The app also updated reply settings, allowing paying X users to give second degree connections the ability to comment on posts.

The brief comment function is being expanded beyond mutual followers and could potentially become a new way for creators to broadcast information.

The app highlighted the popularity of its public discussions during March Madness, though Threads and X still have more active users during live events.

New demographic data points could be valuable for brand partners, while Google’s latest Nano Banana model will help with image generation.

There may be opportunities for wellness brands that want to engage with people beyond the confines of a doctor’s office, according to a new study from the company.

New insight from the platform highlights the importance of variable signals within Pin recommendations. 

In just over a week, and months before the scheduled launch of GTA 6, GTA 5 will no longer be playable on Xbox Game Pass.

It's no secret that prices for electronics are skyrocketing across the board, and shortly after it seemed as though there may be some hope on the horizon, it has been revealed by VideoCardz that the ASUS AMD Radeon RX 9070 XT GPUs have seen a significant price increase in US markets. All three ASUS RX 9070 XT models listed on PCPartPicker have seen a substantial price increase in recent days, with the average increase coming out to around 17%.

The ASUS Prime OC Radeon RX 9070 XT saw its price go from $819.99 to 959.95 at both B&H and ASUS's own online store. It currently retails for the same $959.95 at Amazon, too. Similarly, the black version of the Prime OC RX 9070 XT and the ASUS TUF Gaming OC Radeon RX9070 XT have increased from $799.99 to $939.99 and $849.99 to $989.99, respectively. Curiously, the ASUS Prime OC RX 9070 XT can still be had at Newegg and Amazon for its lower $799.99 price, suggesting that this is effectively a pricing change that was implemented by ASUS when new GPUs were sent out to retailers.

When Blizzard rebranded Overwatch 2 to just Overwatch, it also announced a slew of new characters coming in 2026. One of those character designs, Anran, sparked upheaval in the community over her design being generic and a stark deviation from the character previewed in cinematics leading up to her introduction. Blizzard acknowledged the community feedback, announced an upcoming redesign, and has now subsequently shown off Anran's final design ahead of her launch in Season 2 on April 14.

The character's new look features a number of changes, mostly focussed on the facial shape, in order to make her design match her personality, which Overwatch game director, Aaron Keller, describes as "confident, determined, fierce, and a natural-born leader." The changes include giving her a more focussed expression, darkening the shading on her face, giving her a more defined jawline and a wider mouth and smile, and changing her posing to make her appear more confident. In general, critics of Anran's initial design seem to be appreciative of the changes, although, as is the case with anything related to gaming, there are still complaints about her looks.

Storm infostealer hijacks session cookies, bypassing multi-factor authentication, harvesting credentials, and enabling persistent account access across enterprise and cryptocurrency systems globally.

The contrast between Apple’s 50th anniversary and Xerox leadership change shows how early innovation alone rarely secures lasting relevance.

"Meta cannot be trusted with this" — an anti-smartglasses movement is brewing.

The Artemis II crew used an iPhone, and suddenly, nothing is more important about Apple's iconic product, not even the possibility of a foldable device.

Japan is advancing floating data center plans using converted ships, with Hitachi support, to address land shortages and growing AI infrastructure demand.

Arcee is a tiny 26-person U.S. startup that built a high-performing, massive, open source LLM. And it's gaining popularity with OpenClaw users.

Eclipse will put some of that money towards incubating, or building startups.

Google CEO Sundar Pichai said AI models could expose more software vulnerabilities and agreed it was plausible AI is affecting zero-day exploit markets.

The post Pichai Says AI Could ‘Break Pretty Much All Software’ appeared first on Search Engine Journal.

Google is giving advertisers new visibility into whether its automated recommendations actually drive performance — a long-standing blind spot in the platform.

What’s happening. A new “Results” tab within Recommendations shows the incremental impact of bidding and budget changes after they’ve been applied, allowing marketers to evaluate outcomes instead of relying on assumptions.

How it works. The feature attributes performance changes to specific recommendations, helping advertisers understand what effect adjustments like budget increases or bid strategy shifts had on results.

Why we care. Marketers can now validate whether recommendations improved performance, making it easier to decide which automated suggestions are worth adopting in the future.

