the obvious ones out for itself: the links donβt teach it anything it didnβt already know.
With connected proof of claims done comprehensively for a given claim, the engine has enough corroboration to back the brand confidently, and the claim becomes fact in the corpus. Confidence transfers cleanly because thereβs nothing to guess at.Β
Connected proof of claims is also a great weapon for a smaller brand competing with a bigger one: a specialist accounting firm with 50 pieces of proof, all explicitly connected to a specific positioning, beats a Big 4 with thousands of unconnected pieces on that specific positioning, because connection is what turns proof into substance that the engine can transmit.
What happens when Level 2, connected proof of claims, is done well? Brand X is frequently mentioned convincingly as a provider of Y.
This is where framing enters, and where strategic claim bridging earns its name.Β
For each claim that matters, the brand publishes Claim A, connects the proof, and then does the thing the engine canβt do (and the audience is unlikely to do either, for that matter).
It reaches the non-obvious J that benefits the brand, and constructs the bridge from A and B to J in language the engine can transmit. Not merely βwe are the leader in X, demonstrated by Y,β but the frame:Β
A frame is a logical inference from corroborated facts, where the brand chose where the inference would land. For example:Β
Every component is verifiable independently, and every connection between components is logical. The J the bridge reaches to is the one I chose, not the J the engine would have generated unprompted.
One well-constructed frame makes one claim into fact in the AIβs voice. Run that across the claims that matter, and the cumulative weight is what shifts a brand from βfrequently mentioned convincinglyβ to βalmost always mentioned as the leading providerβ: dominance is a stack of well-framed facts, not a single masterstroke.
The result: the AI doesnβt merely confirm, it enthuses. βBrand X leads in Y, and here is why that matters for your situation.βΒ
The engine transmits the frame wholesale, in the language you chose, to the audience you specified, with a reason to keep coming back. The machine didnβt generate the narrative; it relayed it warmly.
What happens when Level 3, framed proof of claims, is done well across the claims that matter? Brand X is almost always mentioned as the leading provider of Y, and dominates the space.
Each level builds on the previous: connected proof of claims requires scattered proof of claims connected, and framed proof of claims requires connected proof of claims bridged strategically.
The brands that think theyβre at framed proof of claims are usually at framed proof of claims for humans, and scattered proof of claims for machines. Marketing and narrative work supplies frames to humans all the time, and plenty of brands do it well.Β
What almost no brand does is supply frames the machine can use, and the gap between the two is where framed proof of claims is most powerful.
Some brands operate below even that and are effectively standing still: published facts at the surface, few proof connections, and no interpretive content the machine can use for any purpose.Β
The signature objection from a standing still brand is the same in every consulting room: βWe already do this, our website explains who we are.β The website does that. The website is doing zero work to help the machine with framing.
The cost of standing still isnβt visible until a model update or two down the line. Brands that think theyβre at framed proof of claims are usually investing harder in the wrong layer (content), while the layer that matters (framing and, ideally, joining the dots) compounds for someone else.Β
The gap widens every year. If you have content that doesnβt frame effectively or join the dots with links to proof, youβre leaking huge value, and pushing through connection and framing is the best return on past investment you can make right now: youβre doing the heavy lifting for the machines, and theyβll reward you for giving them this extremely valuable context on a plate.
Three structural conditions separate framed proof of claims from marketing-and-narrative-as-usual, and missing any one collapses the brand back to connected proof of claims or lower.Β
The entity has to be well-established, well-resolved, and trusted, because a frame canβt anchor to a vague brand. The underlying proof has to be connected, because most brands have fluent marketing prose on top of scattered proof, which is scattered proof of claims with prettier wallpaper.Β
The bridge itself has to be strictly logical, because machines read logic first and tone second, and a logically broken bridge fails, however well itβs written.
Smarter AI rewards better framing rather than replacing it, and the reason is the same selection pressure SEO practitioners have been operating under since the early 2000s.Β
Thereβs a seductive and entirely wrong conclusion to draw from rapid improvement in AI reasoning: that engines will eventually figure out how to frame brands correctly without help. The opposite is true. The engine rewards the brand whose assets reduce its own workload for the same or better result.
Search engines reward sites that are easy to crawl, render, and classify. Knowledge Graphs reward entities that are easy to resolve. AI assistive engines reward content that is easy to ground, verify, and transmit confidently. Where the engine has to choose between two roughly equivalent candidates, the candidate that demands less computation, less inference, and less guesswork wins.
Framed proof of claims is that principle operating at the bridging layer. A more capable engine encountering this level has the bridge handed to it ready-made. It doesnβt have to figure out the frame, it transmits the bridge the brand supplied, fluently and confidently, with the engineβs full reasoning capability now amplifying rather than substituting for the framing work.
A more capable engine without a frame falls back to inference over scattered evidence, which is expensive, ambiguous, and produces hedged output. Every improvement in reasoning capability makes the hedging more detailed and the noncommittal language more sophisticated, but the underlying problem isnβt capability, itβs the absence of a frame to amplify. The engine is doing more work for a worse result, and thatβs the exact failure mode the engineβs selection pressure is designed to penalize.
The gap between those two outcomes is the framing gap, and it widens with every generation. Brands implementing only connected proof of claims donβt lose ground in absolute terms, they lose ground relative to brands implementing Framed Proof of claims faster every year, because the engine increasingly rewards assets that let it deploy its growing capability productively rather than waste it on guessing and hedging.Β
The selection pressure that rewarded fast websites in 1998, clean HTML in 2003, and structured data in 2015 rewards framed proof of claims now. The mechanism of gaining a competitive advantage by reducing costs for the AI for the same or better results hasnβt changed β and probably never will.
The framed proof of claims trajectory rises steeply and continues climbing. The connected proof of claims trajectory rises gently and flattens. The shaded area between the two lines is labeled the framing gap and visibly widens with each generation.
The SEO toolkit you know, plus the AI visibility data you need.
The bridge is human territory, and it stays human because it requires commercial intent specific to the brand that the engine doesnβt have.Β
Everything the machine does well will get better: retrieval, connection, pattern extraction, and synthesis. None of that helps the brand whose evidence the machine can see but canβt bridge meaningfully to a beneficial conclusion.
Whether AI confirms your brand, overlooks it, or champions it comes down to one discipline: strategic claim bridging, claim by claim, fact by fact. Itβs the last layer of brand-AI communication that wonβt yield to automation, if it yields at all.
This is the 11th piece in my AI authority series.Β
Wil Reynolds, founder and CEO of Seer Interactive, is challenging SEOs to rethink what success looks like in a world increasingly shaped by AI.
In his SEO Week session, βSEO is a performance channel, GEO isnβt. How do you pivot?β, Reynolds said many marketers are focused on the wrong outcomes β and producing work that people donβt believe.
Reynolds opened by pushing back on the idea that visibility alone is the goal of marketing.
βMarketing was never just to be seen or be visible,β he said. βYou had to turn that visibility into something β believing something about your brandβ¦ And then they ultimately have to choose you.β
He described a progression that marketers need to focus on: being seen, being believed and being chosen.
βItβs how you take your time with people, and turn them from seeing you, into believing something about you,β he said.
βI got the ranking, job finished,β he added. βJobβs not finished.β
Reynolds also questioned the value of surface-level success metrics.
βI got a lot more followers, but they donβt pay you,β he said.
Reynolds pointed to common marketing tactics β including automated outreach β as examples of work that doesnβt create value.
βThatβs not marketing,β he said, referring to spam-like SMS messages.
Those tactics made him reflect on his own past work, he said.
βI started looking at the stuff that I used to doβ¦ was that really marketing?β he said.
βSome of us are strategists. Some of us are loopholists,β he said. βYouβve got to make a decision today.β
Reynolds criticized the widespread use of scaled, templated content designed primarily to rank.
He used broad listicle-style pages as an example.
βWhy would you write content saying best restaurants in Minnesota when nobody thatβs a human looks for the best restaurant in Minnesota?β he said.
He described this type of content as βzombie content.β
βThatβs what we do,β he said, describing how marketers repeat what already ranks instead of doing something different.
He also described how many marketers approach content creation.
βIβm going to look at the top 10 and look at what they did slightly wrongβ¦ and Iβm only going to do it slightly better,β he said.
Reynolds contrasted short-term SEO tactics with long-term brand building.
βSome people like to win in decades,β he said. βOther people like to win quarter to quarter.β
He described how many teams focus on immediate results.
βWhat works this quarter to get my boss off my back long enough so I can survive the next quarter?β he said.
That approach leads to work that people donβt actually want, he said.
βYou will never produce a thing that anyone wants if you continue to play that,β he said.
Reynolds shared an example involving βethical jeansβ to show how SEO and AI results can differ.
One brand ranked well in Google without being known for ethical practices, while another brand that invested in ethical production ranked much lower.
In AI-generated answers, that outcome changed.
βIf that worked, if it was the same, that brand would be showing up in AI models,β he said. βAnd they showed up in none.β
He connected this to credibility.
βNobody believed them,β he said. βNobody chose them.β
Visibility alone isnβt enough, Reynolds said.
βIf you have all the visibility in the world and people donβt believe you or trust you, then youβre not going to get chosen,β he said.
Visibility is only part of the process, he said.
βThis visibility is just an opportunity,β he said. βThatβs all it is. β¦ Iit is not the job to be done.β
Reynolds suggested looking at platforms like Reddit to understand how people actually talk about brands.
βGo to Redditβ¦ look at all the brands,β he said. βYou find out that humans donβt believe you. And they have to pay you for you to stay in business.
He contrasted that with how brands present themselves in content.
βNot only did they not think youβre number one β they donβt think youβre number 100,β he said.
Marketers often focus on metrics that are easy to track rather than meaningful, Reynolds said.
βWeβre measuring the easy stuff to measure,β he said. βThe real work is in the hard-to-measure stuff.β
He encouraged comparing visibility metrics with signals tied to outcomes.
βIf your visibility is skyrocketing and your pipeline is flat, thatβs bad,β he said.
Reynolds described research his team conducted by observing real people using AI tools.
βWhen you actually watch people do the jobβ¦ your eyes open so much wider,β he said.
One person typed four words, while another typed more than 100 words for the same task, he said.
He also noted that AI tools often suggest additional steps or actions beyond what users ask for, and people frequently accept those suggestions, he said.
Marketers should focus on how their brand appears in AI-generated answers, especially for branded queries, Reynolds said.
βYou spend all this money trying to get people to know your brandβ¦ and then you donβt want to make sure that answerβs right?β he said.
Reynolds shared an example where AI-generated responses surfaced incorrect information about his company.
βSo now itβs showing up everywhere,β he said.
He described responding by publishing content to address the claim directly.
βIf itβs false, then Iβve got to fight that,β he said.
βThereβs too much content out there,β he said.
He described shifting his approach.
βIβm trying to become a curator,β he said.
Reynolds shared examples of how different traffic sources perform.
βMy direct converts 1.5 times better than my SEO,β he said. βMy social, five times better.β
Reynolds ended by asking marketers to rethink their priorities:
βAre you willing to sacrifice a little bit of this visibility game to be more believable?β
One of the most dependable ways to grow organic visibility was to publish more content. Expanding into the long tail and creating pages around different variations of a topic often led to steady traffic growth.
Many SEO teams still operate with this mindset. Content calendars are built around search volume targets, and growth is often equated with how much new content is produced. The problem is the results no longer reflect the effort.
In many cases, adding more pages doesnβt lead to increased visibility and can even dilute overall performance. Large content libraries are harder to maintain, compete internally, and often result in fewer pages surfacing in search results.
The challenge is no longer producing more content, but understanding why much of it fails to contribute to visibility.
For a long time, increasing content volume was a rational and effective strategy. Search engines relied heavily on keyword matching and topical coverage, which meant expanding into the long tail created more opportunities to capture demand.
Competition was also significantly lower, and many queries had limited high-quality results, so publishing across a wide range of keyword variations often led to quick visibility gains. In this environment, covering more topics translated directly into increased traffic.
Publishing frequency also helped strengthen domain authority. Sites that consistently added new content signaled freshness and relevance, which improved their ability to compete in search results.
This approach was further amplified by programmatic SEO. By creating scalable templates and targeting large keyword sets, companies generated thousands of pages and captured traffic at scale.
Most importantly, this strategy worked because it aligned with how search engines evaluated content at the time. Expanding coverage increased the likelihood of ranking, and more pages meant more opportunities to be discovered.
However, the conditions that made this approach effective have changed. As search ecosystems have evolved and competition has increased, the relationship between content volume and visibility has become less predictable.
Dig deeper: Content marketing in an AI era: From SEO volume to brand fame
Most commercially relevant topics now have dozens of established pages competing for the same queries, many with years of accumulated links and behavioral data.Β
A new page enters this environment at a disadvantage because the keyword spaces it targets are already consolidated around results with existing authority and signal history.
As sites expand into adjacent keyword variations, search engines increasingly route similar queries to the same URL rather than distributing traffic across multiple pages.Β
This shows up in Google Search Console as two or three URLs splitting impressions on identical queries β neither ranking strongly because neither has consolidated authority. The intent overlap that content teams treat as coverage, Google treats as redundancy.
AI Overviews now appear across a significant and growing share of informational queries. Google has confirmed continued expansion of the feature across search types and markets. Informational content is the most affected by this shift, and itβs also the type most volume strategies produce.Β
A site with a large number of blog articles is therefore more exposed than one focused on a smaller set of transactional pages. More ranked pages donβt produce proportional traffic when an increasing share of visible positions no longer generate a click.
Googleβs budget documentation states directly that low-value URLs drain crawl activity away from pages that matter. At scale, thin or redundant content is deprioritized β meaning a significant percentage of a siteβs published pages may never meaningfully enter search competition regardless of how much continues to be added.
Dig deeper: The authority era: How AI is reshaping what ranks in search
Whatβs less understood is how content libraries behave at scale. These are system-level problems that compound over time and are difficult to reverse.
Every page published creates an ongoing obligation. It needs to be monitored for ranking decay, updated when information changes, evaluated periodically for pruning or consolidation, and factored into crawl allocation. These costs are rarely accounted for at the point of creation.
At low volumes, this is manageable. At scale, it becomes a compounding liability. A site with 2,000 articles isnβt sitting on 2,000 assets, itβs managing 2,000 maintenance commitments that depreciate at different rates.Β
Editorial resources that could strengthen existing high-performing pages are instead absorbed by keeping a growing library from becoming a liability.
The true cost of a volume-driven content strategy only becomes visible 18 to 24 months after the investment, when maintenance demands begin to outpace the capacity to meet them.
Google allocates a finite crawl budget to each domain. When a site scales content volume without proportional gains in quality or authority, Googlebot distributes that budget across a larger number of pages, many of which offer limited signal value. The result is that high-value pages are crawled less frequently, indexed less reliably, and are slower to reflect updates.
This creates a compounding problem for sites with important transactional or evergreen pages that depend on frequent re-crawling to stay current and competitive. Beyond crawl distribution, similar pages targeting overlapping intent compete for the same ranking positions internally.Β
Search engines consolidate these signals rather than rewarding each page individually, meaning two pages targeting near-identical queries often perform worse combined than one authoritative page targeting both would perform alone.
Search engines evaluate whether a site is a genuinely deep and trustworthy resource within a defined topic space. Expanding into a wide range of loosely related subtopics can erode this signal rather than strengthen it.
A site with 40 tightly interconnected, substantive pieces on a specific topic will consistently outperform one with 400 surface-level articles spread across adjacent themes. The depth and coherence of coverage within a defined area are what build the authority signal that drives durable rankings.Β
Pursuing breadth at the expense of depth fragments that signal, making it harder for search engines to assign clear expertise to the domain on any individual topic, even the ones the site knows best.
Search engines use behavioral data such as dwell time, return-to-search rates, and click-through rates as quality signals at both the page and domain levels.Β
When a site publishes high volumes of content that users engage with poorly, those signals accumulate and begin to affect how search engines evaluate the domain as a whole. This creates a negative reinforcement loop thatβs difficult to detect and slow to reverse.Β
Weak pages actively contribute to lower domain-level quality assessments, affecting the performance of pages that would otherwise rank well. More mediocre content compounds. Each low-engagement publish incrementally reduces the baseline trust that search engines extend to the domainβs better work.
The goal of SEO has traditionally been to rank. Increasingly, the more valuable outcome is to be cited or referenced in AI-generated summaries, pulled into knowledge panels, or sourced by other publishers as a primary reference. These two outcomes require fundamentally different content strategies.
LLMs and AI Overviews are selective about which sources they draw from. The selection is weighted toward pages with strong E-E-A-T signals, high specificity, and clear authoritativeness within a defined domain.Β
A site that has published hundreds of generic articles covering a topic broadly is less likely to be treated as a primary source than a site that has published fewer, more definitive pieces with clear depth and original perspective.Β
Volume doesnβt increase citation probability β it may actively reduce it by signaling that the domain is a generalist content producer rather than a reliable primary reference.
The accessible long tail that drove content volume strategies for the better part of a decade no longer exists in the same form. Between 2010 and 2020, there were genuinely underserved keyword opportunities across most industries.Β
Today, in most commercial verticals, every remotely valuable query has multiple established pages competing for it, especially from high-authority domains with years of accumulated signals.
New content entering this environment doesnβt find open space. It enters a war of attrition against incumbents with advantages it canβt easily overcome. The marginal SEO return on a new article targeting a long-tail keyword is a fraction of what it was five years ago.Β
The economics only justify creation when thereβs a genuinely differentiated angle, a proprietary data point, or a perspective that exists on your page that other pages canβt offer. A keyword existing is no longer a sufficient reason to publish.
At scale, these factors turn content growth into diminishing returns rather than compounding gains. The library becomes harder to maintain, harder for search engines to evaluate clearly, and harder to extract meaningful visibility from β regardless of how much is added to it.
Dig deeper: How to keep your content fresh in the age of AI
The implication is to change what publishing is for.
Volume targets made sense when more pages meant more opportunities. In the current environment, they measure the wrong thing. The more useful question isnβt how much content a team is producing, but how much of what already exists is actively contributing to visibility, and what is quietly working against it.
For most sites, that audit reveals the same pattern. A relatively small number of pages generate the majority of organic traffic. A larger number generates little to none, and a significant portion actively drains crawl allocation, fragments topical authority, or dilutes the behavioral signals that stronger pages depend on.
You need to move from expansion to consolidation. Existing pages that cover overlapping intent are stronger merged than competing. Thin pages that rank for nothing and engage no one are more valuable removed than retained.Β
The energy going into producing new content at volume is often better spent deepening the pages that already have authority and signal history behind them.
New content earns its place when it:Β
In practice, this means retiring a few default assumptions:
None of these were ever true measures of content effectiveness. They were convenient ones.
Dig deeper: Content strategy in 2026: What actually changed (and what didnβt)
The replacement for volume isnβt simply better content. Itβs a different definition of what content is trying to achieve.
Focus coverage on a smaller number of topics and develop them thoroughly. A single piece that addresses a topic with specificity, original perspective, and clear authorial expertise will outperform multiple pieces covering adjacent variations of the same theme.Β
Depth is what builds authority signals, drives engagement, and increases citation potential. Prioritize what the site can say with the most credibility.
Allocate more effort to distribution. Publishing less creates capacity to deliver strong content to the right audiences. Distribution is a core part of SEO performance in a citation-driven environment.
Create content that can serve as a primary source. Focus on clear points of view, verifiable expertise, and specific insights that other pages canβt replicate.
The goal is to be referenced in AI-generated summaries, cited by other publishers, and included in the knowledge systems search engines rely on.
Dig deeper: Content alone isnβt enough: Why SEO now requires distribution
Sites that rely on frequency and broad coverage are being outperformed by sites that are clearly authoritative on a defined topic, consistently useful to a specific audience, and structured in a way that search systems can evaluate with confidence.
Prioritize depth, clarity of expertise, and consistency within a focused topic area. Treat each published page as a long-term asset that requires ongoing maintenance, evaluation, and improvement.
The content factory model is no longer effective. The approach that replaces it requires more effort, stronger editorial standards, and a higher bar for what gets published.
NVIDIADemand for GeForce RTX GPUs remains strong, and memory supply is constrained. In order to maximize memory availability, we are releasing the GeForce RTX 5070 Laptop GPU 12 GB configuration with 24 Gb G7 memory. This gives our partners access to an additional pool of memory to complement the 16 Gb G7 supply that currently ships with most GeForce GPUs. The 12 GB configuration will exist alongside the current 8 GB configuration, and allows our partners to bring a broader range of GeForce RTX 5070 laptops to consumers.
Corsair has just launched its ThermalProtect PCIe 5.1 600W cable for 16-pin GPUs with over-temperature protection to safeguard your graphics cards. Corsair Is The Latest Manufacturer To Offer A Safer Cable With Built-In OTP To Safeguard 16-Pin GPUs Running a 16-pin graphics card has become a scary ordeal. You will constantly be checking real-time monitoring utilities, the physical connectors, and your PC for fluctuations because 16-pin cards have a higher chance of dying due to the flimsy nature of the connector. Every day, you hear an RTX 5090 or a similar 16-pin graphics card card either burning up or dying [β¦]
Read full article at https://wccftech.com/corsair-16-pin-cable-shuts-down-your-gpu-the-moment-the-connector-gets-too-hot/
Appleβs new Liquid Glass UI was almost immediately copied by Chinese smartphone competitors as they integrated the plethora of changes on their custom Android skins. However, thatβs not the only design these manufacturers intend to bring, and if they are quick enough, they can actually beat the Cupertino firm in their race to introduce a quad-curved display design, the same one thatβs expected to debut on the iPhone 20. OPPO is said to be working on this technology and is rumored to adopt the same bezel-less illusion effect thatβs said to arrive on Appleβs 20th anniversary release. OPPO is rumored [β¦]
Read full article at https://wccftech.com/chinese-smartphone-companies-copy-iphone-20-quad-curved-display-design/
The war on piracy in video games between the game publishers selling games and the parrot-companioned players who would rather not pay for those games has just seen its latest milestone, as a committed community of players known as the MKDev Collective and user DenuvOwO, who are known for cracking games, claim they have cracked all Denuvo-protected single-player games. Which has seemingly caused Denuvo and at least one publisher, 2K Games, to respond with online DRM checks with a two-week window. This all comes from a new report from Tom's Hardware, which spotted claims on X (formerly Twitter) that games [β¦]
Read full article at https://wccftech.com/denuvo-2k-games-reportedly-add-two-week-drm-checks-after-pirates-crack-all-single-player-denuvo-games/
While GPUs aren't seeing a significant price increase these days, they are still selling for much higher prices than in the pre-RAMpocalypse era. GPU Market Data for 10 Countries Show Prices for NVIDIA RTX 50 and AMD RX 9000 Series GPUs are Almost Stagnant, but Future Remains Uncertain We have the latest GPU prices data for 10 countries from Tech Spot, which has been tracking the prices since November 2025, when the GPU prices were the lowest since RAMpocalypse started. The GPUs started to become more expensive right after DRAM and SSDs became more expensive, and although we didn't see [β¦]
Read full article at https://wccftech.com/latest-gpu-market-data-shows-stabilized-prices-in-different-regions/
NVIDIA is launching a new configuration of its highly popular GeForce RTX 5070 Laptop GPU, which features 12 GB of memory. NVIDIA GeForce RTX 5070 Laptops Are Very Popular & Now Getting a 12 GB Memory Option NVIDIA's GeForce RTX 5070 laptops are highly popular in the gaming segment. These laptops not only offer great gaming performance, but they also pack strong AI capabilities, making them an ideal choice for mainstream users. Now, NVIDIA is expanding its GeForce RTX 5070 Laptop lineup with a brand new configuration. The new configuration packs 12 GB of memory, a 50% boost over the [β¦]
Read full article at https://wccftech.com/nvidia-bumps-rtx-5070-laptop-gpu-to-12gb-gddr7-memory/
NVIDIA has released a new GeForce Game Ready Driver (version 596.36) ahead of the May 5th launch ofΒ Conan Exiles Enhanced, the sweeping Unreal Engine 5 overhaul of Funcom's long-running survival title.Β As announced last week, Conan Exiles Enhanced will debut on PC exclusively via Steam as a free upgrade. For GeForce RTX players, the update also includes support forΒ DLSS Multi Frame Generation,Β DLSS Frame Generation,Β DLSS Super Resolution, andΒ NVIDIA Reflex, the latter reducing PC latency to make combat and survival gameplay feel snappier and more responsive. All of these GeForce features were entirely missing from the original Conan Exiles, so they will be [β¦]
Read full article at https://wccftech.com/nvidia-game-ready-driver-conan-exiles-enhanced-dlss-4-ue5/
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If your paid social campaigns arenβt converting, you may be undervaluing their impact. Your brandβs exposure on social media can influence other parts of your marketing that platform metrics donβt capture.
Hereβs how to design and measure a test to understand how paid social influences your other marketing channels, including PPC.
Start with what you want to learn, then define a hypothesis you can realistically evaluate with your data.
For example, this is a common hypothesis for measuring paid search lift from social traffic:
Your hypothesis could have a different scope, such as measuring paid and organic lift from social spend or an increase in direct traffic.Β
The next step is to set up the test parameters. Generally, measuring before and after a change is a mistake, as seasonality or other factors can affect your test results.
The most common test setup is a geographic split. In this test, weβll increase social spend for only a set of geographies. Then weβll examine the PPC data for the geographies where we ran the test and compare them with areas where we did not.
As you choose geographies, youβll want to control for other variables that may affect your test. Here are some common issues that companies have run into and need to control for in their tests and measurements:
Your control and experimental groups should be statistically similar across factors such as income levels, and urban versus rural regions.
As you set up and measure your test, consider your budget. If you increase social spend and expect higher clicks and conversions for your PPC campaigns, ensure you have the budget to capture the increased demand.
Examine your impression share and impression share lost to budget before and after the test to ensure budget limits wonβt severely impact your results.
Dig deeper: Why PPC tests in 2026 call for nuance, not winners
Measurement can go from very simple to extremely complex.
At a simple level, you can compare platform data to see how your data changed. In this case, a Google Ads report shows how pausing social spending and influencer campaigns across all social platforms (TikTok, LinkedIn, Facebook, YouTube, etc.) affects performance.
For this test, pausing social spending yielded mixed results for conversion rates. As brand searches decreased, conversion rates in some regions increased, while in others they fell.
However, what was consistent was a dramatic drop in conversions.
You can get more sophisticated in your testing. Depending on your analytics setup, some companies want to measure touchpoint differences for their conversions. Others will want to measure overlap rates between social and paid search visitors, or examine attribution touchpoints and models.
Before you set up your test, ensure you have the measurement capabilities needed to understand and interpret the results.
As you run various tests, you want to measure the results against your hypothesis. However, itβs useful to list other variables worth evaluating beyond your test criteria.
This is where search consoles, analytics tools, CRM, internal data, and even the paid and organic report can come into play.
In one example, a company was running a test to see whether pausing several advertising channels, from social media to TV ads, would dramatically change its brand search volume. They hypothesized that their brand was so well known in the marketplace that they could cut back on several forms of brand advertising and reallocate that budget to other channels and non-brand advertising.
While the simple paid and organic report in Google Ads wonβt tell you the full story about in-store revenue and direct traffic changes, it can serve as a signal to form an overall picture of a very complex test.
They had recently launched a new product line, and that line continued to see a large increase in traffic during the test. However, their most common brand terms saw significant declines from the test. This was a year-over-year comparison across a set of geographies, rather than a period-to-period comparison, to help correct for the increase in holiday traffic that would have occurred during the previous period.
The results were by far the most dramatic Iβve ever seen in this type of test, to the point it was clear other variables had to be in play that could affect the test.
This takes you to the sniff test. Rely on your experience with data to make common sense adjustments. If you look at the data and it just doesnβt seem right, ask yourself whether this makes sense, if itβs a math quirk (common with low data), or if other unforeseen variables are in play.
In this example, no one believed the results should be this dramatic. The company stopped running the test and began an internal evaluation of its organic presence, including Googleβs recent updates, changes to AI Overviews, AI engagement, and other factors affecting its web presence beyond its usual marketing channels.
Dig deeper: Are your PPC ads still authentic in the age of AI creative?
The test setup is simple:
For some companies, Facebook and other social channels are their top conversion channels, and these tests wonβt be applicable. For others, social media advertising results often look poor when evaluated in isolation.
In these examples, the companies were already running many social media campaigns, so the test was to reduce social media spend. If you donβt run much social media, your test will be to increase your social media spend to see how it affects your data.
Iβve seen a lot of these tests, and the results are highly inconsistent across companies. Many companies will increase their social media spend and see little change in their data. Others will increase their spend and see a nice lift in overall performance. These are tests you need to run yourself, as your results will vary by company.
Running geographic split tests in your social media campaigns and then measuring the results on paid or organic search traffic can give you insights into how to leverage social media campaigns for other marketing channels.
Google announced they are testing a new βconversational search experience to complement how you already search on YouTube.β It is called βAsk YouTubeβ and it lets you βdive deeper into the topics youβre curious about in a more interactive way,β Dave from YouTube wrote.
What it looks like. Here is a GIF of it in action:
How can I try it. If you want to try it out, you can go to youtube.com/new and try to opt into it.
This experiment is currently available for YouTube Premium members 18+ in the US who opt-in. Google is working on expanding the experiment to non-Premium users in the future.
What it does. Dave from YouTube posted this example:
βIf youβre in the experiment, you can try it out by selecting βAsk YouTubeβ in the search bar. For example, you can ask for help planning a 3-day road trip from San Francisco to Santa Barbara, and youβll get a structured, step-by-step itinerary instead of a list of videos. The response will bring together a new mix of long-form videos, Shorts, and informative text featuring local tips and must-see stops. You can ask follow-up questions like, βwhere can I find good coffee?β to explore local spots along your route. Weβll surface videos and relevant video segments, accompanied by their titles and channel details, to make it easy to discover new creators and jump into the most helpful content from your search.β
Why we care. AI search is creeping into every search interface across Googleβs properties. YouTube is no exception. Expect more and more AI search experiences in more Google surfaces and expect them to change and adapt over time.
You can find more coverage of this across Techmeme.
Understanding the ins and outs of paid media can seem like an overwhelming process when youβre first entering the field. As AI has rapidly changed ad platforms in recent years, keeping up can feel challenging.
Thankfully, youβre not alone. Youβre part of a supportive industry with a wealth of content and knowledge to share. Here are seven tips to help you learn and become a more confident PPC manager.
Curiosity is foundational to growth in PPC. Youβll learn best by taking initiative to understand ad platforms, how campaigns are structured, and what options are available on the backend. Of course, be careful about tweaking settings youβre not familiar with, but donβt be afraid to dig in on your own.
If youβre part of a team, ask your colleagues why they use a particular setup. If youβre not familiar with a platform and have a team member who frequently uses it, ask if they can walk you through it.
There are countless industry professionals producing content to teach PPC. Whether you learn best from reading, listening to podcasts, or watching videos, youβll find options that fit your style. Looking up the authors of articles on this site is a great starting point to build a list to follow.
Block out time in your schedule for education. Even setting aside a couple of hours a week helps you gain perspective from others in the industry and keep up with constant platform updates.
The PPC industry has long been known for its welcoming, supportive community. Seek out individuals and organizations who are actively sharing, and donβt be afraid to engage with them on social media. Conferences are also a great way to network with other PPC professionals and sometimes discuss their approaches in a more informal setting.
A brief word of caution: Vet recommendations you see from others against your own experience in ad accounts. Just because a βbest practiceβ worked for one account doesnβt mean itβll work for every account. Depending on the tactic, you may want to test it as an experiment to measure impact, or compare results before and after.
Dig deeper: What 10 years of PPC testing reveals about breaking best practices
While ad platform certifications can serve as a starting point for demonstrating basic functionality, be cautious about relying on them as the end-all proof of PPC expertise.
Certifications often lean heavily on platform-recommended best practices, which may conflict with tactics that align with a brandβs goals. Academic knowledge canβt match the insight gained from practical, hands-on experience in accounts.
While Iβd encourage staying aware of ad platform updates and current tactics, Iβd discourage implementing a new campaign type or expanding into a new platform just because itβs new. Make sure you have sufficient budget and a clear reason to test.
Additionally, avoid making adjustments without a rationale. If campaigns are performing and driving qualified leads or sales, keeping the status quo may be best.
Basic marketing principles still apply, such as knowing your target audience, addressing their problem with a solution, and presenting a clear call to action. Focus on aligning your channel choices with these goals, and the rest will follow.
Dig deeper: 10 keys to a successful PPC career in the AI age
As you become more embedded in PPC, you may naturally use industry terms and acronyms such as CTR, CPC, ROAS, and CPA. However, these metrics are often meaningless to stakeholders who arenβt immersed in your world. One of the most vital skills for a paid media professional is translating abstract metrics into language that connects with what stakeholders care about.
For instance, I often default to βconversions,β even though the term can be ambiguous in reports. Referencing the actual action being tracked (such as account open, form fill, or purchase) is more concrete and ties directly to what stakeholders are tasked with driving.
AI is an inevitable part of a future-forward career, and ignoring it will be detrimental to career development. However, donβt lose the human oversight that sets a seasoned PPC practitioner apart.
When writing ad copy, LLMs can offer a strong starting point and help refine wording. But donβt rely on AI to produce all your copy, as it may pull irrelevant content from your site (or elsewhere), and may not reflect your brandβs voice and perspective. Also, learn where AI can save time on βbusy workβ tasks, such as reviewing search terms and placements for exclusions, while still reviewing the output for accuracy.
While most ad platforms default to automated campaign setups and encourage a hands-off approach, a standout PPC manager understands the levers they can pull to maintain control when needed. Examples include:
Dig deeper: The new PPC playbook: From media buyer to profit engineer
One common temptation for both new and seasoned paid media practitioners is to make changes just to appear busy. The motivation may be valid, as you want to prove to your client or boss that youβre attentive to PPC account management.
However, particularly with campaigns that rely heavily on data to drive automated bidding, too many changes in a short period are often detrimental. Be sure to allow for data significance and enough time before pausing ads and keywords or tweaking bid targets.
If you can show positive performance trends and provide readouts on which campaigns and channels are driving those results, you can validate your decisions to take or not take action when presenting to stakeholders.
Becoming a confident PPC manager requires mastering a blend of technical, interpersonal, and marketing skills. As you build your knowledge, look for opportunities to share what youβre learning with peers. Itβs one of the fastest ways to reinforce what you know and keep improving.
Dig deeper: 7 power moves to accelerate your PPC career
The Division Resurgence is now available on PC through Ubisoft Connect Following the gameβs release on iOS and Android, Ubisoftβs The Division Resurgence is now available on PC in βEarly Accessβ. Resurgence is a free-to-play looter-shooter RPG thatβs set in New York City. The game offers 3rd-person tactical combat and is playable solo or in [β¦]
The post The Division Resurgence is now available on PC in Early Access appeared first on OC3D.
The fancy-looking ASUS RTX 3090 has a common problem, which often goes unnoticed but can kill the GPU components if not paid attention to. NorthWestRepair Fixes Damaged PCB and SMD Components on ASUS Strix RTX 3090 Caused Due to Too Much Pressure Applied on the Shroud Screws Sometimes a simple disassembly/assembly can cause complicated problems with PC components, and that's even difficult to spot when it's a GPU. The PCB traces and SMD components are easy to damage, resulting in shorting, which could potentially kill the GPU. That's why it's advised not to start any DIY process with these components [β¦]
Read full article at https://wccftech.com/asus-strix-rtx-3090-has-a-hidden-design-flaw-that-kills-the-vrm/
Colorful has launched two budget-tier motherboards with the LGA 1851 and LGA 1700 sockets for previous-gen and latest-gen Intel processors. Colorful Introduces Battle-AX B860M-Plus S and B760M-Plus S Motherboards With WiFi 7 and PCIe Gen 5.0 Support for Intel 12th/13th/4th gen and Core Ultra 200S Series Chinese hardware maker Colorful has introduced two new motherboards in the Battle-AX series. While most manufacturers are releasing boards for the newer Arrow Lake processors, Colorful has introduced new motherboard models for both Arrow Lake and 12th/13th/14th gen processors. Both motherboards are aimed at the budget segment, featuring the B860 and B760 chipsets. The [β¦]
Read full article at https://wccftech.com/colorful-launches-battle-ax-b860m-and-b760m-motherboards/
The opening of Saros pits you against the Consort, a formidable tutorial boss designed to teach you the high stakes of combat. While most players will fall to this boss, it is possible to defeat it and receive some rewards for your efforts. However, the fight is really difficult because you lack the advanced abilities such as Parry, Power Weapons, and Second Chance (free revive) unlocked later in the game. You are limited entirely to a Handcannon, and your own personal skills action game skills. Should You Try to Beat The Consort? If you manage to defeat the Consort, you [β¦]
Read full article at https://wccftech.com/how-to/saros-can-you-beat-the-tutorial-boss-consort-boss-guide/
Samsung recently exited low-end NAND and DRAM businesses, which has resulted in a major boost for Taiwanese and Chinese markets. Taiwan-Based NAND Maker, Macronix, Sees Big 4x Boost In MLC Business As Samsung Focues on High-End Products Recently, we reported that Samsung had exited LPDDR4 and LPDDR4X memory segments to focus on the more lucarative LPDDR5/X memory, which is a hot item for AI. The semiconductor giant also closed its MLC NAND business to focus on higher-end NAND products. While this led to a short disruption in the memory and NAND markets for entry-level platforms, others have filled in the [β¦]
Read full article at https://wccftech.com/samsung-exiting-mlc-nand-buisness-opens-up-space-for-taiwanese-nand-maker/
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Rotten Tropes tags new movie releases with recurring narrative patterns like Power Always Corrupts, The Chosen One, Violence Gets Results, or Love Conquers All, so you can pick films by the messages you want and skip the ones you've seen too often. Mark any trope as loved or avoided, and the site surfaces matching releases while hiding the rest.
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Branded search is often treated as predictable and easy to manage. In practice, it isnβt.
PPC teams see rising CPC on brand terms. SEO teams see declining branded CTR, even when rankings hold. These issues are usually investigated separately, with different dashboards, hypotheses, and fixes.
Both signals often stem from changes within a single SERP. What look like two separate problems are, in reality, one shared environment reacting to shifts in competition and visibility.
The issue isnβt a lack of data. Most teams already have basic reports and brand monitoring tools, including PPC and SEO platforms. The problem is how the data is used.Β
To understand whatβs happening in branded search, teams must manually piece signals together. This takes time, doesnβt scale, and delays decisions.
Hereβs why that fragmentation is harmful and what to do about it.