Between the lines. Google has a vested interest in encouraging adoption of its recommendations, so providing performance data could build trust — but it also raises questions about how that impact is measured.

The catch. Advertisers may question whether the reported results are fully objective or skewed toward showing positive outcomes, given Google’s incentives.

What to watch. How detailed and transparent the reporting becomes — and whether advertisers see mixed or negative results alongside wins.

Bottom line. Google is moving from “trust us” to “here’s the proof,” but advertisers will be watching closely to see how impartial that proof really is.

First seen. This update was first spotted by Arpan Banerjee who shared seeing the new tab on LinkedIn.

Google is giving advertisers more control over how AI generates ad copy, making it easier to scale campaigns without losing brand consistency.

What’s happening. Google Ads is rolling out a beta feature that allows marketers to copy text guidelines from existing campaigns and apply them to new ones, eliminating the need to rewrite brand rules from scratch.

How it works. Advertisers can replicate approved tone, style and messaging rules across campaigns in one click, ensuring AI-generated ads stay aligned with brand standards while reducing setup time.

Why we care. The feature helps teams launch campaigns faster by reusing what already works, while maintaining consistency across large accounts where multiple campaigns run simultaneously.

Between the lines. This shift reflects a growing demand from marketers to “train” AI systems rather than rely on them blindly, effectively turning brand guidelines into reusable inputs for automation.

Bottom line. AI is speeding up ad creation, but control is becoming the real differentiator — and Google is starting to hand more of it back to advertisers.

First spotted. This update was spotted by Paid Media expert Arpan Banerjee when he shared spotting the alert on LinkedIn.

Replace Snipping Tool with Yoink. Using this tool, you can capture, edit, record, translate, and share your content seamlessly on Windows 11.

UK publisher Kwalee and independent studio Out of the Blue are pleased to announce that the Lovecraftian narrative puzzle adventure Call of the Elder Gods will launch on May 12, 2026. The game is coming to PC (via Steam), Nintendo Switch 2, PlayStation 5, and Xbox Series X|S, and is available day one with Xbox Game Pass. A sequel to 2020's award-winning Call of the Sea, Call of the Elder Gods is a single-player, first-person puzzle adventure with a strong narrative focus.

Players step into the roles of Professor Harry Everhart and newcomer Evangeline Drayton, solving intricate puzzles driven by logic, observation, and environmental interaction.Together, they journey from New England to the Australian desert, the frozen Arctic and the ancient city of Pnakotus, searching for missing loved ones while confronting personal grief.

A little over a year after the release of Assassin's Creed Shadows, Ubisoft has shipped the Title Update 1.1.10, which, aside from the usual bug fixes, adds PSSR 2 support to the game for PS5 Pro players and a number of quality-of-life updates and gameplay changes across all of the game's platforms. The full changelog is available via an Ubisoft news post.

Ubisoft has not detailed the exact visual upgrades wrought by the addition of PSSR 2, but we can likely expect smoother, higher frame rates with sharper upscaling, as has been seen in other games, like Resident Evil: Requiem and Cyberpunk 2077. As of the new update, all players will be able to access the Bo staff, which was previously locked behind the Claws of Awaji expansion. The Switch 2 version of Assassin's Creed Shadows also now features mouse and keyboard support, and the laundry list of bug fixes include UI fixes for damage indicators, a fix for an unintentional +100% stat cap in some cases, issues with fast travel points not being available, and progression getting stuck at 97.89% despite all content being completed.

Was it TikTok, WhatsApp, Facebook, or WeChat?

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According to longtime Intel watcher Jaykihn, Nova Lake's integrated graphics will be built around Xe3, the same generation used in Panther Lake integrated GPUs. Jaykihn had previously suggested that Nova Lake would include an Xe4 media component but has since walked that back, stating that "there is nothing Xe4 on...

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Intel is working on its own neural texture compression with similar compression performance to Nvidia's counterpart. Best of all, Intel has a fallback version of its compression tech that will work with GPUs that don't come with Intel's XMX engine.

Anthropic's latest frontier AI model, Claude Mythos Preview, is so adept at finding software vulnerabilities that the lab is holding it back to allow companies and institutions to proactively patch their products against the 'thousands' of bugs it has already uncovered.

ZeroTwo lets you access the combined capabilities of Claude, Perplexity, ChatGPT, Manus, and Higgsfield. These top AI platforms each have unique features that give them special abilities beyond their models. Now you can use all of them without paying for several subscriptions. Perplexity's agentic search, Claude's agentic connector, ChatGPT's apps, and Higgsfield's AI tools for creatives are all available on one platform.

The platform also offers deep research, canvas mode, and shared access to threads and projects. Plans include unlimited messages, expanded memory, priority performance, and team features for businesses.

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OrbitMeet is a browser-based AI meeting co-pilot that listens to your meetings in real time, surfaces questions you might miss every 75 seconds, and builds your summary as you talk with no plugins or installation.

It detects action items by speaker name, generates follow-up documents such as emails, memos, and action trackers in seconds, and works across Zoom, Teams, Google Meet, or in-person meetings. It's designed for consultants, founders, and distributed teams working in multiple languages. A free plan is available, with Pro at $20.5 CAD/month.

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It's officially marathon season, and if you're looking for new gear, I've rounded up our top-rated running shoes and smartwatches that are currently on sale at Amazon.

Microsoft and Yobi partner to deploy a 700 billion parameter AI model that predicts consumer intent using consented behavioral data across platforms.

A joint FBI, NSA, and CISA advisory warns that Iranian hackers have "escalated" their tactics in response to the ongoing U.S.-Israel war with Iran.

Nvidia-backed Asia AI data center provider Firmus has now raised $1.35 billion in six months.

Google says its AI-powered advertising tools are starting to deliver meaningful results, including major revenue gains for some retailers, as it experiments with how ads work in AI-driven search.

The big picture. Fears that AI chatbots like ChatGPT would disrupt Google’s core search business haven’t materialized, and instead the company’s ads business continues to grow, suggesting AI may be expanding how people search rather than replacing it.

By the numbers:

• Alphabet Inc. surpassed $400 billion in revenue in 2025.
• Q4 ad revenue: $82.28 billion (+13.5% YoY).
• YouTube ads: $11.38 billion (+~9% YoY).

What’s happened. Google is embedding ads into its AI-powered search experiences, including AI Mode powered by Gemini, while introducing new ad formats designed for conversational queries and tools that allow brands to shape how they appear in AI-generated answers, with a new “business agent” feature enabling companies like Poshmark and Reebok to control how their products are represented.

Driving the results. AI-driven campaigns like Performance Max and AI Max match ads to more detailed and conversational search intent, and Google says queries in AI Mode are often two to three times longer than traditional searches, giving the system more context to connect users with relevant products, as seen with Aritzia, which reported an 80% increase in revenue after adopting AI Max.

How it works. The system scans a retailer’s website and creative assets, interprets user intent from conversational queries, and dynamically matches products and messaging in real time. This is increasingly important given that 15% of daily searches are entirely new (according to Google) and cannot be predicted through traditional keyword targeting.

Why we care. Google is shifting from keyword-based ads to intent-driven, AI-matched advertising, meaning campaigns can reach consumers with far more precision at the moment they’re ready to buy. As search becomes more conversational and unpredictable, advertisers who rely on traditional targeting risk falling behind those using AI-driven formats that automatically adapt to new user behavior.

Zoom in. Google is testing new formats such as “direct offers,” which deliver personalized promotions when users show purchase intent, using Gemini to analyze conversational context and behavior, with brands like E.l.f. Beauty, Chewy and L’Oréal participating in early trials.

Commerce push. Google is also advancing its commerce strategy through a Universal Commerce Protocol developed with Shopify, which allows purchases to happen directly within AI conversations.

Yes, but. Google is not alone in experimenting with ads in AI search, and early results across the industry have been mixed, as Amazon has reportedly seen limited traction from ads in its AI shopping assistant, OpenAI continues to explore monetization models, and Perplexity AI has begun phasing out ads after underwhelming performance.