Branded search is often described in terms of channels β paid and organic. For users, that distinction doesnβt exist.
A single SERP brings together multiple layers:
All of these elements appear at once, within the same decision-making space.
From a SERP analysis perspective, this isnβt a set of isolated placements. Itβs a dynamic environment where each element influences the others. A competitor ad above your organic result can reduce CTR. An affiliate listing can compete with your paid campaign. A review page can shift user intent before a click.
In practice, this creates a mismatch.Β
For users, branded search is a single page. Inside the company, itβs split across workflows and handled by different functions.
PPC focuses on bids and efficiency. SEO focuses on rankings and organic traffic. Affiliate activity is often tracked separately, if at all. Competitor tracking may exist, but usually within a single channel. The result is a fragmented view of what is, in practice, a shared space.
Understanding whatβs happening in branded search often requires manual effort. The data is there, but building a complete, up-to-date view of the SERP on a regular basis is time-consuming and hard to scale. That makes it difficult to understand how these elements interact β and even harder to respond to changes as they happen.
From a PPC perspective, teams focus on these signals:
At first glance, this suggests increased competition. The typical response is to adjust bids, defend impression share, or refine targeting. All of it makes sense within paid media.
But this is where context changes everything.
What PPC teams donβt always see is whoβs driving that competition.Β
Not every new entrant in the auction is a direct competitor. Often, itβs affiliate activity β partners bidding on branded terms outside agreed-upon rules. Without deeper competitor tracking, these cases can look identical while requiring different actions.
Thereβs also the organic layer. Changes in SERP structure β more ads, different layouts, stronger third-party rankings β can directly affect paid performance. Even if the campaign setup stays the same, the environment shifts. Without ongoing SERP analysis, these changes are easy to miss.
In many cases, brands arenβt just competing with others β theyβre competing with themselves. Over 40% of advertised pages already rank #1 organically (Ahrefs, 2025).
PPC teams rarely see the full page in context. They see auction data, metrics, and reports β but not always how their ads appear alongside organic results, affiliates, and other placements in real time.
But beyond missing context, thereβs a more practical limitation.
Ad platform reporting rarely explains what changed. It shows performance shifts β but not how the SERP looked to users, who appeared alongside the ad, or how placements were arranged.
This creates a gap.
Competitor tracking without context doesnβt explain the situation β it only signals change. Without broader SERP-level brand monitoring, PPC teams often optimize on partial visibility, reacting to symptoms while the root cause must be reconstructed manually.
From the SEO side, branded search issues tend to surface differently.
The most common signals look like this:
On the surface, it looks like an SEO problem. The natural response is to review snippets, adjust metadata, or check for technical or content issues.
But in many cases, performance drops arenβt driven solely by SEO factors.
SEO teams generally know that paid activity, competitors, and affiliates can influence branded search. The challenge isnβt awareness β itβs consistent visibility over time.
To understand what changed, teams need to see how the SERP looked at a specific moment:
This isnβt what standard SEO workflows are built for. Teams often have to manually check results, compare snapshots across tools, or rely on incomplete data.
Then thereβs the SERP itself. Modern branded SERPs arenβt static. Layout changes, added modules, and mixed result types can significantly affect click behavior.
Without consistent SERP analysis, itβs hard to isolate the cause. As a result, SEO teams may keep optimizing β and see no stable results.
At a glance, PPC and SEO issues in branded search may look unrelated β different metrics, dashboards, and teams. But when you look at the SERP as a whole, the connection is hard to ignore.
Studies show this overlap isnβt an edge case. Nearly 38% of websites advertise on keywords where they already rank in the top 10 organically (Ahrefs, 2025). In branded search, the overlap is even higher.
That means both channels operate in the same environment β and compete for the same user attention.
Changes within that environment rarely affect just one side:
In this context, itβs not unusual for PPC performance to decline while SEO metrics shift in parallel. These arenβt isolated issues β theyβre different reflections of the same underlying change. Yet theyβre rarely analyzed together.
The real problem isnβt visibility β itβs fragmentation.
Most teams already have access to data. Specialized tools make SERP analysis, competitor tracking, and brand monitoring possible. The limitation isnβt what can be seen, but how itβs used.
PPC and SEO operate in separate systems β different platforms and reporting environments, KPIs, and workflows. To understand what changed in branded search, teams must align manually by comparing reports, checking SERPs, validating assumptions, and sharing findings across functions.
As a result, insights are delayed, alignment lags behind SERP changes, and decisions are made with incomplete or outdated context.
Most teams donβt miss the signals β a spike in CPC, a drop in CTR, unexpected competitors in the auction. These changes rarely go unnoticed. The challenge comes next: confirming what happened and deciding how to respond.
This is where branded search performance slows. Teams dig through separate reports, trying to reconstruct what the SERP looked like at a specific moment. By the time the picture is clear β if it ever is β the window to react has already passed.
Improving performance here isnβt about adding more data. Itβs about changing how itβs collected and used.Β
With the right setup, SERP analysis becomes continuous instead of manual. Changes in branded search are captured automatically, including competitor and affiliate activity that might otherwise require manual checks, post-fact validation, or go unnoticed.
Tools for branded search monitoring such as Bluepear provide:Β
Instead of spending time collecting screenshots, comparing reports, and reconstructing what happened, the information is already structured.
This shifts the process from reactive to operational. Instead of investigating issues after the fact, teams receive a clear signal or a complete case.
This creates a reliable record of what actually happened:
Instead of scattered evidence and manual reconstruction, teams get structured, ready-to-use context.
Reporting becomes simpler. Insights can be shared across PPC, SEO, and affiliate teams without rebuilding context each time, reducing internal alignment time. Most importantly, decisions can be made faster.
With Bluepear, brand monitoring and competitor tracking become continuous. Teams receive structured signals instead of raw fragments and can act without rebuilding the situation from scratch.
To see how Bluepear can improve your workflow, create an account and start your free trial.
PPC and SEO teams donβt lack data β they interpret different signals from the same SERP. But these signals are connected. Theyβre shaped by the same changes in the search environment, even if they appear in different reports.
When SERP analysis is fragmented, itβs harder to see the full picture β and even harder to act quickly.
What makes the difference is not more data, but better coordination:
When branded search is managed holistically, teams donβt just react to performance changes β they understand what drives them and respond with clarity.
To simplify how your team tracks and responds to branded search changes, start using Bluepear to automate monitoring, capture SERP changes, and centralize evidence in one place.
Xbox still has no launch timeline for βProject Helixβ In a recent interview, Asha Sharma, the CEO of Xbox, confirmed that Microsoftβs next-generation βProject Helixβ console will be impacted by the global memory shortage. Memory pricing will impact pricing and availability. At this time, Xbox is not ready to share its launch timeline for its [β¦]
The post Memory shortages could impact Xbox βProject Helixβ pricing and availability appeared first on OC3D.
Before Zoom was popular, this tech giant had 40% of its workforce remote. Then came the reversal.
Some PlayStation users have noticed a new online DRM policy for digital games purchased on the PlayStation Store: newly purchased digital games now display aΒ "Valid Period"Β tag showing a start date, an end date, and a countdown timer. If the console does not connect to the internet within 30 days, the game's license reportedly expires, and the title becomes unplayable until an online connection is restored. Crucially, this only affects games purchased after March 2026, so titles already in players' libraries before the update are unaffected. The story broke over the weekend through Lance McDonald, the well-known modder who managed to [β¦]
Read full article at https://wccftech.com/playstation-drm-policy-xbox-2013-backlash/
ACEMAGIC has launched its brand new Mini PC, which packs AMD's Ryzen AI 9 HX 470, and starts at a price point of $759. ACEMAGIC Highlights Multi-Use Case Design of its F5A Mini PC, Which Packs AMD's Fastest Gorgon Point APU, The Ryzen AI 9 HX 470 Mini PCs make compact Agentic AI possible, and for this purpose, ACEMAGIC is releasing its brand new F5A Mini PC. The Mini PC is just as compact as one might expect, giving your PC setup a lot of breathing space. In terms of specs, the F5A comes packed with an AMD Ryzen AI [β¦]
Read full article at https://wccftech.com/acemagic-palm-sized-f5a-mini-pc-pairs-amd-ryzen-ai-9-hx-470-oculink-dual-usb4-759-usd/
The PlayStation 6 is said to deliver 10x ray tracing performance over the base PlayStation 5, but the real-world FPS gain will be closer to 3x in games that don't use much ray tracing. However, these improvements could allow the system to run games with path tracing at 30 and even 60 FPS, according to the tech experts at Digital Foundry, as Codemasters managed to get a path-traced game running on PlayStation 5 Pro at 30 FPS with some computational headroom to boot. During the latest episode of their weekly podcast, the tech experts went over the F1 25's Path [β¦]
Read full article at https://wccftech.com/playstation-6-path-tracing-60-fps-rdna5-built-for-it/
High-Bandwidth Flash or HBFD, the memory that offers more capacity than HBM, will not be used by NVIDIA; instead, Google is going to be a key customer. NVIDIA To Keep on Using HBM, HBF Not Yet In Consideration, But Set For Sampling Later This Year NAND DRAM has seen big adoption with the recent AI push. While primarily used for storage, such as SSDs, the upcoming flash memory technology could play a major role with HBF (High-Bandwidth Flash), the next generation NAND DRAM tech that bridges the gap between HBM and NAND Flash. HBF is being co-developed by SanDisk and [β¦]
Read full article at https://wccftech.com/nvidia-not-interested-in-hbf-memory-despite-4tb-stacks-dwarfing-hbm/
Flydial provides a dedicated outbound AI cold caller that pitches your product, handles objections, and books meetings around the clock. Upload contacts from CSV or your CRM, pick a voice and persona, and sync calendars to auto-schedule demos. Track performance with real-time analytics, run multiple parallel dialing lines, and tailor tone and messaging to your market. Pricing starts at $10/month plus per-minute usage, letting you replace or augment SDRs at a fraction of the cost.
R&D Tax Credits for Tech Companies
AI-powered payments and conversational commerce
A travel app that learns how you travel from your inbox
Accounting, finally without errors
AI-Native Data Infrastructure for Spatial and Physical AI
Valveβs next-gen Steam Deck is in development, but it wonβt launch soon Valve has confirmed that its Steam Controller is launching next week, but thatβs not the only piece of hardware that Valveβs working on. The Steam Machine and Steam Frame are still due to launch this year, and Valve is already working on its [β¦]
The post Valve is βhard at workβ on Steam Deck 2 appeared first on OC3D.
Following Final Fantasy VII Remake Intergrade's release on Nintendo Switch 2 and Xbox consoles back in January, Square Enix will soon allow owners of these systems to continue Cloud's journey with Final Fantasy VII Rebirth from June 3. However, the first steps of this second journey can be taken right now thanks to a meaty playable demo that has gone live today. Unlike the PlayStation 5 demo, which only covered Chapter 1 of the full game, the Nintendo Switch 2 and Xbox Series X|S demos are packed with more content, as it lets players not only experience the famous Nibelheim [β¦]
Read full article at https://wccftech.com/switch-2-final-fantasy-vii-rebirth-demo-silence-doubt/
AMD AI PCs are seeing massive adoption in the enterprise segment as Agentic AI rages on to be the next frontier of computing. Only 4% of Organizations Don't Have Plans To Deploy AI PCs; the rest have already deployed AI PCs, as AMD leads the charge in the AI PC Segment The focus on localized AI and the rise of Agentic AI have rapidly boosted the adoption of AI PCs. This has led AMD to see a big demand for AI PCs in the Enterprise segment as organizations shift their workflows, aligning with future AI requirements. AI is reshaping how [β¦]
Read full article at https://wccftech.com/amd-says-ai-pcs-are-the-new-enterprise-standard-for-agentic-ai/
Resident Evil Requiem has been such a smashing success with its seven million units sold in less than two months, the fastest ever in the horror franchise, that it even caused the upward revision of CAPCOM's fiscal year 2026 forecast from a net profit of $319.9M to $341.8M (+6.9%). Now, all those fans who loved the game are waiting for the first post-launch content drop: the mini-game, which will be released as part of a free update. Well, in an interview with Japanese website Denfaminicogamer, Game Director Koshi Nakanishi and Producer Masato Kumazawa have teased that it might be released [β¦]
Read full article at https://wccftech.com/resident-evil-requiem-mini-game-release-chapter-2-scrapped/
Major CPU manufacturers such as Intel, AMD & MediaTek are boosting their CPU production, but prices continue to rise. CPU Makers Boost Production, But This Won't Change Current Pricing Trends & Shortages Agentic AI demand has prompted a CPU shortage that has further led prices to increase. As demand swells, the GPU to CPU ratio has fallen from 8:1 to 4:1, and is on the path to hit 1:1 sooner or later. As processors continue to face supply constraints, multiple chipmakers are now boosting their production capacities. Supply chain sources indicate that after Intel decided to prioritize its limited production [β¦]
Read full article at https://wccftech.com/intel-amd-mediatek-are-boosting-cpu-production-prices-continue-to-increase/
Map Your Video is a video planning tool that helps short-form video creators turn their ideas into a clear, structured shot list before they pick up their phone. Instead of hitting record and hoping for the best, you map out each frame of your Reel or Short so you know exactly what to film and in what order. When the map is done, you open your shot list and film scene by scene. It's built for ADHD solopreneurs who have many ideas but get stuck in the stall-record-delete loop. The problem was never the idea, but not knowing what to film. Map Your Video fixes that before you press record.
FRNTIR is buyer-funded car pricing intelligence with zero dealer money or kickbacks. You get independent market data, leverage points, and a negotiation playbook so you know what to pay and when to walk.
Start free with Match My Ride (top 3 AI-matched picks and Decision Guide) and the Purchase Planner. Upgrade to the $49 Negotiation Package (VIN pricing and dealer playbook) or $99 Scout (AI ranks your top 3 picks and selects the best). It helps recover the $3,000+ buyers lose to dealer markups.
Ranking management solution that boosts your OTA visibility
Visa Applications made easy
Syndication and Intelligence Layer for Agentic Commerce
Where sales teams and AI agents work side by side.
A relocation and immigration platform for tech talent
File your UK Self Assessment in 15 minutes with AI
Marketing intelligence for the Agentic AI era
Intel & Microsoft have joined hands to scale up Azure Local deployments from 100s to 1000s of servers using Xeon 6 CPUs. Microsoft & Intel Scale Up "Azure Local" From 100s to 1000s With Xeon 6 CPUs, Adjusting To User Needs Without Architectural Redesign Press Release: Azure Local is the foundation for Microsoftβs Sovereign Private Cloud, allowing organizations to run cloud-consistent infrastructure on hardware they own and operate within their sovereign boundary. It supports deployments across connected, intermittently connected, or fully disconnected environments. With Azure Local disconnected operations, customers retain the ability to apply policy enforcement, role-based access control, auditing, [β¦]
Read full article at https://wccftech.com/intel-xeon-6-accelerate-amazons-azure-local-scaling-deployments-to-1000s-of-servers/
Screenplay Assistant is a writing tool for people who have always wanted to write a screenplay. You type your story scene by scene in your own words and the app turns it into a real, properly formatted screenplay. No learning curve or expensive software.
It is the first app from PLAYCODE3.ai, a small studio building everyday tools by hand. Currently in closed beta. Request access to be one of the first writers in.
MediTailor delivers personalized, AI-generated meditation sessions that adapt to your mood, goals, and progress. It generates each session from scratch, so no two sessions are the same. Built on neuroscience and cognitive research, MediTailor guides you through goal-oriented journeys and tracks your emotional progress while keeping your words private.
Autopilot for your crypto and tokenized portfolio
Top-tier AI video generation and editing from Alibaba ATH
Draw a gesture for your Mac to execute
Query data to build dashboards and generate detailed reports
Compete and Build your Community with Challenges
Netflix killed comments. We brought them back.
Autonomous agent that communicates results like a human
Recover abandoned carts with AI via WhatsApp
Turn expertise into 24/7 client-facing AI voice agents
AI agent that builds skills from every task you give it
Reverse engineer any GitHub repo into an agent-ready plan
Private, local AI transcription for your Mac
Shared context that turns AI into your teammate
A clean Markdown editor with a smooth, block-based UX
A 3D portrait lighting simulator
Your AI On-call Engineer
Learn algorithms by watching them run
Self-hosted AI workflow automation with agents, RAG, and MCP
A shared bucket list with active scheduling and planning
AI employees who build their own knowledge base
World's first conversational AI fluency and know-how test
Multimodal RAG platform, from POC to production in minutes
Edit Videos and Design Images with Claude Code and Codex
Live captions & translation for Google Meet, Zoom and Teams
See your AI agents think. Reasoning, tool calls & decisions
One-shot bigger coding tasks
Test camera features directly in the iOS simulator
Open-source local AI that learns how you edit video
An AI agent matching candidates to the right roles.
Pull real-time data from any social platform via API.
Grow your revenue faster with signal agents
Turn your data into insights
Know if your internet is flaky before your next call
The portable vector database for AI agents beyond the cloud
Your ideas don't wait for you to sit down at a desk
A CLI agent that keeps working when you close your laptop
Private family hub for schedules, health, and shared bills
Self-driving AI observability and evals for agents
Gradients that don't look like defaults
Heroku for AI prompts
Make guaranteed money from prediction markets
Connected intelligence for Governance & Sustainability
AI match capture and highlights for youth and amateur clubs
The enterprise layer that unlocks MCP at scale
The medical receptionist in your pocket
AI agents for accounting firms
Multi-channel listing sync for luxury fashion resellers
Life changed. Your money didn't get the memo.
The permission layer for agent-driven finance
Write up to 10x faster with an ethical AI writing partner
Office Solver is an all-in-one business management platform designed for small to midsize businesses and startups that want to grow without juggling multiple tools. Instead of using separate systems for CRM, HR, payroll, and operations, Office Solver combines everything into one simple, connected platform. Manage customers, your team, and daily operations from a single dashboard, so you can focus on growth, not admin work. With over 30 integrated applications, Office Solver helps you run and scale your business efficiently by managing hiring, storing employee records, running payroll, overseeing projects, sending invoices, and automating workflows.
B3OS lets you build deterministic onchain workflows that connect wallets, smart contracts, and 2,000+ tools. Use a visual block builder and an AI copilot to design, test, and deploy flows backed by pre-audited contracts, sealed sandboxes, and real-time logs.
The platform self-heals on failure, enforces secure payment logic, and guarantees same inputs produce the same outputs. Scale production automations with role-based controls, deep crypto context, and precise, repeatable execution.
Consumers in India can now save their Aadhaar Verifiable Credentials in Google Wallet and digital IDs expand to more countries.
FlowRank is an AI article generator that turns your website into a daily content engine. It analyzes your site, maps your market positioning, and selects topics your audience searches for, then delivers research-backed, competitor-aware drafts to your dashboard each morning. You can review them in a calendar workflow, edit in the built-in editor, and export Markdown to your CMS or auto-publish via webhook to grow organic traffic with articles aligned to product goals.
DunnAI reads the decline code and decides what to do next. Expired cards and insufficient funds are different problems, so your customer shouldn't receive the same response. Timing issues get smart retries, while communication problems get personalized outreach matched to the actual reason the payment failed, sent in your brand's voice. Connect your Stripe account in 5 minutes. Free until DunnAI recovers $49, then $49/month.