What they’re saying, Google positions itself as a “matchmaker” rather than a retailer, emphasizing that AI helps deliver more relevant and personalized ads while allowing brands to maintain control over their messaging and build user trust by showing the right product at the right moment.

What’s next. Gooogle says it has no current plans to introduce ads directly into Gemini but will continue testing and expanding advertising within AI Mode, including more personalized offers and AI-driven shopping experiences.

Bottom line. AI is not replacing search but reshaping it, and for Google that shift is making advertising more conversational, more targeted and, in some cases, significantly more profitable.

Dig deeper. Google says its AI-powered ads help some brands lift online sales by 80%.

Google Search is evolving beyond links and answers into a system that completes tasks, potentially fundamentally changing how users interact with the web. That’s according to Alphabet CEO Sundar Pichai, speaking on the Cheeky Pint podcast.

Why we care. Google is signaling a move from information retrieval to task execution.

Search becoming agentic. Traditional search behavior is already changing and will continue to, Pichai said.

• “If I fast-forward, a lot of what are just information-seeking queries will be agentic in Search. You’ll be completing tasks. You’ll have many threads running.”

Pichai also described a future where Google Search acts less like a list of results and more like a system that coordinates actions:

• “Search would be an agent manager in which you’re doing a lot of things. I think in some ways, I use Antigravity today, and you have a bunch of agents doing stuff. I can see search doing versions of those things, and you’re getting a bunch of stuff done.”

AI Mode is already changing queries. Users are already adapting their behavior in Google’s AI-powered search experiences, Pichai said:

• “But today in AI Mode in Search, people do deep research queries. That doesn’t quite fit the definition of what you’re saying. But people adapted to that. I think people will do long-running tasks.”

Search vs. Gemini overlap. Despite the rise of Gemini, Pichai said Google isn’t replacing Search with a chatbot. Instead, the two will coexist — and diverge (echoing what Liz Reid said last month):

• “We are doing both Search and Gemini. They will overlap in certain ways. They will profoundly diverge in certain ways. I think it’s good to have both and embrace it.”

The interview. The history and future of AI at Google, with Sundar Pichai

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Google’s AI Overviews answered a standard factual benchmark correctly 91% of the time in February, up from 85% in October, according to a New York Times analysis with AI startup Oumi.

However, Google handles more than 5 trillion searches per year, so that means tens of millions of answers every hour may be wrong.

Why we care. We’ve watched Google shift from linking to sources to summarizing them for more than two years. This report suggests AI Overviews are improving, but still mix correct answers, weak sourcing, and clear errors in ways that can mislead searchers and reshape which publishers get visibility and clicks.

The details. Oumi tested 4,326 Google searches using SimpleQA, a widely used benchmark for measuring factual accuracy in AI systems, the Times reported. It found AI Overviews were accurate 85% of the time with Gemini 2 and 91% after an upgrade to Gemini 3.

• The bigger problem may be sourcing. Oumi found that more than half of the correct February responses were “ungrounded,” meaning the linked sources didn’t fully support the answer.
• That makes verification harder. The answer may be right, but the cited pages may not clearly show why.

What changed. Accuracy improved between October and February, but grounding worsened. In October, 37% of correct answers were ungrounded; in February, that rose to 56%.

Examples. The Times highlighted several misses:

• For a query about when Bob Marley’s home became a museum, Google answered 1987; the correct year was 1986, according to the Times, and the cited sources didn’t support the claim or conflicted.
• For a query about Yo-Yo Ma and the Classical Music Hall of Fame, Google linked to the organization’s site but still said there was no record of his induction.
• In another case, Google gave the correct age at Dick Drago’s death but misstated his date of death.

Google’s response: Google disputed the Times analysis, saying the study used a flawed benchmark and didn’t reflect what people actually search. Google spokesperson Ned Adriance told the Times the study had “serious holes.”

• Google also said AI Overviews use search ranking and safety systems to reduce spam and has long warned that AI responses can contain mistakes.

The report. How Accurate Are Google’s A.I. Overviews? (subscription required)

Microsoft has announced April's wave of Xbox Game Pass additions, and it includes the Call of Duty: Modern Warfare reboot, Hades 2, and many other titles.