Four-Leaf is an AI career platform that helps you tailor resumes and cover letters to each role, practice voice mock interviews, and negotiate offers with confidence. It surfaces matching jobs, optimizes your LinkedIn profile, assists with emails, and tracks applications with feedback. Start with a 7-day free trial and get every feature for $20/month.
Google is testing "Ask YouTube," a conversational search feature that returns AI summaries with cited videos. Available to US Premium users.
The post Google Tests βAsk YouTubeβ Conversational Search Experiment appeared first on Search Engine Journal.
Microsoft previewed four new AI reporting features for Bing Webmaster Tools at SEO Week, including Citation Share and grounding query intent labels.
The post Bing Previews AI Citation Share For Webmaster Tools appeared first on Search Engine Journal.
The app is experimenting with an option that could allow users to react to particular parts of a post by attaching publicly highlighted reactions.
The companyβs partnership with Albertsons Media Collective will bring more precise audience targeting to YouTube and Display 360 campaigns.
Advertisers will be able to expand their campaigns to consumersβ home TV sets through enhanced CTV spots.
A new partnership with Overview Energy will reduce downtime for solar facilities, while a deal with Noon Energy is designed to expand storage capacity.
The National Development and Reform Commission ruled that the $2 billion deal was invalid, and ordered the companies to unwind.
InekIA is an augmented strategic intelligence platform that turns scattered open-source signals into actionable analysis. It aggregates over 300 sources, scores criticality, impact, and urgency with the Kairos engine, producing board-ready briefs in about 60 seconds. Teams monitor competitors and geopolitics, investigate risks and opportunities, and export structured recommendations to PDF, PPTX, Notion, or Slack. Modules like Vigia, Shadow Broker, Stratebox, and Intel Board cover the full cycle from detection to decision.
Convertful is a 100% free, browser-based suite of 56+ tools to convert, compress, and edit files. Handle images, PDFs, videos, audio, and text all on your device with no uploads, no limits, and no file size caps. Sign up for free to unlock unlimited daily use.
Everything runs locally for instant results and strong privacy. Resize or crop images, remove backgrounds, merge or split PDFs, trim or convert videos, extract audio, and moreβall in one fast toolkit.
Ginny Marvin didnβt get into PPC because she had a grand plan.
She got into it because she was ready to start again.
After years working in print publishing and ad sales marketing, Marvin found herself at a career pivot point. A startup magazine she had helped launch folded, and she decided it was time to move fully into digital.
That meant going from marketing director to entry-level applicant.
That reset eventually led her into search marketing, Search Engine Land, and later Google, where she is now Google Ads Liaison.
In this interview, Marvin looks back at how paid search has changed, what marketers still misunderstand, and why the next phase of search will reward curiosity more than control.
Marvin started on the SEO side at a small agency.
Then the paid search manager went on holiday.
She took over the campaigns temporarily β and immediately saw the appeal.
Coming from print, where measurement was slow or sometimes impossible, PPC felt almost instant. You could launch, spend, measure and see action quickly.
That speed changed everything.
For Marvin, PPC made the connection between marketing activity and business results much clearer than SEO did at the time.
When Marvin entered the industry, Google wasnβt the only serious search player.
Yahoo was still a major force, and Microsoft was part of the mix. But over time, Google pulled ahead.
Marvin believes the difference was focus.
Google kept improving the product, launching new features and iterating faster than competitors. It became increasingly clear that Google was building around advertiser needs and pushing the industry forward.
Todayβs PPC marketers may complain about manual work, but the early days were on another level.
Campaigns were built around huge keyword lists, endless permutations and highly granular structures. Advertisers spent hours creating keyword combinations and negative keyword lists.
It gave marketers a sense of control, but it also forced them to build campaigns around how the platform worked β not necessarily how the business worked.
That, Marvin said, is one of the biggest changes in paid search: campaigns now start more naturally with goals.
When Search Engine Land launched, Marvin was still early in her search career.
But it quickly became the place people went for search news, updates and expert analysis.
What made it valuable wasnβt just the reporting. It was the mix of fast news, contributed columns and practical insight from people doing the work.
For Marvin, Search Engine Land played a major role in professional growth across the industry because it made knowledge easier to share.
One thing Marvin repeatedly came back to was the generosity of the search community.
From the early days, practitioners shared what they were testing, what worked, what failed and what others should watch for.
That culture of learning helped define the industry.
It also shaped Marvinβs own career, both as a journalist at Search Engine Land and now in her role at Google.
Marvin believes one of the biggest misconceptions about AI in search is that it suddenly appeared.
Machine learning has been part of Google Ads for years, powering changes such as close variants, Smart Bidding and automation.
What changed recently was the speed of progress driven by large language models.
AI did not arrive overnight. But LLMs accelerated the shift dramatically.
For Marvin, the biggest change is not just what Google can do.
It is how people search.
Queries are getting longer and more complex. People are searching through images, voice and multimodal inputs. Search can now understand intent without relying only on typed keywords.
That means advertisers need to think beyond the final conversion moment and understand the full customer journey.
Marvin does not think the definition of success in search has changed.
It still comes down to business outcomes.
What has changed is marketersβ ability to measure those outcomes and connect campaign activity to business goals.
That makes data, measurement and first-party signals more important than ever.
When asked what kind of marketer will succeed in the next phase of search, Marvin pointed to curiosity.
The best advertisers will be those who keep learning, watch how customers behave and adapt before they are forced to.
She compared it to mobile, where consumers moved faster than advertisers did.
The same thing is happening with AI.
Marvinβs reality check for the industry was simple.
PPC marketers often say they love change, but many resist every major shift when it arrives.
Her advice is to take a longer view.
Many of the changes that feel sudden have actually been building for years. Automation, AI, broader intent matching and full-funnel campaigns have all been moving in this direction for a long time.
Marvinβs message is not that every new feature will work immediately.
It is that marketers should not write things off forever because they tested them once months or years ago.
Platforms evolve quickly. Capabilities improve. What failed before may work differently now.
For advertisers still holding tightly to old ways of working, the next phase of search will be harder.
Looking back, Marvin said she is proud of the search community itself.
Its willingness to share, learn and support each other has made the industry stronger.
She also sees her role, both at Search Engine Land and Google, as being a resource for marketers.
A huge milestone was seemingly achieved by Apple earlier this month when the iPhone FoldΒ was rumored to have entered trial production at Foxconn. Unfortunately, the device still has time to reach this stage as one tipster reveals an update thatβs going to put a frown on those eagerly waiting for its arrival. According to the latest rumor, Apple hasnβt even begun the prototype manufacturing of the iPhone Fold, suggesting that there are still some tweaks required in the deviceβs design. A new rumor highlights more complications that Apple could potentially face with the iPhone Fold design At the start of [β¦]
Read full article at https://wccftech.com/apple-iphone-fold-progress-unimpressive-tipster-shares-disappointing-update/
GoDaddy accidentally transferred someone's domain name to someone else then refused to fix the problem.
The post GoDaddy Transferred A Domain By Mistake And Refused To Fix It appeared first on Search Engine Journal.
Editorβs note: This research was conducted by Exploding Topics, the trend discovery platform owned by Semrush, and is republished here with permission. Data is drawn from a proprietary survey of 1,009 US consumers. Full methodology appears at the end of this article.
More than three in four consumers have used AI to help with shopping or purchasing decisions in the last six months, according to new research from Exploding Topics.Β
AI tools like ChatGPT and Google Gemini have been absorbed into weekly shopping routines. The technology has rapidly become a staple of product research and price comparison, for everything from clothing to groceries.
But at the same time, we found significant and widespread discomfort about the next chapter in AI commerce.Β
The very same people who are eagerly embracing AI to shop often draw the line at empowering AI to spend. βSkepticismβ is the prevailing attitude about tools like ChatGPTβs short-lived Instant Checkout, while even something as simple as storing card details with an AI chatbot makes consumers uncomfortable.
Looking ahead, shoppers expect AI to become ever more prominent in their buying habits. But this research highlights some significant barriers that will need to be overcome before that can truly happen.
Download the summary of our findings.
See this yearβs biggest emerging trends.
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To get a baseline, we first asked respondents how they would describe their use of AI generally. This yielded a striking response.Β Of the 1,000+ people we surveyed, almost half reported using AI frequently. But more eye-catchingly, only 9.81% had never used an AI tool.
High adoption was a recurring theme when we asked about AI commerce specifically. 43.21% of consumers are using AI to help with shopping at least once a week, with well over half of shoppers using the technology at least monthly. Among βfrequentβ AI users, only 2.76% had never used the technology to help with shopping or purchasing decisions. That figure rose to 22.4% overall, leaving over three-quarters of consumers who have at least tried using AI for shopping. Even among the over-60s, more than half (52.78%) reported using AI for shopping in the last six months. 18.75% of them use AI shopping tools weekly or more. We put the next set of questions exclusively to the 77.6% of respondents who have adopted AI commerce, in order to better understand how they are using AI to shop. βAI commerceβ is a broad term that can capture a wide range of consumer activities. We wanted to find out exactly how people are incorporating AI into their purchases. Product research emerged as the leading use case, adopted by more than two-thirds (68.5%) of shoppers. More than half (55.19%) also reported using AI for finding the best price/deals. Deciding between brands, getting gift ideas, and summarizing customer reviews were all also reasonably common (>35%). Interestingly, shoppers also have clear preferences about what they will buy with the help of AI. Consumers are most likely to employ AI assistance when browsing for clothing or technology. This data really underlines how embedded AI has become in shopping routines already. 44.62% have used it for something as mundane as grocery shopping.Β More βexceptionalβ and potentially expensive purchases, where you might intuitively assume that consumers would turn to AI for a bit of extra assistance, tend to be less common use cases. Furniture (29.62%) and jewelry (28.08%) were among the least popular responses. ChatGPT still enjoys the largest market share across most consumer AI functions, and shopping is no different. 77.56% of shoppers use ChatGPT when they want AI assistance. The prevalence of Gemini is perhaps more surprising. 58.21% of shoppers reported using Googleβs AI, well over twice as many as the next most popular tool. Of course, Google has embedded Gemini in AI Overviews and AI Mode. Its search engine has long been the go-to tool for manual product research, so perhaps it should be no great surprise that its AI has now captured a lot of the same market. But intriguingly, Gemini usage is actually most saturated among people who use AI to write shopping lists. 75.86% of AI list-writers report using Googleβs tool to shop (compared to 60.49% of those who use AI for product research). Thatβs not to say Gemini is necessarily being used to write these shopping lists. But the expected skew toward Gemini among those who reported using AI for product research simply did not materialize, suggesting that shoppers may well have a genuine preference for Googleβs AI beyond just its embedded search features. Fewer than one in five people using Claude for AI commerce was also notable. Anthropicβs tool actually overtook ChatGPT in an enterprise context last year, but adoption for everyday consumer tasks is still lower than competitors. Grok remains the most highly gendered tool. Itβs used by 31.98% of male shoppers, but just 15.16% of women. Across the board, men were more likely than women to use AI tools for shopping. However, ChatGPT usage was close to equal (78.05% of men vs 77.51% of women). It is remarkable how quickly AI has embedded itself as a standard shopping companion. Among those who are now using the technology, 39.1% say they use AI for shopping βmuch moreβ than they did six months ago.
A further 28.97% of consumers are using AI tools for shopping βa bit moreβ in the last half-year. Only 6.02% have decreased their usage. Middle Atlantic residents stand out as the keenest adopters. Almost half (49.04%) are using AI for shopping much more in the past six months, and close to eight in 10 (78.98%) have at least somewhat increased their usage. West North Central is the least enamored with the technology, with over 13% using AI for shopping less frequently than they did previously. Nationwide, the impact of the technology on purchasing habits is stark. 92.54% of consumers say it is at least possible AI has directly influenced them to buy something they wouldnβt have otherwise purchased.
Almost seven in 10 (68.64%) can definitely remember being directly influenced to make a purchase. That includes 36.89% who say they have been influenced βmany timesβ by AI. This trend is most pronounced among the highest earners. 61.9% of consumers with a household income of $125,000 or higher have made AI-influenced purchases βmany times,β and only 13.19% cannot recall any such purchase. Why the increased uptake?
Although the speed of AI shopping adoption is startling, the reasons behind it are ultimately no mystery. Quite simply, the majority of people who have tried using AI tools have found that they make product research easier. 37.18% say that AI makes shopping research much easier. A further 40.9% say AI makes it somewhat easier.Β
For the most part, consumers also trust AI as a shopping tool.Β Only around one in five shoppers say that they trust AI completely. But that rises above 60% when also counting those who mostly trust AI as a shopping tool, with some manual fact-checking. In many ways, this is the expected pattern, given that the question was only put to people who have tried using AI as a shopping tool. Those with the least trust may not have tried it in the first place. However, itβs quite a sharp contrast from another of our original surveys, assessing attitudes to AI Overviews. In that context, 82% of respondents were at least somewhat skeptical of the outputs, and yet the vast majority continued to rely on them anyway (without routinely checking sources) for the sake of convenience. When it comes to shopping, users seem to have more genuine faith in AI outputs: They are using it not only for its convenience, but because it generally works well. That could be a sign of general AI improvements in the ~nine months between the surveys, or it may be a sign that commerce is an area where the technology can really excel for consumers. So most people are using AI commerce tools, and uptake has only gotten higher in the last six months. But interestingly, there is no clear consensus about how to use AI for shopping. We know that product research and price comparison is popular. But that doesnβt tell us too much about what a typical AI-assisted purchasing journey actually looks like. We gave respondents four options: There was an almost exactly even split between the first two options. 44.8% start on retail websites and then add in AI, while 44.03% use AI as a starting point before looking externally. This is notable for retailers, and underlines the paramount importance of Generative Engine Optimization (GEO).Β A huge base of potential customers are using AI as a starting point, so it is imperative that your brand gets organically mentioned. And for those starting on your website but then double-checking with AI, brand sentiment could make or break a sale. The other thing that stands out from this data is that using AI for the entire shopping journey is still a fringe use case. Only 8.99% of users are using AI as their only source before purchasing, and only 2.18% are checking out via AI.Β In Part 2, weβll examine the reasons why. Questions in the second part were put to all respondents, to get a better idea of the current attitudes held by both adopters and non-adopters of AI commerce.Β Spot the next βAI commerceβ 12 months early. Exploding Topics Pro tracks 11M+ trends with search volume, growth curves, and category filters. Start your 7-day free trial.Β
Regardless of which stage in the shopping process users introduce artificial intelligence, the final step is nearly always external checkout. Given that consumers are clearly keen on using AI as part of the commerce journey, tools that eliminate this point of friction make superficial sense.Β That was the idea behind Instant Checkout from ChatGPT; you can do all of your research within the app, and then complete your purchase there as well. In effect, the AI agent completes the transaction on your behalf.Β OpenAI isnβt the only one to build something like this. Visaβs Intelligent Commerce is a similar payment-side solution, while Google has developed its own AP2 protocol for βagent-led payments.βΒ But awareness of new and upcoming tools that allow you to checkout from directly within an AI interface is quite low. 42.83% of people were not at all aware, with a further 23.01% only βvaguely aware.βΒ Unsurprisingly, those who use AI for shopping weekly or more are most likely to be βvery awareβ of Instant Checkout and similar tools (63.3%). But that drops to 25.19% among monthly users, and just 11.11% among those who have used AI shopping tools βa few times.βΒ Having been told about the existence of these tools, the response could best be described as mixed.Β From a preset list of options, βskepticalβ was chosen most often (41.08%), followed by βsuspiciousβ (33.1%). But respondents could pick more than one answer, and βexcitedβ (31.61%), βhappyβ (24.33%), and βimpressedβ (24.03%) were the next most-common answers. Those who selected to fill in an answer of their own were overwhelmingly negative. Responses included βhunted/preyed upon,β βterrified,β βwary,β and βnot interested.βΒ Crucially, there was significant negativity toward Instant Checkout even among those who are already routinely using AI tools for shopping.
29.82% of the most regular AI shopping users said they were suspicious of tools like Instant Checkout, and 29.59% reported being skeptical. Among monthly users, skepticism was the single most popular attitude (37.04%).Β Meanwhile, only 2.22% of the people who arenβt currently using AI to shop reported being excited at the prospect of agents being able to carry out purchase orders.Β In fact, the idea of AI purchasing power is actively making non-users less likely to try AI for shopping.Β
44.89% of AI shopping non-adopters are βmuch less likelyβ to try the technology as a result of these new tools. Over half are at least a bit less likely, and only 7.11% are more likely.Β On the other hand, the most regular existing AI shoppers anticipate that tools like Instant Checkout will further increase their usage. 72.71% say that the innovations make them at least somewhat more likely to shop with AI more regularly. Outside of power users and non-users, indifference is more common. 48.89% of monthly users anticipate Instant Checkout (and similar tools) will make no difference to their usage, as do 52.17% of occasional users. And it seems OpenAI must have reached a similar conclusion. Mere months after launching Instant Checkout, it has rowed back on direct shopping features, doubling down on the discovery side of things. One of the biggest hurdles when it comes to further integrating AI into commerce is that most people donβt feel comfortable trusting chatbots with their card details in order to make direct purchases easier in future. In total, 51.45% of consumers are at least somewhat uncomfortable at the idea of AI tools storing their card details. Only around 1 in 4 are βvery comfortable.βΒ
As well as being the most popular response overall, βvery uncomfortableβ also cut across age groups to an unexpected degree. More than a third of consumers aged 18-29 said they would be very uncomfortable storing card details with an AI tool, despite being digital payment natives. Even among the most frequent AI shoppers, barely more than half (50.69%) said they would be βvery comfortableβ with AI tools storing their card details. That dropped dramatically to 18.52% among monthly AI shoppers, 7.25% among those who use the technology occasionally, and just 0.89% among those who donβt currently use AI to shop at all. Pacific residents are most likely to trust AI tools with their card details, with 64.48% at least somewhat comfortable, while the Middle Atlantic once again stands out as a distinctly pro-AI region. New England is the most distrustful (58.53% at least somewhat uncomfortable). Who does AI commerce serve?
Tied in with this discomfort about payment details is the fact that consumers are skeptical of whether they are truly the intended beneficiaries of AI commerce technology. Only 14.16% of respondents said consumers are the ones being primarily served by AI shopping tools right now.
The most common answer (27.52%) was that these tools are made to serve the interests of AI companies themselves. Brands and advertisers (27.32%) was another popular response. And even among the most frequent users of AI shopping tools, only 23.85% of consumers believe they are the ones whom the tools are primarily serving. These power users were more likely to say that brands and advertisers are the ones being served. Among less frequent users, skepticism rises sharply, to the point where just 2.22% of non-users believe AI shopping tools are primarily serving consumers right now. βThe mode amount a consumer would authorize AI to spend autonomously is $0.β Given that some degree of skepticism cuts across multiple demographics, it isnβt too surprising to learn that consumers remain reluctant to empower AI to spend vast sums autonomously.Β However, the extent of the reluctance is eye-catching: the mode amount a consumer would authorize AI to spend autonomously is $0. Specifically, we asked how much consumers would trust AI to spend in the scenario where they were instructing an AI agent to buy something once it became available. This hypothetical aligns closely with the stated use cases of the latest AI commerce innovations, including Googleβs AP2 Protocol: But right now, our survey shows the appetite is simply not there. 31.21% of consumers would not allow any autonomous AI spend at all, 17.45% would cap it at $20, and 20.74% would cap it at $50. This immediately all but wipes out another of Googleβs proposed use cases: the example of instructing an AI to buy concert tickets the moment they go on sale. Assuming most such transactions would exceed $100 total, only 11.71% of consumers would currently be comfortable trusting AI with the purchase. AI companies even face a hard sell among their regular users. 51.84% of weekly AI shoppers would cap autonomous AI spend at $50 or less, as would 67.41% of monthly shoppers. Barely more than one in five (20.87%) of the most frequent AI shopping users would be prepared to authorize a spend over $100. Unsurprisingly, the highest earners are the most likely to trust AI to make bigger purchases. But even then, 68.57% would cap agents at $100 or less: 1/2000th of their annual household income at most. The tension at the heart of these results is that despite this reluctance to sanction AI spend, there is widespread belief that AIβs role in commerce will continue to get bigger. More than half of people (55.83%) think AI will play a bigger role in how they shop in five yearsβ time. Only 12.37% believe it will play a smaller role.