Cyberpunk 2077 has been out since 2022, but it seems as though CD Projekt Red's dedication to the game has not waned, with a new April 8 update bringing enhancements to the game on the PS5 Pro. As detailed in a new PlayStation Blog post, Cyberpunk 2077's PS5 Pro update will bring a slew of visual changes to the game on PlayStation 5 Pro. The biggest change is that it will now use PSSR to upscale the game to 4K, and it will feature ray traced lighting, shadows, and reflections on PS5 Pro. It will be a free update that will be available for players playing on a PlayStation 5 Pro.

Cyberpunbk 2077 PS5 Pro Enhanced version will feature three gameplay modes, giving gamers the choice to optimize their gameplay experience for visuals or the best performance. Ray Tracing Pro mode will enable all RT features, including RT reflections, ambient occlusion, skylight, shadows, and emissive lighting, with a frame rate target of 40 FPS on VRR displays or 30 FPS without VRR. Performance mode will feature the highest frame rate target, at 90 FPS with "high image fidelity," although it isn't specified which features are enabled in Performance mode. Meanwhile, Ray Tracing mode will target 60 FPS with "select ray tracing enhancements" enabled, although CDPR again doesn't specify resolution or RT enhancements for this mode.

PeaZip 11.0 refines one of the most capable free archivers with faster browsing, smoother drag-and-drop across tabs, and a cleaner, more responsive UI. The update also improves scaling, adds flexible icon rendering, and introduces batch archive testing, alongside the usual fixes and cleanup.

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The newly announced Netflix Playground is an all-in-one app designed to give children a curated gaming experience built around familiar cartoon characters. The streaming giant describes it as an ever-growing library of instantly playable games for kids aged 8 and under.

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Shadow OS is the first decision-making app built on 64 hexagrams, the same system Carl Jung studied for over two decades and called his most significant method for surfacing what the unconscious already knows. Other decision apps use random spinner wheels, AI chatbots validate whatever you say, and astrology apps offer forecasts open to interpretation. Shadow OS gives you one committed answer: move forward, hold, or pull back.

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BeMusic AI is a free AI music generator that turns text prompts into fully produced, royalty-free songs in under 30 seconds. Choose from 50+ genres, adjust mood, tempo, and energy, and download high-quality WAV or MP3 for videos, games, podcasts, and ads. It also offers tools to write lyrics, create instrumentals, convert audio to MIDI, edit MIDI, make AI covers, remove vocals, extend tracks, and analyze songs. Use it to avoid copyright issues and keep full ownership of every track.

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The Russia-linked threat actor known as APT28 (aka Forest Blizzard) has been linked to a new campaign that has compromised insecure MikroTik and TP-Link routers and modified their settings to turn them into malicious infrastructure under their control as part of a cyber espionage campaign since at least May 2025. The large-scale exploitation campaign has been codenamed 

Using ChatGPT in CarPlay turns routine drives into more conversational and entertaining experiences

Cisco execs are discussing what they need to send data centers to space, but we're a long way off that just yet.

The Nikon D5's still-unbeaten low-light performance and proven build quality made it NASA's choice for the Artemis II mission's most important photographs.

Intel will join SpaceX and Tesla in an effort to build a new U.S. semiconductor factory in Texas, although the scope of its contributions are unclear.

The new model will be used by a small number of high-profile companies to engage in defensive cybersecurity work.

The news follows a report from Nikkei Asia on Tuesday that raised concerns the company’s foldable iPhone could be delayed due to challenges during the phone’s engineering test phase.

These new features are designed to streamline your browser and help you maximize productivity in Chrome.

Google has begun placing sponsored ad units directly inside the Images tab of mobile search results — a new placement that eligible campaigns can access without any changes to existing keyword targeting.

What’s happening. When a user navigates to the Images tab within Google Search on mobile, they may now see sponsored units appearing within the image grid. Each unit shows a full image creative as the primary visual alongside text, and is clearly labelled “Sponsored” — consistent with how Google labels ads elsewhere in search results.

How it works. Eligible campaigns can serve into the Images tab without any changes to keyword targeting or campaign structure. The placement draws from existing image assets, meaning advertisers running Search or Performance Max campaigns with strong visual creative are best positioned to benefit. No separate image-only campaign setup is required.