Even among non-users, almost a third (32.44%) predict that AI will play an at least somewhat bigger role in how they shop in five yearsβ time. And 74.77% of the most frequent AI shoppers believe the technology will take on an even bigger role in how they make purchases. A future of expanded AI commerce would come with further questions. For instance, a landscape of ads and sponsored links has the potential to disrupt the quality of AI outputs. However, most consumers seem satisfied that increased AI shopping features wonβt actively impact the quality of responses. In fact, 48.35% believe the rollout of more shopping capabilities and the integration of ads will actually improve the overall standard of AI answers. Only around one in 10 of the most frequent users predict that ads and shopping features will make AI outputs worse, a finding which AI companies could well interpret as something of a green light to push ahead with this kind of monetization. The final sure sign that AI commerce will continue to grow is simply that shoppers like it. Even if there is some skepticism about whether consumers are truly the main beneficiaries, 55.83% agree that AI features make shopping at least somewhat better for consumers overall.
Among users and non-users alike, fewer than one in five people think AI has made the shopping experience any worse. That falls below one in 10 among those who have used the technology at all within the last six months. Though there are disagreements about what direction this burgeoning technology should take next, it looks increasingly clear that AI shopping is here to stay. If youβre a retailer, a tool like Semrush Enterprise AIO is more important than ever. 77% of your customers are using AI in their commerce journeys, and the visibility and reputation of your brand has the potential to transform your bottom line. This survey was completed by 1,009 respondents in total. After the general questions about frequency of AI usage and AI shopping usage, non-users were skipped for the remainder of Part 1, before being reintroduced for Part 2 (where the opinions of non-users offered valuable insights). All respondents were from the US, spanning all regions (there were no respondents from the US Territories). 56.03% of respondents were female, and 43.97% were male.Β 10 different household income bands were represented, from $0-9,999 up to $200,000+. The median income range was $75,000-$99,999. The age range was as follows:Β Want the key stats in a one-pager? Download the full summary.
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Part 1: The AI Commerce Surge
AI is an increasingly ubiquitous shopping tool
How are consumers using AI to shop?
The AI shopping tools of choice
Evolving AI shopping habits
The typical AI purchase pipeline
Part 2: The AI commerce red line
Instant Checkout: Donβt know it, donβt like it
Distrust of AI companies with payment data
β Exploding Topics, 2026 consumer AI commerce survey
Hard spending cap for autonomous AI purchases
Agentic commerce is here to stay
Methodology
A company handing out freebies can attract a large customer base momentarily, which may look excellent on Verizonβs earnings call, but Chief Executive Officer Dan Schulman no longer believes that this approach leads to increased retention. In fact, the CEO has altered his stance on where the carrier giant is lacking, and thatβs in customer service, stating that if feedback was taken seriously and acted upon, costs could have been reduced substantially and profits could have risen. Fortunately, Verizon appears to have a solution to this. One problem that Verizon has tackled is providing customers with wireless extenders called femtocells [β¦]
Read full article at https://wccftech.com/verizon-ceo-does-not-believe-that-free-phones-make-up-for-poor-service/
This past weekend was riddled with news, and not just because Creative Assembly finally dropped a teaser for Alien: Isolation 2 after more than a decade of fans waiting for a sequel. There was a shooting at the White House Correspondents' dinner, and in the barrage of information that has come up about the suspect responsible, we learned that Cole Tomas Allen, at least once in his life, dabbled at being an indie developer and even published a game on Steam before allegedly making an attempt on President Donald Trump's life. The game in question is called Bohrdom, and before [β¦]
Read full article at https://wccftech.com/donald-trump-attempted-shooters-game-bohrdom-pulled-from-steam-by-valve/
Google and NVIDIA have teamed up to provide users with access to as much as one million NVIDIA GPUs to power up the freshly launched A5X instances. The announcement is part of the pair's latest collaboration to reduce inference costs and improve token throughput. Their A5X system relies on NVIDIA's network accelerators that enable the development of single and mutli-cluster computing infrastructure for AI workloads. The A5X Instance: Purpose-Built for Agentic AI Workloads The A5X instances are Google's latest products that are designed specifically to run agentic artificial intelligence workloads. They are part of Google's AI Hypercomputer portfolio which also [β¦]
Read full article at https://wccftech.com/nvidias-rubin-lands-inside-googles-virtual-machine-stretching-multi-site-clusters-to-nearly-1-million-gpus/
Elaborate scams can and do mimic official channels. Even so, no one should be able to send you notifications via the Verizon app. And yet, this is exactly what appears to be happening, at least as per anecdotal evidence gleaned from a troubling recent incident. Scammers are now apparently sending Verizon customers notifications from the official app, adding a convincing sheen of authenticity to their elaborate fraud schemes A Redditor has just detailed their harrowing experience as the supposed mark in an elaborate Verizon-linked scam. The story begins on a recent Friday, when our Redditor, who goes by the username [β¦]
Read full article at https://wccftech.com/a-verizon-customer-tricked-into-receiving-a-1500-ipad-pro-13-as-scammers-hijack-the-official-apps-notifications/
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On PPC Live The Podcast, I spoke with Peter Bowen, a Google Ads specialist with nearly 20 years of experience and a strong focus on B2B lead generation.
Pete shared two major lessons from his career: always check the basics, and never assume the systems around your ads are working just because the campaigns look fine.
Pete Bowen shared an early mistake where a South African clientβs account was set up in the UK, defaulting the currency to pounds instead of rand. That simple oversight led to spending roughly 10 times the intended budget, delivering great results at first β but ultimately setting unrealistic expectations and losing the client.
The takeaway from that mistake was to formalise learning into process. Adding something as simple as a currency check to a setup checklist ensures that once a mistake is made, it doesnβt happen again β turning painful lessons into repeatable safeguards.
Beyond setup errors, Pete highlighted a more subtle but common issue he calls βsystem decayβ β where the infrastructure connecting ads, tracking tools, CRMs and sales processes gradually breaks down without anyone noticing.
When conversion data stops flowing properly, Googleβs algorithms lose the feedback they rely on to optimise. This can lead to reduced spend, poor performance or campaigns that suddenly stop delivering β even if nothing appears wrong inside the platform.
One of the biggest mistakes advertisers make is focusing only on what happens inside Google Ads. Strong performance depends on the entire journey, from click to conversion to revenue, and any break in that chain can undermine results.
When tracking fails, the priority is to fix the root issue quickly and, where possible, use data exclusions to prevent bad data from influencing optimisation. Longer term, building monitoring systems that flag issues early is essential to avoid repeat problems.
Pete also pointed to a common but damaging mistake: optimising campaigns for clicks rather than outcomes. Without proper conversion tracking, advertisers can end up driving large volumes of traffic that never turn into leads or sales.
Automation like Performance Max can amplify this issue, as it will follow whatever signals it receives. Without accurate conversion data, it can scale irrelevant traffic quickly, making strong tracking a prerequisite before leaning into automation.
Googleβs bidding systems are powerful but literal β they optimise toward whatever you define as success. That means advertisers need clear goals, reliable data and sensible guardrails, such as CPC limits, to avoid extreme or inefficient outcomes.
With newer tools like AI Max, the risk isnβt testing too early β itβs testing without a clear definition of success. Metrics like impressions and clicks are not enough; advertisers need to measure impact on qualified leads, sales and revenue.
Peter also challenged the idea that everything should be constantly tested. Many accounts simply donβt have enough data to make small tests meaningful, meaning time is often better spent improving fundamentals rather than chasing marginal gains.
The overarching lesson is straightforward: mistakes are part of the process, but only if they lead to better systems. Every error should result in a checklist, a monitoring process or a safeguard β ensuring it doesnβt happen again.
Valveβs Steam Controller is launching on May 4th Valve has officially confirmed that its new Steam Controller is launching on May 4th at 10 AM Pacific time. In the UK, that translates to 6 PM BST. The controller will be released ahead of Valveβs upcoming Steam Machine and Steam Frame, both of which are due [β¦]
The post Valve unveils Steam Controller release date and pricing appeared first on OC3D.
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Valve confirmed that the first of its previously announced hardware products, the Steam Controller, would be making its way to players next week on May 4, after several leaks had already ruined the surprise. While the aftermath of the official confirmation hasn't provided any meaningful updates on other upcoming bits of hardware like the Steam Machine and Steam Frame, we did get a slight update on the Steam Deck 2, of all things. It's been over four years since Valve boss Gabe Newell confirmed that yes, the company did indeed have plans for a Steam Deck 2. Since then, Valve [β¦]
Read full article at https://wccftech.com/valve-hard-at-work-on-steam-deck-2-four-years-after-initial-tease-gabe-newell/
Asha Sharma has been extremely active since she officially replaced the now-retired Phil Spencer at Xbox in late February. One of her earliest moves was discontinuing the "This Is an Xbox" marketing campaign, which had been widely mocked by fans. More significantly, she formally dismantled the Microsoft Gaming identity in favor of a unified Xbox-first structure, with Microsoft plastering the "Return of Xbox" slogan on its office walls. On April 21, Sharma announced a cut to Xbox Game Pass Ultimate's monthly price from $29.99 to $22.99, while PC Game Pass dropped from $16.49 to $13.99. Simultaneously, new Call of Duty [β¦]
Read full article at https://wccftech.com/xbox-asha-sharma-memory-crisis-project-helix-price/
Microsoft's Shader Model 6.10 and AgilitySDK 1.720 are now available in preview, expanding the DX12 API with brand new features. Microsoft DX12 Linear Algebra "Matrix" APIs, Group Wave Index, Raytracing Intrinsics, More With Shader Model 6.10 & AgilitySDK 720 Preview Release Today's launch expands on the previous release of Shader Model 6.9, DXR 1.2, and other enhancements, which were part of the AgilitySDK 1.619. With the release of the AgilitySDK 1.720 preview, Shader Model 6.10 and several other features listed below are being added to the DX12 API: inalg::Matrix Shader Model 6.10 introduces a set of Matrix APIs covering a [β¦]
Read full article at https://wccftech.com/microsoft-shader-model-6-10-agilitysdk-720-preview-now-available-dx12-neural-rendering/
The first of the three new pieces of hardware that Valve announced back in November 2025 will arrive next week on May 4, 2026, and it would be a much bigger surprise if a review of the product hadn't leaked days ago. The Steam Controller, as we already learned, will arrive next week and be priced at $99 USD, and now Valve has officially confirmed the leaks. We also got an update on the Steam Machine and the Steam Frame, which is that Valve has no real updates to share for now, but programmer Pierre-Loup Griffais thinks "in general, things [β¦]
Read full article at https://wccftech.com/steam-controller-release-date-price-no-update-on-steam-machine/
Penvox learns how you actually talk and builds a weekly social content plan tailored to your business. It analyzes your voice from short prompts, then generates platform-ready posts that match your tone, vocabulary, and personality. You can edit or regenerate content, rate performance, and let the system adapt to what works for your audience across 50+ industries. Stay consistent with ready-to-post ideas and plain-English reasoning for each piece.
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A randomized field experiment found Google AI Overviews reduced organic clicks on triggered queries by 38%, while user experience ratings stayed unchanged.
The post Googleβs AI Overviews Cut Clicks Without Satisfaction Gain: Report appeared first on Search Engine Journal.
ARC Raiders is the latest game to add to the list of games that support PSSR 2, the latest generation of PlayStation's upscaling technology. Embark Studios confirmed that tomorrow's Riven Tides update for the extraction shooter will not only add a new map, new map condition, new items, a new enemy, a new event, and new cosmetics, but it'll also bring "meaningful" visual improvements thanks to PSSR 2 that PS5 Pro players will notice "immediately." Announced with a new PlayStation Blog post, members of Embark's technical team praised the improvements afforded by PSSR 2, with engine lead Robert Kihl saying, [β¦]
Read full article at https://wccftech.com/arc-raiders-pssr-2-support-ps5-pro-riven-tides-update/
China has unveiled its new supercomputer, called LineShine, in Shenzen, which will deliver 2 ExaFlops of compute performance. The Chinese LineShine Supercomputer Is All Set To Become The Fastest In The World, Exceeding 2 ExaFlops During a conference at the National Supercomputing Center in Shenzhen today, the fastest domestic supercomputer project was announced. Known as LineShine, the Supercomputer will be built in two phases and will deliver over 2 ExaFlops of compute. Currently, the world's fastest supercomputer is the AMD-based El Capitan, which has a peak compute of 2.8 Exaflops. Coming to the specifications, the LineShine Supercomputer is purely a [β¦]
Read full article at https://wccftech.com/chinas-lineshine-supercomputer-2-exaflops-47000-cpus-zero-reliance-on-foreign-chips/
Kingston has launched a large capacity Gen 5.0 U.2 SSD for data centers, featuring up to 14 GB/s of sequential read speeds. Kingston Launches DC3000ME 30.72 TB Gen 5.0 U.2 NVMe SSDs as Data Centers Push Toward Higher Density AI Storage Popular storage maker, Kingston, has debuted its high-capacity variant for the DC3000ME Gen 5.0 U.2 NVMe SSD. The new SSD brings a capacity of 30.72 TB, expanding the storage ceiling of the enterprise PCIe 5.0 lineup for data centers that are rapidly scaling for AI operations. The DC3000ME 30.72 TB SSD aims to deliver higher-capacity alternative for enterprises that [β¦]
Read full article at https://wccftech.com/kingston-launches-dc3000me-30-72-tb-u-2-gen-5-0-ssd/
People Can Fly, the studio behind Gears of War: Judgement and Outriders, which is currently co-developing Gears of War E-Day has just acquired games publisher Cooldown Games for an undisclosed amount, per GamesIndustry.Biz. This acquisition is part of People Can Fly establishing its own publishing arm, and it comes after the company's 2025 was marked by project cancellations and layoffs. People Can Fly's 2025 started with players learning that the studio would be co-developing Gears of War E-Day, as previously mentioned. That was then followed with the news that the studio would develop a new game based on one of [β¦]
Read full article at https://wccftech.com/people-can-fly-acquires-publisher-cooldown-games/
Later this week, MotoGP 26Β will launch on PC, PlayStation 5, Xbox Series S and X, Nintendo Switch, and Nintendo Switch 2. According to Italian developer Milestone, this year's entry represents the most significant overhaul of the franchise's core in years. The headline change, the new Rider-Based Handling system, flips the fundamental control philosophy on its head: where previous games mapped player input directly to the bike, MotoGP 26 routes it through the rider's body first, shifting weight before the bike responds. It is a subtle but far-reaching change that touches animations, physics feel, and how veterans will need to approach [β¦]
Read full article at https://wccftech.com/motogp-26-rider-based-handling-interview-milestone/
The AirPods family offers a product for every price bracket, meaning that thereβs something for everyone, just as long as you have the budget for the purchase. Fortunately, Amazon will make those purchases simpler as it has knocked off up to 22 percent from the AirPods 4 without Active Noise Cancellation and the AirPods Pro 3, which are Appleβs top-tier wireless earbuds at this time. For just $99.99, you can be the proud owner of one of these. The higher-end AirPods Pro 3 are currently listed for $199.99 after a 20 percent discount, making it the lowest price for Appleβs [β¦]
Read full article at https://wccftech.com/apple-airpods-4-and-airpods-pro-3-are-up-to-22-percent-off-on-amazon/
Samsung's much-anticipated entry in the rapidly populating AR space is finally taking shape in the form of Galaxy Glasses. And now, we have just received some of the first renders of the new augmented reality device, which appears to be borrowing a lot of design cues from Meta's Ray-Bans and Google's Gemini Glasses. Galaxy Glasses will be Samsung's second Android XR device, following the launch of the Galaxy XR headset last year OnLeaks and Android Headlines have now published some of the very first renders of the upcoming Samsung Galaxy Glasses, which will leverage the Android XR platform and Gemini [β¦]
Read full article at https://wccftech.com/samsung-galaxy-glasses-surface-within-early-renders-50g-frame-snapdragon-ar1-and-no-display-in-2026-launching-variant/
Flowsery is a privacy-first web analytics platform built for teams that care about revenue, not just pageviews. Track the channels, pages, funnels, and user journeys that drive conversions, all in one clean dashboard. Flowsery includes revenue tracking, advanced bot filtering, funnels, goal tracking, and visitor journey analysis out of the box, so you can see what works and where people drop off. It is built in Europe, works without cookies, and is designed for teams wanting clear answers without the complexity of traditional analytics tools.
Stylino aggregates fashion from the best retailers in Cyprus so you can compare prices, check size availability, and shop women's, men's, and kids' styles in one place. Browse top brands and categories, track sales, and click through to trusted stores to buy at the best price.
As ad dollars begin shifting toward ChatGPT, ad tech firms have started working to make that transition as seamless as possible.
Whatβs happening. Adthena launched a new tool, AdBridge, designed to convert existing Google Ads campaigns into formats ready for ChatGPT advertising. The pitch is simple: donβt rebuild from scratch β repurpose what already works.
The tool analyzes advertisersβ search campaigns to generate keyword lists, negative keywords, and competitive insights that can be directly applied to ChatGPT campaigns. It also surfaces which brands are showing up in specific auctions, how often they appear, and which prompts are triggering those placements β giving marketers more than just a copy-paste approach.
Why we care. Adthenaβs Adbridge makes it much easier to shift budget from Google Ads into ChatGPT without rebuilding campaigns from scratch. By repurposing existing keywords, learnings, and competitive insights, brands can test and scale ChatGPT ads faster with less risk. As the platform opens up and inventory grows, tools like this lower the barrier to entry and could accelerate how quickly ChatGPT becomes a serious performance channel.
As Adthena CMO Ashley Fletcher put it, the goal is to get campaigns βready so they can go straight in,β mirroring the CSV-based workflows advertisers already use across major platforms.
Early testing. The company already held multiple sessions with large enterprise brands testing the tool, signaling early demand from advertisers looking to scale activity in ChatGPTβs still-limited ad ecosystem.
Between the lines. This isnβt just about convenience β itβs about momentum. Advertisers experimenting with ChatGPT ads have faced constraints like low inventory and limited scale. By making it easier to deploy campaigns quickly, Adthena is positioning itself to accelerate adoption as those constraints ease.
Zoom in. AdBridge is part of a broader push from Adthena, including Arlo, an AI assistant that allows advertisers to query performance data and compare results between ChatGPT and search campaigns. Together, they point to a future where managing AI-driven ad channels looks increasingly similar to existing search workflows.
The backdrop. OpenAI has been rapidly evolving its ads offering β quietly rolling out an ads manager, lowering minimum spend thresholds, and introducing more flexible pricing models. Partnerships with firms like Criteo and Smartly signal a growing ecosystem.
Bottom line. If ChatGPT ads are going to compete for search budgets, the winners may be the tools that make switching feel effortless β and Adthena wants to be first in line.
High CPU demand is allowing Intel to sell βbinned downβ CPUs that would otherwise have been considered βscrapβ Q1 2026 has been a strong quarter for Intel. It drove revenue and margin growth, resulting in much higher earnings. Intel has already confirmed growing yield for its foundry nodes, resulting in more usable CPUs per wafer. [β¦]
The post Salvaging scraps β Intel boosts revenue by selling βscrapβ CPUs appeared first on OC3D.
Gaming laptop prices have finally started to stabilize, and if youβve been following the swath of deals posted by Amazon, youβre more than likely going to stumble upon this MSI Vector 16 HX AI gaming laptop. In a nutshell, this machine oozes an outstanding βprice to performanceβ ratio as itβs equipped with an RTX 5070 Ti GPU, but more importantly, is its price. At $200 off, this powerhouse of a machine is now available for $1,599.99, and if you purchase one right now, a free copy of Capcomβs PRAGMATAΒ can be yours for no extra charge. At $1,599.99, the MSI Vector [β¦]
Read full article at https://wccftech.com/msi-vector-16-hx-ai-rtx-5070-ti-gaming-laptop-now-200-off-with-free-pragmata-copy/
After Noctua announced its fan 3D CAD models for public usage, it clarified that these aren't meant for 3d printing. Noctua Allows Printing CAD Fan Models, but Clarified That These Have Altered Fan Blade Geometry Popular fan and cooler manufacturer, Noctua, has recently announced on its X handle and the official website that it's now offering 3D CAD fan models for all of its fans for the public. These 3D CAD models reportedly represent "accurate" mounting and external dimensions fo the fans. However, if you think that you can simply 3D print an existing Noctua fan, then you are mistaken. [β¦]
Read full article at https://wccftech.com/noctua-drops-public-cad-files-for-its-fans/
Nioh 3 received its biggest post-launch update, update 1.05, earlier today, introducing new mechanics and content that address one of the biggest complaints the community had since its release: its low challenge level compared to its predecessors. Update 1.05, whose complete patch notes can be found on the game's official website, introduces, among balance changes and fixes on both PC and PlayStation 5, a new gameplay mechanic called Stone of Penance, which is unlocked from the opening mission Escape from Hitokoto Slope onward in the Shogun's Journey difficulty level. Available at Shrines, this mechanic allows users to exchange an accessory [β¦]
Read full article at https://wccftech.com/nioh-3-cranks-up-difficulty-patch-1-05/
There's something in the water about Assassin's Creed Hexe. Barely two months ago, it was the project that was showing major promise and the one that "everyone at Ubisoft wants to work on," according to insider reports. Amidst the company's turmoil of the "major reset" it underwent to start 2026, Hexe seemed like one of the bright spots for the company's future. Well, that has quickly changed after it lost two major creative leads and is now losing another 50 developers while also getting pushed out of its previous 2026 release window into a potentially late 2027 release window. This [β¦]
Read full article at https://wccftech.com/assassins-creed-hexe-release-date-june-2027/
Intel now gives users the ability to allocate up to 93% of system memory to Arc iGPUs, enabling wider AI LLM support. Trying To Run AI LLMs That Don't Fit On Your Arc iGPU? Intel Made It Possible By Allowing You To Dedicate Up To 93% System Memory In Its Latest Drivers Intel has dropped a new HotFix driver for Arc Pro Graphics, 302.0.101.8517 - Q1.26 R2, which lets users allocate even more system memory to the GPU, ideal for running larger AI LLMs. Previously, Intel's Drivers were able to allocate up to 87% of the system memory to the [β¦]
Read full article at https://wccftech.com/intel-drivers-lets-users-allocate-93-percent-system-memory-to-arc-igpus-wider-ai-llm-support/
The inception of Liquid Glass with iOS 26 didnβt garner the best reception, but Apple isnβt taking a backseat with the UI choice, as iOS 27 wonβt revert back to the original design because the company is planning a multitude of optimizations and improvementsΒ that will span several years. Aside from Apple typically being steadfast in its decisions, the reason it will stick with Liquid Glass has more to do with what it has planned for future iPhones, with a tipster noting that the California-based giant is set to release the most advanced display design to fulfill its bezel-less dreams. New [β¦]
Read full article at https://wccftech.com/apple-liquid-glass-display-development-the-most-advanced-ever/
AMD is enabling CUDIMM DDR5 memory support with new AGESA updates & upcoming EXPO 1.2 tech, but only next-gen Ryzen CPUs will enable it. DDR5 CUDIMM Support on AM5 Platforms Limited By IMC; Only Next-Gen AMD Ryzen CPUs Support It Recently, there has been a lot of talk regarding AMD EXPO 1.2 and how it's bringing improved DDR5 memory support to AM5 platforms. It all started when ASUS launched its latest AGESA BIOS, which added EXPO 1.2 support on X870 series motherboards. Soon after ASUS's release, more details for EXPO 1.2 were shared, which suggested CUDIMM & CSODIMM support, along [β¦]
Read full article at https://wccftech.com/amd-expo-1-2-cudimm-ddr5-memory-next-gen-ryzen-cpus-current-cpus-bypass-mode/
The AI Agent Index is a structured directory of AI agents built for business automation. Search and compare agents across sales, customer support, research, marketing, coding, and HR, filtered by pricing, deployment method, integrations, and customer segment. Every listing includes editorial ratings, pros and limitations, and comparison pages so you can make faster, more informed decisions about which agent fits your workflow.
Microsoft teased new AI reporting features within Bing Webmaster Tools that enhance the AI performance reports and other reports around AI. The new features that were showcased include citation share, grounding query intent, GEO-focused recommendations.
More details. Several shared screenshots of this presentation that was given by Krishna Madhavan from Microsoft at SEO Week today in New York City. Here are some of those slides:
Bing Webmaster Tools just dropped some VERY COOL stuff at #SEOWeek 2026
Citation Share, Grounding Query Intent (15 pre-defined intents), and GEO-focused recommendations.
The gap between Bing's transparency and Google's is getting harder to ignore.
Cc @rustybrick @glenngabe pic.twitter.com/kOMhVyQvpQβ Azeem Ahmad (@AzeemDigital) April 27, 2026
Bing webmaster tools owning SEO & GEO @kmadhavan77
Citarion share
Intent
Topics
Geo recomendaciones
Exclusive for #seoweek pic.twitter.com/H2arlFtS8Rβ MJ CachΓ³n (@mjcachon) April 27, 2026
Not live yet. These new features and reporting do not seem live yet but Microsoft still showed them off.
Why we care. More transparency into how your content is performing within the AI search results is useful. So we all welcome additional reporting from Bing Webmaster Tools.
It is not clear exactly how these reports will work and when they may be live for you and me, but you can read those posts for more details.
If youβre reading this, youβre likely an SEO aficionado like me. Iβm a seasoned SEO with 10+ years of agency experience.
Being on the agency side gave me deep SEO expertise, exposure to top industry talent, and experience working with some of the worldβs most well-known brands.
I did a bit of everything on the agency side β from technical SEO to content marketing to new business.
Working at an agency is nothing like working in-house. After a long run on the agency side, I moved in-house for the first time. Here are seven things Iβve learned since making the switch.
On the agency side, when performance drops, you know the drill: a frantic message hits your inbox β traffic is down β and the client needs a report on whatβs happening by yesterday.
You then spend the next few hours in the SEO trenches analyzing search trends, tracking ranking changes, and digging through Google Search Console to find your answers. You cross your Tβs. Dot your Iβs. You beautify that report a bit. And β finally β you fire it off to your client.Β
After sending the report, you may get a few questions from the client. A little back and forth, but for the most part, your job is done. The fire drill is over. Youβve done everything you can from the agency perspective. On to the next client on your roster.Β
This situation looks a lot different on the in-house side.Β
From my new perspective, receiving that agency report is just the beginning. Now, Iβm the one on the hook for translating that analysis, figuring out how to socialize it, and turning it into a concrete action plan to turn performance around.
I always knew my clients were under a lot of stress. I figured their bosses were the ones catching the dips and asking difficult questions, leading to that inevitable frantic message in my inbox. But, boy, it hits differently when youβre the one getting asked those difficult questions.
When youβre in-house, you arenβt just reporting on a dip in performance β it feels like youβre defending your entire SEO strategy. The way you frame that data can make or break the projects or the direction youβre taking the program.
Itβs a lot of pressure β and itβs different when youβre responsible for the results.
On the agency side, the deliverable is the destination. You spend hours researching, analyzing, and refining a beautiful slide deck. Each slide flows, tells a story, and looks pristine. I mastered this β and did it fast.
Now that Iβm in-house, Iβve realized the deliverable isnβt the destination anymore.
Itβs all about the execution.Β
I was lucky enough during my agency days to have one engagement where I was deeply embedded in day-to-day operations. I was doing things like building dev tickets, reviewing Figma designs, and actually pushing CMS updates. I thought I knew exactly what execution looked like.
But executing while in-house is way more challenging than I expected.Β
In order to execute on an SEO strategy, you have to work through the entire org to bring your vision to life. You need to coordinate with the design team to review Figma designs. You need to align messaging and copy with PMMs. You need to work with project managers to make sure deadlines are being met. You need to work with devs to make sure the technical implementation is correct.
Itβs not easy. Sometimes itβs messy. And β quite often β itβs pretty frustrating.Β
But hereβs the truth: once you move from polished decks to pushing changes live, you become 10x the SEO you were before.
Dig deeper: Why branding matters for in-house SEO teams
One of the more interesting parts of making the switch to in house, was that suddenly, I became the client. Iβm the one on the other end of the video call. Iβm the one receiving the strategy docs. Iβm the one calling all the shots.Β
And honestly? Itβs been a huge (and super exciting) opportunity to take everything that Iβve learned on the agency side and put it into action.Β
And Iβve gotten to decide what type of client I want to be.Β
I had a wide range of clients on the agency side. Some disappeared. Some were demanding and made every call tense. Some pushed impossible deadlines. Some didnβt trust my judgment. Some couldnβt execute the strategy.
You name it β Iβve probably experienced that type of challenging client.
Then I had dream clients β kind, collaborative, and treated me like an equal. Calls felt like catching up with a friend before getting into SEO. They could take a strategy and execute without being demanding or difficult.
That was the client I wanted to be. And thatβs the client I strive to be, too.Β
Iβm a technical SEO at heart.
Nothing makes me happier than seeing the indexing rate improve after an XML sitemap refresh. Or seeing a massive improvement to Largest Contentful Paint after implementing Core Web Vitals optimizations. Or even a perfectly executed hreflang optimization to target your key international markets.Β
Chefβs kiss β it warms my technical SEO heart to see all this work get executed.Β
The problem? Your execs donβt understand that technical jargon.
Thatβs where storytelling becomes your best friend. And Iβd say itβs almost as important as the execution itself.Β
Because it doesnβt matter if you do all this SEO work if your bosses canβt understand it. You need to tell a story about what you did, why you did it, and the results. All in a simple, easy-to-understand format β ideally with a pretty visual right next to it.
Letβs take, for example, hreflang optimizations. You realize that hreflang is important. But how do you make it seem important for an exec so that they can understand it?
What I do is pretty simple. I explain the background behind why Iβm doing what Iβm doing and frame it in simple terms.Β
Instead of saying that we updated hreflang to target France correctly, I would frame it as improving the search experience for France searchers. Iβd then show a SERP screenshot of before the optimizations to show incorrect targeting, and follow it up with an updated screenshot with correct targeting. Lastly, Iβd share results β ideally, an increase in CTR, traffic, or conversions.Β
(Side note: If youβre one of my agency partners reading this, you know I ask for an insane amount of screenshots β but this is exactly why I do it.)
Following this formula allows you to:
Itβs a simple blueprint that makes it easy for execs to understand the importance of your optimizations.Β I know it may seem small, but storytelling is one of the secrets to success in in-house life.Β
Dig deeper: How to use the three-act structure for data storytelling
In a massive organization, itβs so easy to live on an SEO island. If youβre not collaborating, you can easily find yourself on a beach hanging out with a volleyball named Wilson β just optimizing <title> tags, writing meta descriptions, and optimizing on-page copy for keywords.Β
But thereβs absolutely no way youβre going to get anything meaningful done without the support and assistance from others within your organization.Β
You need to be a team player. And cross-functional collaboration is important for success.Β
After years on the agency side, I learned to move fast β really fast. When I went in-house, I tried to keep that pace. I wanted to make changes, test, and see results immediately. I saw documentation as a hurdle, and large cross-functional meetings without progress as a waste of time.
Quickly, I found out thatβs not the case. You need the support of those partners in cross-functional meetings to get things done.Β
It takes time to get to know your cross-functional teams and understand what theyβre good at, what their goals are, and β crucially β where they need support. Iβve learned that once you understand the developerβs sprint capacity or a product marketing managerβs roadmap, you can stop just requesting things from them and start partnering with them to get things done.Β
When you align your SEO goals with their existing priorities, you stop being a line item in their backlog and start becoming a teammate. In-house, having a teammate in engineering or product is the difference between a strategy that sits in a slide deck and one that actually ships.
OK, fine, I added a clichΓ© to the list. But in the in-house world, it might be the most important one.Β
Iβve been given this advice several times throughout my career. If you want to get something done, go get it done. Donβt wait around for permission from your bosses to do something that will have a significant impact. If you wait for permission, you may never get anything done.Β
Thatβs why I ask for forgiveness β not permission.Β
When I started in-house, I knew the team was lean. I knew my bosses had a million things on their plates. And, most importantly, I knew they hired me for a reason: to drive organic growth.
During my first few weeks, I remember asking myself, βCan I launch this content?β βCan I expand into this market?β βAm I allowed to test this tactic?βΒ
And then it hit me: This is exactly why Iβm here. They hired me to make these decisions and move the needle, not to add more approval meetings to their calendars.
And if I asked for permission for everything, I would never be able to get anything done.Β
This is why I trust my instincts when it comes to SEO strategy and execution. I rely on my 10+ years of experience in the SEO game. If I think something is going to drive growth for the business, I donβt just sit around and wait for permission to do something. I execute.Β
And if something doesnβt turn out exactly how I had planned? Thatβs when I take the forgiveness route.Β
Dig deeper: 5 lessons from delivering bad SEO news to executives
I did a lot of high-impact, business-changing work during my agency life. Iβve built the strategies, seen them come to life on a site, and watched them drive results. Driving results and building case studies have always been my favorite part of the job.
However, when youβre sitting agency-side, youβre often the silent partner in those results, not the owner.Β
Now that Iβm in-house, I get to see my projects come to life on the site β and itβs pretty cool.
During my first few months in-house, I knew I wanted to make an impact quickly. I implemented a few of my high-impact, low-effort optimizations β the ones I would typically implement for a new client I had just onboarded.Β
After reviewing monthly reports, I saw an insane spike in performance that lined up exactly with a significant site update we implemented.Β
I remember thinking, βWait, was that us?βΒ
The answer: It sure was.Β
I then created my first case study and shared the results throughout our organization. And, shockingly (to me, anyway), people were really interested. Within my first three months, I found myself sharing those results at our entire companyβs all-hands meeting β something I never expected to happen.Β
I used to think a massive organization wouldnβt be interested in SEO, but I was wrong. When it comes to moving the needle for the business, everyone cares.
So, yeah, itβs always fun to get SEO results. But itβs a lot cooler when youβre in-house.Β
Making the switch from agency to in-house life has been a lot of adjectives for me. Exhausting, challenging, and exciting are some of the first that come to mind.Β
But the biggest takeaway after one year in-house? Iβve learned a lot.
I hope you can take these seven lessons and apply them to your own journey β whether youβre at an agency or leading an in-house team right now.Β
The transition isnβt always easy, but for me, seeing the strategy finally turn into reality has made every cross-functional meeting and performance fire drill worth it.
Star Wars Galactic Racer release date leaks on Steam Star Wars Galactic Racer is shaping up to be one of 2026βs most exciting racing games. With fast-paced racing, various vehicle types, and its Star Wars underground setting, it is unlike most modern racing games. While Star Wars: Galactic Racer was unveiled with a β2026β release [β¦]
The post Star Wars Galactic Racer release date leaks appeared first on OC3D.
Despite Assassin's Creed Codename Hexe reportedly being the game in Ubisoft's portfolio that "everyone at Ubisoft wants to work on," the upcoming project has gone through another major leadership change. After it lost its creative director, Clint Hocking earlier this year, Assassin's Creed Hexe has now lost game director Benoit Richer, who departs the company to go start his own. Richer announced his departure on his LinkedIn page, calling it "the beginning of a new chapter" in his career, as he finally moves away from working at some of the biggest publishers in the industry to be a co-founder and [β¦]
Read full article at https://wccftech.com/assassins-creed-hexe-another-leadership-change-game-director-leaves-ubisoft/
Need gift ideas for people in your life who may deserve a little treat for this Mother's Day? Laifen has been a Wccftech-favorite lifestyle brand that explores new technologies to make personal care products work for the person. From hair dryers that don't take ages and jiujitsu-level movements to dry and style your hair to dentist-approved toothbrushes, the company makes glow-ups possible without investing thousands of dollars or spending hours. One of its most sought-after products is the Laifen SE 2 high-speed hair dryer, which, unlike regular hair dryers, makes hair drying and styling a breeze. Making salon-quality hair at [β¦]
Read full article at https://wccftech.com/personal-care-products-that-make-the-ultimate-lazy-beauty-mothers-day-gifts/
It's been over two years since we learned that the Watch Dogs movie was finally being produced. The big screen adaptation of the open world game was first announced back inΒ 2013Β alongside the original game, then disappeared into development hell for years. It finally resurfaced whenΒ New Regency and Sony Pictures/Columbia PicturesΒ formally partnered with Ubisoft on the adaptation and picked the director (Mathieu Turi, who worked on Meander and The Deep Dark), writers (Christie LeBlanc, who worked on OxygΓ¨ne, and Victoria Bata, who worked on Pitch Perfect 3 and Fate: The Winx Saga), and cast (Tom Blyth, known for Billy the Kid [β¦]
Read full article at https://wccftech.com/watch-dogs-movie-tom-blyth-praise-tears-apart-world/
UNPWNED is a web security scanner for websites and GitHub repos that runs 500+ checks across headers, DNS, infrastructure, code, and compliance. It explains findings in plain English with ready-to-paste AI fix prompts. It detects leaked secrets, misconfigurations, and vulnerabilities in minutes, and offers continuous monitoring, alerts, PDF reports, and GitHub Issues integration to help teams ship secure code.
Jogga is a highly adaptable, budget-friendly AI running coach that adjusts when life changes. If you miss a run or change your pace, the AI instantly recalibrates your plan to keep you safely on track, offering premium digital coaching at a fraction of the cost.
Google is bringing back its 5-Day AI Agents Intensive Course with Kaggle and registration is open.
Supercharge performance across the shopper journey by connecting Albertsons data with Googleβs AI and scale.
Paid search platforms are getting better at deciding who should see your ads, often without relying on the keywords you choose.Β
As that shift accelerates, optimization is moving away from query-level control and toward signals like audience data, landing page context, and conversion behavior. Understanding that change is key to knowing what to actually optimize for now.
A decade ago, our world was defined by the illusion of control. Every decision we made was anchored in the keyword. Hypersegmentation and single keyword ad groups (SKAGs) ruled the land.
If possible, weβd build a unique landing page for every single keyword in every single ad group. The process was tedious, manual, and we loved it because we felt like we were the ones driving the machine.
Fortunately (or unfortunately, depending on how much you miss spreadsheets and Editor), times have changed. Weβve long speculated about whether Google and Microsoft would finally sunset keywords altogether. That day feels closer than ever.
From Performance Max to the emerging AI Max solutions β and even the shift toward contextual, LLM-driven search like ChatGPT β the industry is moving toward a keywordless reality.
But if we take a step back, we have to admit why the keyword is so vital. Itβs a window into clear intent that tells us exactly where a user is in their journey:
If those signals are now handled behind the scenes by a black box, the role of the marketer changes. So what are we actually optimizing for?
Dig deeper: Beyond keywords: Mastering AI-driven campaigns
Intent is inferred from a complex web of signals that have rendered the individual keyword secondary. To win in 2026, your optimization focus must shift toward three core pillars.
Googleβs algorithms now prioritize customer match and first-party data over the query itself. With the full integration of the Data Manager API, the system knows which users in the auction match your closed-won deals.
You no longer bid on the query βcloud security.β You bid on the director of IT (because youβre sharing first-party data) who has a history of researching SOC 2 compliance, even if their current search is as vague as βscaling infrastructure.β
B2B match rates are notoriously stubborn. But this is exactly where you need to evolve your strategy. Move beyond one-to-one list matching and get creative with integration partners to enrich your signals.
Start by clustering individuals by shared pain points, then use on-site experiences to allow them to self-identify. By the time they hit a remarketing list, you arenβt just targeting a βuser,β youβre targeting a verified intent state.
Your landing page is a data source. Googleβs AI scans your page to understand the nuance of your offering. Creative assets are also important signals and need to complement your targeted themes and keywords, plus your landing page content.
If your landing page clearly articulates a βmid-market manufacturingβ use case, the AI will automatically find those users, even if they never type the word βmanufacturing.β Your βkeyword strategyβ is now your content strategy.
You might think looking at Meta is a deviation here, but the parallels are impossible to ignore. Metaβs Andromeda retrieval engine now influences a massive portion of the social auction by using the creative itself as the primary targeting signal.Β
If both platforms are moving toward a world where your assets (whether itβs a 15-second video or a high-value landing page) are what actually define your audience, you have to ask: How much weight are you giving your creative inputs versus your technical ones?Β
With journey aware bidding and value-based bidding, the algorithm isnβt just looking for the final click. Itβs analyzing the historical sequence of a userβs journey.
Optimization now happens against βhigh-value need states.β Youβre feeding the system data on which mid-funnel behaviors (like a whitepaper download or a webinar sign-up) actually lead to six-figure contracts.
Dig deeper: Why better signals drive paid search performance
The most significant mental hurdle for digital marketers is the shift from query-level intent to user-level intent.
| Feature | Query-level intent (legacy) | User-level intent (2026 and beyond) |
| Primary driver | The specific words typed. | The userβs historical behavior and context. |
| Logic | βThey are in state X, so they need Y.β | Triggered by a predicted βneed state.β |
| Measurement | CTR and CPC. | Pipeline value and predicted LTV. |
| Auction entry | Triggered by a keyword match. | Triggered by a predicted βneed stateβ |
In the old model, a query like βhow to manage payrollβ might have been ignored by an enterprise SaaS company as βtoo informational.β In 2026, the AI knows if that user is a student or a VP of finance at a 5,000-employee firm.
If itβs the latter, the user-level intent is commercial, regardless of the query-level phrasing, assuming youβre providing the right signals (see what I did there?). If youβre advertising on Microsoft Ads, you can leverage LinkedInβs profile targeting.
Now that AI is handling the matching, your job has evolved from a mechanic to a data architect.
The future of search isnβt about finding the right words. Itβs about being the best answer for the right person at the exact moment their need state evolves.
Keywords were the training wheels. Now, the wheels are off. Itβs time to see how fast your data can take you.
Dig deeper: Why PPC teams are becoming data teams
AI systems are getting better at generating Spanish. Theyβre not getting better at understanding Spanish markets.
What weβre seeing instead is a consistent pattern: more than 20 Spanish-speaking countries collapsed into a single default. Spain becomes βstandard.β Mexico becomes interchangeable. The rest get flattened into statistical averages.
The failure modes are structural β dialect defaulting, format contamination, and regulatory hallucination β and theyβre amplified in a generative search environment where one synthesized answer replaces 10 blue links.
That distinction is now a visibility constraint. Generative systems resolve ambiguity. When your content doesnβt make its market context explicit, the system defaults to the statistical average β and thatβs where otherwise solid content gets misapplied or ignored.
Below is a framework for fixing that problem. Itβs designed to make market context explicit β across content, technical signals, and retrieval systems β so AI doesnβt have to guess.
Cultural SEO goes beyond hreflang and localization. The technical foundation is locale precision β controlling market context across retrieval and generation so an AI system treats your Spanish content as belonging to a specific country, not to βSpanish speakersβ in the abstract.
Hereβs the framework that works when you operate across Spain and Latin America.
But thereβs a prerequisite no framework can substitute for: you canβt optimize for a market you donβt serve.
Cultural SEO isnβt a localization layer you bolt onto a website. Itβs the technical expression of a business decision to operate in a market β with real logistics, real customer support, real legal compliance, and real product-market fit.
If you ship from Spain to Mexico with a three-week delivery, process returns in euros, and have no local support channel, a perfect hreflang setup wonβt save you. The model might surface your content, but the user will bounce β and the next time the model learns from that signal, youβll be deprioritized.
Internationalization means speaking the marketβs language in every sense: visual trust cues, payment methods, delivery expectations, regulatory compliance, and customer experience.
The four pillars below assume youβve made that commitment. If you havenβt, start there. Everything else is decoration.
Most international SEO teams think of segmentation as a folder structure: /es-es/, /es-mx/, /es-ar/, but thatβs not enough.
In generative search, the question is whether the system recognizes that page as belonging to Mexico β and whether it has enough market-specific signals to prefer it over a generic alternative. If your architecture collapses variants, your visibility collapses with it.
Donβt just use es. Use es-ES for Spain, es-MX for Mexico, es-AR for Argentina, es-CO for Colombia, and es-CL for Chile. Include x-default for users who donβt match any specific locale. Consider ccTLD strategies (.es, .mx, .com.ar) where they make business sense.
ccTLDs remain one of the strongest explicit geographic signals on the open web, and they reduce ambiguity for both search engines and downstream retrieval systems. Googleβs documentation on localized pages supports this specificity.
But hereβs the caveat. In the first article, I discussed Motoko Huntβs concept of geo-legibility and the phenomenon of geo-drift β AI systems misidentifying geography because language alone doesnβt resolve market context.Β
Simply put, if your Spanish content doesnβt carry explicit country-level signals beyond hreflang, the model has to guess. Guessing, at scale, means defaulting.Β
Ultimately, hreflang helps with traditional routing, but in AI synthesis, itβs one signal among many β and not necessarily the decisive one.Β
When a generative system assembles an answer, it weighs semantic relevance, authority, and content-level cues alongside metadata.Β
If your Spanish content relies on hreflang alone to declare βthis is for Mexico,β youβre betting on a single signal in a multi-signal environment. Geographic markers need to live in the content itself and in structured data β not only in HTTP headers.
Dig deeper: How AI search defines market relevance beyond hreflang
When you point es-MX, es-AR, and es-CO pages to one canonical es URL, youβre telling engines thereβs only one βrealβ version β the exact Global Spanish assumption youβre trying to avoid. Each market page should canonicalize to itself.
Google cautions against this. Crawlers may not see all variants. More importantly, AI crawlers donβt carry IP signals the way users do. Offer a visible region selector and let users choose.
This is essentially what Hunt calls geo-legibility β encoding geography, compliance, and market boundaries in ways machines can parse:
A practical example: if your Mexico page shows prices in MXN, but your structured data still says EUR because it was copied from the Spain template, the model sees a conflict. Conflicts breed uncertainty. Uncertainty breeds generic answers. Generic answers are where Global Spanish lives.
A note on es-419: It can be useful as a catch-all for Latin American Spanish where market-specific pages donβt exist, but it should never substitute for es-MX, es-AR, or es-CO when the content involves legal, financial, or compliance information. Generic means vulnerable.
If your market pages arenβt self-evident to machines, the system will resolve ambiguity for you β and defaults win.
Translation converts words. Transcreation converts meaning. The distinction matters because translated templates are easy for models to deduplicate β and deduplication is where localized pages go to die.
If two regional pages are 95% identical, the model will treat them as one. The βdefaultβ will win. Localized pages need substantive differences that prove market specificity, including:
The classic example: McDonaldβs βIβm lovinβ itβ became βMe encantaβ β not a literal translation, but an emotionally equivalent expression. Appleβs iPod Shuffle tagline, βSmall talk,β became βMira quiΓ©n hablaβ for Latin American Spanish.
These brands understood that meaning doesnβt translate. It must be rebuilt.
Identify which Spanish-speaking markets have the most search volume and business potential for your verticals. Volume alone isnβt enough. Consider market maturity, competitive landscape, and conversion potential. Then bring in native speakers from those specific countries.Β
This doesnβt mean rigid dialect policing. Context matters β a premium brand in Mexico City might use tΓΊ deliberately for intimacy. The test is whether those choices are strategic or inherited from the training dataβs statistical average.
Take a returns policy page. Spain (/es-es/devoluciones/) and Mexico (/es-mx/devoluciones/) shouldnβt differ only in currency symbols. At least one section needs to be genuinely market-specific:
If the pages are 95% identical after these changes, theyβre not differentiated enough. The model will still collapse them.Β
The feedback loop makes it worse: when a Mexican user lands on βespaΓ±olizedβ content and bounces, that rejection signal teaches the model not to retrieve that page for Mexico next time. Poor transcreation doesnβt just lose one visit. It trains the system against you.
This pillar addresses a layer that most traditional SEO doesnβt touch β and itβs where a lot of the Global Spanish problem actually lives.
If youβre building RAG-powered experiences (chatbots, AI assistants, and AI-enhanced customer support) or optimizing content for AI discovery, the question is: What content is eligible to be retrieved and synthesized for a given market?
Without explicit constraints, the model pulls from its statistical average β which, in this case, is βGlobal Spanish.β The fix requires intervention at the retrieval layer:
Think of it as the AI equivalent of telling your customer service team: βIf a caller is from Mexico, use the Mexico playbook. Donβt improvise.β
This matters beyond your own properties. Up to 43% of fan-out background searches ran in English even for non-English prompts, Peec AIβs analysis found. This is a structural disadvantage for brands whose authority signals exist only in local-language corpora.Β
Spanish sessions may still trigger English sub-searches, which changes which sources are eligible for retrieval. If the modelβs own retrieval is biased toward English sources, your Spanish content needs to be unambiguously market-specific to compete for selection.
LLMs learn from your site and what the web says about you.
This isnβt traditional link building. Itβs regional corroboration β building the external signal layer that tells a model where your brand operates and who considers you authoritative:
This is how you stop being a Spanish brand and become a Mexican authority β or both, explicitly. The key is intentionality: If you serve both markets, the model needs to see distinct authority signals for each, not a single blended profile.
If you need to brief a cross-functional team β dev, content, PR β hereβs what each pillar produces as a deliverable:
| Pillar | Deliverable |
|---|---|
| 1. Segmentation | Locale URL map + hreflang/canonical rules + indexable alternates checklist |
| 2. Transcreation | Per-market glossary + βsubstantive differenceβ content brief template |
| 3. Retrieval constraints | Locale filters + prompt contract (market, currency, jurisdiction) |
| 4. Entity reinforcement | Quarterly PR/citation target list per market + entity consistency audit |
These are the artifacts that make the framework auditable and repeatable across teams.
You canβt improve what you donβt measure. Hereβs a practical error taxonomy for auditing AI-generated content across Hispanic markets:
| Error class | What to look for | SEO/UX impact |
|---|---|---|
| Dialect markers | Wrong pronouns, missing voseo, region-inappropriate vocabulary | Trust erosion, higher bounce rates |
| Format errors | Wrong currency, decimal separator mismatch, incorrect date formats | Conversion risk, especially in e-commerce and finance |
| Legal/regulatory | Wrong authority cited, incorrect compliance steps, mixed frameworks | E-E-A-T damage, potential liability |
| SERP intent | Wrong product categories, wrong local entities, incorrect eligibility | Click-through and engagement drops |
| Brand voice | Formality mismatch (too formal in Mexico, too casual in Colombia) | Brand perception damage |
| Retrieval contamination | Facts or citations sourced from a different locale than the target user | Errors propagated into AI summaries |
If you want a quick QA starting point, check three things first: the currency symbol, the regulator name, and the second-person register. Those three alone will catch most critical mismatches.
For teams working across multiple Hispanic markets, these are the signals that most commonly trigger cultural mismatch in AI outputs:
| Signal | Spain (es-ES) | Mexico (es-MX) | Argentina (es-AR) | Colombia (es-CO) | Chile (es-CL) |
|---|---|---|---|---|---|
| Second-person | Vosotros/ustedes | Ustedes; tΓΊ | Vos/ustedes | TΓΊ/usted varies | TΓΊ/ustedes; local slang |
| Currency | EUR (β¬) | MXN ($) | ARS ($) | COP ($) | CLP ($) |
| Decimal separator | Comma (1.234,56) | Period (1,234.56) | Varies | Varies | Varies |
| Hreflang | es-ES | es-MX / es-419 | es-AR | es-CO | es-CL |
| Privacy framework | GDPR + LOPDGDD | Federal law (2025 changes) | Habeas Data | National data protection | Updated legislation |
| Fiscal/commercial ID | NIF / CIF | RFC | CUIT / CUIL | NIT | RUT |
| Typical LLM default risk | Grammar as βstandard,β vocab ignored | Vocab as βstandard,β context flattened | Voseo erased or flagged | Ustedeo misidentified | Local markers missed |
Not every industry feels this problem equally. But if you work in any of these verticals, cultural SEO means risk management.
In these verticals, the cost of Global Spanish is a liability exposure, compliance failure, and E-E-A-T erosion that compounds across every AI-generated interaction.
Frameworks are only useful if they translate into Monday morning actions. Hereβs how to operationalize cultural SEO:
LoginpriceCurrency and addressCountry, and has areaServed declarations. Two metrics worth tracking from Day 1:
If you can measure those two consistently, you can prove the framework is working.
Everyoneβs talking about markdown formatting, llms.txt files, and structured data for AI. Some of that matters. But before chasing the latest optimization trick, review your:
Thatβs what LLMs are actually reading and what shapes whether an AI assistant recommends you or your competitor. If an LLM had to explain what your product does in the Mexican market based only on whatβs public, would the answer be any good?Β
If not, you donβt have an AI optimization problem. You have a documentation problem.
The fix? Sit down and write clear, market-specific docs that both humans and machines can understand.
If you want a more structured approach, Iβve put together a cultural SEO checklist for Hispanic markets covering technical signals, content signals, entity signals, retrieval constraints, and QA governance.
Before moving on, run these five prompts through any LLM β once specifying Spain, and once specifying Mexico. The differences in the output should be intentional, not accidental:
If the answers are identical, the model is defaulting. If they differ but cite the wrong jurisdiction, you have a retrieval problem. Either way, now you know where to start.
Thereβs an irony in this article that I donβt want to skip over.
Weβre telling brands to stop treating Spanish as a monolith, build market-specific signals, and respect the difference between Madrid and Mexico City.Β
Then we go back to our desks and use ChatGPT to do keyword research βin Spanish.β We generate content briefs with tools that have the exact same geo-inference failures we just diagnosed. We run audits with AI assistants that default to the same βGlobal Spanishβ weβre warning our clients about.
If the tools we use every day carry this bias, then every output we produce risks inheriting it β unless weβre actively correcting for it. That means specifying the market context in every prompt.Β
Donβt trust a βSpanishβ keyword list that doesnβt distinguish between markets. Treat your own AI-assisted workflows with the same rigor youβd ask of your clientsβ content architectures.
The βGlobal Spanishβ problem is also in your own stack. If youβre not fixing it there first, youβre part of the pattern.
The goal is to produce Spanish that is market-true. In 2026, βlocalizedβ is a systems milestone: routing, content, entities, retrieval, and QA all have to agree on the same country context β or the model will pick one for you.
If you want a definition of done for cultural SEO, itβs this: Spain and Mexico can ask the same question and get different answers for the right reasons β and your pages are the ones that stay eligible to be cited.
Stop translating. Start architecting.
Microsoftβs finally fixing Windows Update β Hereβs how Microsoftβs finally listening to feedback. Windows users are finally getting more control over Windows Update. Starting now, with Windows 11βs Dev Channel and Experimental versions, users have new options that give them control over Windows updates. In time, these changes will roll out to all Windows 11 [β¦]
The post Hereβs how Microsoftβs finally fixing Windows Update appeared first on OC3D.
The iPhone FoldΒ is arriving to the market several years after Appleβs competitors have refined multiple versions, which only means that the next category to introduce this unique form factor will be the iPad. While this product would be the obvious choice, a new report states that thereβs a chance that the foldable tablet launch may not happen, and it boils down to reasons such as price, design complications, and software optimizations. Even if Apple manages to scale past the internal problems surrounding the iPad Fold, its potentially exorbitant price will threaten its popularity In Mark Gurmanβs latest βPower Onβ newsletter, [β¦]
Read full article at https://wccftech.com/apple-ipad-fold-may-not-witness-a-launch/
The performance gap between an eGPU and a GPU installed via the PCIe interface natively disappears with the latest MCIO 8i connector. GPD Intros GPD BOX Mini and G2 External GPU With MCIO 8i Connector That Deliver 4x Bandwidth of OCuLink The external GPUs have always been trailing behind the traditional desktops due to the limitation of bandwidth as a result of the absence of a native PCIe interface. We do have some good options to bring the performance closer to the conventional PCIe 4.0 x4 setup, but it's not enough since modern GPUs work much better at PCIe 4.0 [β¦]
Read full article at https://wccftech.com/gpd-box-mini-and-g2-egpu-ditch-oculink-for-mcio-8i-pushing-512-gbps-to-external-rtx-4090-setups/
Being a roguelike, Saros expects you to build your loadout as you proceed through Carcosa. However, the random generation of weapons and Artifacts can often make a Cycle more difficult than expected. However, there is a simple re-roll trick that lets you start every run with your preferred weapon. The Secret to Starting Weapons To get the exact weapon you want, you need to take advantage of a specific quirk in Saros: your next run always begins with the same weapon type you were holding when your previous run ended. Whether you were defeated by an enemy or manually decided [β¦]
Read full article at https://wccftech.com/how-to/saros-how-to-get-your-favorite-weapon-at-the-start-of-every-cycle/
While Saros offers a diverse arsenal of Soltari weaponry, two specific Shotgun variations stand out as the undisputed best choices for clearing biomes. If you are struggling with fast-moving enemies or bosses that leave little opportunities for you to attack, using Stalwart or Annihilator Shotguns is the most effective way to turn the tide. How to Unlock Shotguns Shotguns are not available in the starting area. You will unlock them for the first time in the second biome, the Ancient Depths. The Power of Stagger Damage Still, what makes every Shotgun superior to other early-game weapons is their ability to [β¦]
Read full article at https://wccftech.com/how-to/saros-the-best-weapons-for-high-damage-and-stagger/
In Saros, the Eclipse is dangerous in more ways than one, introducing more powerful enemies that can inflict an altered status condition known as Corruption. While most players will instinctively try to avoid it as much as possible, the game rewards those who understand when to embrace it. Mastering the balance between a fully working suit and a corrupted one is the key to mastering the game's most powerful offensive builds. What is Corruption? During the Eclipse, you will encounter enhanced versions of enemies that fire a different projectile type. Distinguished by their yellow color, these projectiles cause Corruption upon [β¦]
Read full article at https://wccftech.com/how-to/saros-how-to-cleanse-corruption-and-why-you-shouldnt-always-do-so/
Saros gameplay mechanics are the natural evolution of those seen in Returnal, with additional layers of complexity added to defense. Instead of dashing through enemy attacks, the game is all about mastering a sort of rock-paper-scissors defensive loop between your Dash, Shield, and Parry. The last is the riskiest and most satisfying, but before you can pull it off, you must unlock it. How to Unlock Parry Parry is the only defensive option in the game that has to be unlocked before it can be used. To do so, you will have to reach the Blighted Marsh biome and play [β¦]
Read full article at https://wccftech.com/how-to/saros-how-to-parry-enemy-attacks-and-projectiles/
Survival in Saros depends not only on your skills, but also on Arjunβs high-tech suit. Understanding the balance between the three Growth Attributes of the suit and how to improve them is often the difference between a successful Cycle and a quick trip back to the Passage. The Three Growth Attributes None of the Growth Attributes enhances Arjun's attack power or speed. However, Traversal Boost is there to make traversal faster and more enjoyable. How to Improve Stats Growth Attributes in Saros are not static and can be enhanced both permanently and temporarily. Permanent Upgrades Permanent stat increases are handled [β¦]
Read full article at https://wccftech.com/how-to/saros-best-stats-to-upgrade/
While most folks play PokΓ©mon relatively casually, simply catching critters that look cool and building whatever team suits their fancy, there's always been a more hardcore, competitive side to the franchise. This competitive aspect of PokΓ©mon has traditionally been rather difficult to get into, but the PokΓ© powers that be are looking to change that with PokΓ©mon Champions, the recently released free-to-play battle-focused game designed to be the new home of the franchiseβs competitive scene. Does PokΓ©mon Champions successfully open up a previously difficult-to-access side of the franchise? Or is it less than super effective? Roll on for the answer. [β¦]
Read full article at https://wccftech.com/review/pokemon-champions/
While Saros doesn't waste much time teaching the basics of the game, including the Dash maneuver used to avoid enemy attacks, the game often glosses over other mechanics that can make exploring Carcosa smoother and more fun. This is the case of the Traversal Boost ability, which can be a big help if you feel like Arjun is moving too slowly between combat arenas. How to Sprint (Traversal Boost) While Traversal Boost would have worked wonders in a game where repositioning is key to surviving its intense combat encounters, it cannot be used when enemies are present. If you hold [β¦]
Read full article at https://wccftech.com/how-to/saros-how-to-increase-movement-speed-traversal-boost/
The Carcosan Modifiers system in Saros allows you to manipulate the difficulty of a Cycle by altering specific parameters. While the system is entirely optional, and provides neither direct resource bonuses - like increased Lucenite - nor penalties, it is the most powerful tool at your disposal if you are struggling with the game's intense combat. How to Unlock Carcosan Modifiers To unlock this system, you must complete the Shattered Rise biome and defeat the first boss, Prophet. Once the boss is down, the system becomes available at the Primary Unit for all future runs. How the Modifier Dial Works [β¦]
Read full article at https://wccftech.com/how-to/saros-the-best-carcosan-modifiers-to-use-for-easy-progression/
Coming after Returnal, Saros marks Housemarque's return to the roguelite genre with yet another gripping dark space adventure where protagonist Arjun Devaraj faces not only the bullet hell unleashed by the many threats on planet Carcosa, but his own past. In this complete walkthrough and guide hub, you will find anything you need to learn to master the bullet ballet that defines the experience, and have fun while doing so. Getting Started Although generally easier than Returnal, Saros has its unique quirks you need to understand from the beginning of your exploration of Carcosa to improve some of the experience's [β¦]
Read full article at https://wccftech.com/how-to/saros-complete-walkthrough-guide-combat-character-progression-difficulty-modifiers/
A major DRAM & NAND crisis is impending as Samsung faces an 18-day strike in May, which could disrupt the global supply chain. DRAM & NAND Output Will See Up To 4% Disruption In May As Samsung Faces 18-Day Strike DRAM & NAND production is already facing supply constraints, and to make matters worse, Samsung union workers are expected to go on an 18-day strike as the company is unwilling to meet the salary-related demands. As per reports, Samsung's union workers are asking the company for bonuses, demanding a 15% of Samsung's annual operating profit, which amounts to around $30 [β¦]
Read full article at https://wccftech.com/samsung-18-day-strike-cut-off-dram-nand-output-recovery-will-take-2-3-weeks/
Mass Effect Andromeda is still vividly remembered by fans of the series and the internet as a whole for being a very underwhelming game. Still, not everyone associates bad memories with the latest main entry in the series developed by BioWare. Tom Taylorson, voice actor for the male version of protagonist Ryder, stated in a fresh interview with We Are Mass Effect that it was the best thing he has ever worked on, but it was done dirty by its publisher EA and by the toxic atmosphere it launched in, where it quickly became the punching bag of the week [β¦]
Read full article at https://wccftech.com/mass-effect-andromeda-done-dirty-ea-online-chuds/
AIBlogMax turns breaking news into unique, SEO-optimized blog posts and publishes them across WordPress, Shopify, or a hosted blog, plus Facebook and LinkedIn. It monitors thousands of sources, rewrites articles with attribution, and schedules posts on autopilot. Use its website analyzer and keyword intelligence to pick topics, include and exclude terms, and keep content on brand. Manage profiles and channels from a single dashboard, review drafts, add AI images, and run in 20 languages.
Think about the last time you binged those true crime documentaries. The next time you opened your streaming app, the homepage likely shifted. Investigative series rose to the top. Maybe a notification alerted you when a new series dropped. Promotional emails highlighted only what you hadnβt watched. You didnβt see the data parsing or the decisioning behind it. You just looked forward to enjoying the next title.
Thatβs the standard. According to the Adobe 2025 AI and digital trends report , 71% of consumers want personalized β or personally relevant β offers and information, and 78% expect seamless experiences across channels. Yet fewer than half of brands consistently deliver.
The issue is structural. When customer data lives in disconnected systems, teams will struggle to align insight, timing, and execution quickly enough to take meaningful action. AI canβt magic the problem away. According to the Adobe 2026 AI and digital trends report, fewer than half of organizations say their data foundation is adequate to support AI at scale.
At the initial stages of the modernization journey, the path to personalization can feel daunting. But progress will be easier than you think when you introduce a foundation for a unified customer experience.
Most brands have plenty of data. Itβs cohesion they lack. Your marketing team likely runs email, web, mobile, paid media, support, and even in-person channels. Each collects important signals, but are they sharing context across channels fast enough to shape the next interaction?
If not, impact is immediate. A customer browses a product online, then receives an email with a different price. Or a subscriber contacts support and has to repeat their story to multiple team members before getting help. Or a loyal customer happily purchases your productβonly to see the same ads promoting it in their feed for weeks after.
Even minor bumps along the customer journey chip away at trust. Nearly half of customers say they disengage when promotions feel irrelevant or mistimed.
Delivering a unified customer experience requires continuously updating your understanding of each customer and then immediately sharing that insight across every department and touchpoint.
This can require substantial change. But taking the following steps makes the path ahead more straightforward:
A unified experience starts with a single, living view of the customer.
Instead of keeping separate records for each channel, create a dynamic profile that reflects behavior, preferences, and history across all departments as customer activity happens in real time. Every click, purchase, service interaction, and loyalty update should feed into the same source of truth.
With that information, customer segmentation becomes smarter and messaging becomes more relevant. Customers stop receiving duplicative or contradictory communications. And performance can be more accurately measured across the full lifecycle.
This shift moves your marketing strategy from channel and campaign management to customer-first engagement. With a unified profile in place, teams respond to customers as individuals, not isolated events.Β
Accurate data doesnβt create value on its own. Those behavior signals must trigger action to shape meaningful engagement. Cart abandonment should prompt a quick follow-up (but not too quickly). Product recommendations should reflect recent browsing and past purchases. Irrelevant offers should be removed entirely. Journeys should evolve as preferences change.
Relevance largely depends on timing and second chances donβt come easily. Results from a Cognition Neuroscience Research project show the brain processes digital advertising in less than 400 milliseconds. Customers decide almost instantly whether a message applies to them. If systems canβt recognize context and activate insight within that window, the moment passes β and so does the opportunity to connect.
AI supports this speed at scale. It identifies patterns in customer data, anticipates purchase intent, flags churn risk, and determines next-best actions within milliseconds. Its effectiveness, however, depends on accurate, unified data. Reliable inputs enable relevant outcomes.
Privacy expectations are rising, and protecting customer data is a top priority. As organizations unify more signals and activate them in real time, governance canβt be layered on later. It has to be built in from the start.
To sustain a unified customer experience at scale, organizations need a modern cloud foundation that allows teams to process and activate data where it lives, reduce latency, limit unnecessary movement, and strengthen security controls.
In the cloud, data ingestion and activation happen faster. Infrastructure grows alongside customer volume. Compliance frameworks are embedded, not bolted on. And technology teams spend less time maintaining custom connections and more time enabling innovation.
Personalization succeeds when brands are prepared for the right moment, not just the right message. When your data foundation is unified, activation happens in real time, infrastructure is more secure, and personalization stops feeling experimental. Instead, it becomes operational. And relevance becomes repeatable.
Adobe Experience Platform on Amazon Web Services (AWS) brings these elements together and simplifies execution for your teams. Adobe Experience Platform creates real-time customer profiles that power segmentation, analytics, and journey orchestration across touchpoints. Deployed natively on AWS, it runs on scalable infrastructure designed for speed, resilience, and securityβwhile reducing technical maintenance and complexity.
Read the eBook, Capturing attention in the age of AI, to learn more about howAdobe and AWS provide the holistic view of your customer, which marketers need to deliver personalization, build retention, and increase customer lifetime value.
Or, if youβre ready to see specifically how Adobe and AWS can simplify your unique path to unified customer experiences, reach out and start the conversation today.
Noctua releases 3D CAD models for most of its products Noctua has released official 3D CAD models for many of its products, enabling CAD users and animators to incorporate Noctua products into their designs and renders. These models are free to download for many Noctua products and are available as STEP files. These files are [β¦]
The post Noctua releases 3D fan models for CAD users and renderers appeared first on OC3D.
Alien Isolationβs sequel will use Unreal Engine 5 β Creative Assembly Confirms Creative Assembly have recently released a teaser trailer for what could be Alien Isolation 2. Now, a Creative Assembly job listing has confirmed that their sequel to Alien Isolation will be βbuilt in Unreal Engine 5β. Gamers should note that the original Alien [β¦]
The post Alien Isolation 2 will use Unreal Engine 5 β Job listing confirms appeared first on OC3D.
GPU prices have stopped getting worse, but they have not gotten much better either. Demand has fallen, prices remain elevated, and most graphics cards still sell well above MSRP worldwide.
Intel is not only rolling right now, but also operating smartly, driving its revenue up by salvaging CPU dies and selling them off to hungry AI customers. CPUs Demand Is So High Right Now That Intel Got an Unexpected Margin Lift By Selling Salvaged Chips CPU demand is going off the charts as AI inferencing continues to surge with the arrival of Agentic AI. In countless posts, we have stated why CPUs have become so important for AI, a market that was previously dominated by GPUs. Now, AI inferencing is going after CPUs and Memory, in a big way, and [β¦]
Read full article at https://wccftech.com/intel-selling-cpu-dies-it-used-to-throw-in-the-trash-ai-demand-turns-scrap-into-profts/
Foxconn will be the lead supplier for NVIDIA's Groq 3 LPX, a chip designed specifically to boost AI inferencing capabilities. NVIDIA Vera Rubin Platforms To Benefit Greatly From Groq 3 LPX For Boosting AI Inferencing, Driving Foxconn's Share To Record Levels At GTC 2026, NVIDIA announced its Groq 3 LPX chip, in addition to the Vera Rubin AI platform. The Groq 3 LPX is an LPU that is designed to boost AI inferencing by up to 35x. The Groq 3 LPX rack will feature a total of 256 chips with 128 GB of SRAM and 12 TB of DDR5 memory, [β¦]
Read full article at https://wccftech.com/nvidia-35x-ai-inferencing-leap-arrives-early-foxconn-fast-fowards-groq-3-lpx-racks/
Today, Sony announced pricing changes for its PS5, PS5 Pro, and PS Portal consoles acrossΒ South Korea and Southeast Asia, effectiveΒ May 1, 2026. Sony cited "continued pressures in the global economic landscape" as the reason. This follows similar hikes already announced for North America, Brazil, Europe, and Japan, which came into effect onΒ April 2, 2026. You can find tables detailing the new, higher pricing in each territory below. New PS5 Console Prices by Territory Territory PS5 PS5 Digital PS5 Pro South Korea β©948,000 (~$693) β©858,000 (~$627) β©1,298,000 (~$949) Singapore SGD 849 (~$629) SGD 764 (~$566) SGD 1,167 (~$864) Malaysia MYR 2,799 [β¦]
Read full article at https://wccftech.com/ps5-ps5-pro-ps-portal-price-increase-asia-korea/
Assassin's Creed Black Flag Resynced has long been one of the worst-kept gaming secrets of the current console generation due to so many leaks over the years, but there's a second series remake that could earn the honor in the future. Following reports that Ubisoft is remaking other entries in its popular series besides its acclaimed fourth entry, known YouTuber and reliable series leaker j0nathan revealed that the very first Assassin's Creed game is getting a full remake. Unfortunately, the leaker didn't add much else on the matter other than that they have known since 2023. However, this is still [β¦]
Read full article at https://wccftech.com/original-2007-assassins-creed-remake-leak/
IteroGO offers GPS-synchronized audio walking tours in over 20 languages that work fully offline. You can browse city routes created by verified local guides, download them once, and enjoy audio playback as you reach each stop. Guides create tours from their phones, set prices, and earn revenue per download with a generous share, reaching travelers worldwide.
Laiki is a dating app where your AI does the searching and first conversations for you. Connect the apps you already use like music, books, calendar, and photos, so Laiki learns your taste, values, and the kind of person you click with. Your AI has real conversations with other people's AIs to test compatibility, and you receive a handful of vetted introductions each week with a full picture of why you fit: values, humor, life goals, and looks. If both want to meet, Laiki picks a time and place and then steps aside. No swiping, no openers to strangers, no burnout. Your raw data never leaves your device. Currently in private beta, launching on iOS and Android.
Valve Steam Controller release date revealed by leaked review Another review outlet has accidentally leaked its Steam Controller review. While the review is now hidden, it has unveiled the release date for Valveβs new controller. According to 4Gamers, the controller will be released on May 4th at 3 PM in Japan local time. Last week, [β¦]
The post Steam Controller release date leaks with early review appeared first on OC3D.
Last week, we learned more information on the Steam Controller via an early review by YouTuber Techy Talk that went live before the end of the embargo. Japanese publication 4Gamer has made the same mistake today, and its early review confirmed the controller will be released in just a week, on May 4. While the publication already took their early review down and their social media post promoting it, it wasn't swift enough to prevent some eagle-eyed Reddit users from saving both. Gaming Leaks and Rumors user ___Steve managed to save the images that accompanied 4Gamer's review, which offer a [β¦]
Read full article at https://wccftech.com/steam-controller-lands-may-4-steam-machine/
Intel Core 5 320, a Wildcat Lake CPU designed for budget laptops, has been tested, showcasing good numbers against its competition. Intel Wildcat Lake, Core 5 320, Shows ST and MT Wins Against Current-Gen Chips While Offering 50% iGPU Performance With Just A Quarter of The Xe3 Cores Wildcat Lake should turn out to be a surprise hit from Intel if OEMs build upon the reference design and specs. Just recently, we saw a stunning reference design from Intel, featuring an aluminum body, stunning colors, and decent specs for an everyday PC. Now, we have the first independent benchmarks coming [β¦]
Read full article at https://wccftech.com/intel-budget-wildcat-lake-chip-beats-apples-macbook-neo-a18-pro/
According to movie insider V Scooper, Nintendo is pitching a movie based on its sci-fi franchise Metroid. V Scooper added that Sony Pictures and Universal Pictures are fighting to win the rights to produce it: Metroid, last I heard a few months ago, was still in a bit of a push between studios, no updates since. Sony is one of the stronger contenders for Metroid, Universal is also fighting for it, both are leaning for live action but this could change. Both studios have experience adapting Nintendo IPs to the big screen. Universal, through its Illumination subsidiary, was extremely successful [β¦]
Read full article at https://wccftech.com/metroid-movie-sony-universal-bidding-war-nintendo/
Google's next-generation TPUv8e AI chip will reportedly utilize Intel Foundry's EMIB packaging, marking a series of wins for Intel in recent days. Intel Foundry Might Be Making Google's Next-Gen TPU With Its Advanced Packaging "EMIB" Capabilities Intel has been in the limelight for the past couple of days as it buisnesses gain traction from the recent surge in Agentic AI, which has led to CPUs becoming the hottest commodity after GPUs and memory. Now, reports are coming from Taiwanese outlet, Commercial Times, that Google will leverage Intel's EMIB technology for its next-generation TPU chip. Intel Foundry has already secured Tesla [β¦]
Read full article at https://wccftech.com/google-major-intel-foundry-customer-emib-advanced-packaging-for-next-gen-tpu/
A few hours ago, British developer Creative Assembly and publisher SEGA have posted what looks like a teaser trailer for Alien: Isolation 2 on the official YouTube channel of the first game. The teaser is only 25 seconds long, and most of the video is pitch black, but you can see the Creative Assembly and 20th Century Studios (which owns the IP) logos. The trailer is titled "False Sense of Security," and its description reads:Β "A feeling of being safer than one really is." Interestingly, DSO Gaming spotted that Alien: Isolation 2 will be powered by Epic's Unreal Engine 5 rather [β¦]
Read full article at https://wccftech.com/alien-isolation-2-teaser-unreal-engine-5/
Read to Unlock turns reading into screen time you actually earn. Scan a physical book page with your camera, answer a quick comprehension question, and collect credits to spend on your favorite apps. Use it to build a steady reading habit and enjoy guilt-free scrolling. The iOS app works without an account and enforces discipline that builds over time.
Saarathy is a multi-platform organizational suite that provides an all-in-one communication solution for any community. It offers a rich framework including chats, emails, calls, tasks, files, calendar, web hosting, support, networking, administration, and more. As sovereign software, it is self-hostable on cloud or PC and can be white-labeled with your own branding. Saarathy is approved by the Government E Marketplace, India, and is commercially available at $5 per user per year.
Qvery is an autonomous AI agent that tracks your brandβs visibility across AI search. Add your brand and it auto-generates topics and queries, runs daily checks in ChatGPT and Google AI Mode, and logs every citation and competitor it finds. From these responses, Qvery delivers insights like Visibility, Share of Voice, and Sentiment so you can measure, compare, and act on. The roadmap expands into a suite of marketing agents, including Mention Builder, UGC Agent, and Content Optimizer.