Why we care. This is a meaningful expansion of Google’s paid search real estate. For product-led and catalog-heavy advertisers, the Images tab is where purchase-intent discovery often starts — and now ads can appear right in that moment. If your campaigns already use strong image assets, you may be picking up incremental impressions without lifting a finger.

The big picture. Early indications suggest this placement behaves more like a visual discovery surface than classic paid search. Expect high impression volume but lower click-through rates — more in line with display or Shopping than traditional text ads. That said, the assist value in multi-touch conversion paths could be significant, particularly for retail and direct-to-consumer brands. Treat it as upper-funnel reach, not a last-click channel.

What to watch. Google has not made a formal announcement, and there is no dedicated reporting breakdown for Images tab placements yet. Monitor your impression share and segment data closely to understand whether this placement is contributing — and whether it’s eating into organic image visibility for competitors.

First seen. The placement was spotted by Google Ads Expert – Matteo Braghetta, who shared seeing this update on LinkedIn. No official documentation has been published by Google at the time of writing.

Over 30% of outbound clicks go to just 10 domains, with Google alone taking more than 20%, according to a new Semrush study published today.

ChatGPT also relies less on the live web, triggering search on 34.5% of queries, down from 46% in late 2024.

The big picture. ChatGPT’s growth has plateaued, and its role in how users navigate the web is evolving unevenly.

• Referral traffic from ChatGPT grew 206%, comparing January 2025 to January 2026.

The details. Most ChatGPT referral traffic still goes to a small set of sites, even as more sites receive some traffic.

• Google accounts for 21.6% of all ChatGPT referral traffic.
• The next nine domains bring the top 10 to just over 30% of referrals.
• Most other sites get a long tail of minimal traffic.
• The number of domains receiving referrals expanded, peaking at around 260,000 in 2025 before settling near 170,000.

Why we care. Visibility in ChatGPT doesn’t translate evenly into traffic, and you’ll likely see marginal referral impact. The decline in search-triggered queries also limits your chances to earn citations and traffic.

When ChatGPT searches. It defaults to pre-trained knowledge and uses web search in specific cases, including:

• User requests for sources.
• Questions about recent events.
• Situations where the model lacks confidence.

Behavior shift. Most ChatGPT prompts still don’t resemble traditional search queries.

• Between 65% and 85% of prompts don’t match standard keywords, reflecting more complex, conversational inputs.
• Meanwhile, engagement is deepening. Queries per session jumped 50% in late 2025.

About the data. Semrush analyzed more than 1 billion lines of U.S. clickstream data from October 2024 to February 2026 across a 200 million-user panel, tracking prompts, referral destinations, and search usage.

The study. ChatGPT traffic analysis: Insights from 17 months of clickstream data

Malware ploys from bad actors are getting more elaborate, as axios maintainer Jason Saayman explains how the registry's hijacking was weeks in the making and involved a fake Teams update that delivered a trojan.

2026 has thus far been a busy year for gaming mice releases, with hits like the Razer Viper V4 Pro and VXE's upcoming Logitech G305 alternative launching already. Now, SteelSeries seems to be making something of a come-back in the gaming mouse game, with an as yet unreleased Rival Pro and Rival Pro Mini, which have shown up on Reddit in what appears to be an accidental early leak. If the retail packaging shown off in the Reddit post is anything to go by, the mouse will have a couple of nifty features to set it apart from the rest of SteelSeries's line-up.

Despite the Rival moniker, the Rival Pro Mini looks a lot more like the SteelSeries Prime wireless mouse than the rest of the SteelSeries Rival gaming mice. The Rival Pro Mini will weigh in at 49 g and use the PixArt PAW 3950 sensor that has become ubiquitous in flagship gaming mice in recent years. The Rival Pro Mini's main clicks will be optical switches with a 100 million-click MTBF rating. One of the standout features is the "Infinite Power" swappable battery system, which is similar to those used by Angry Miao in the Infinity AM series and Glorious in the Model O3 Wireless. The Rival Pro and Pro Mini will also have 8 kHz wireless connectivity and 100% PTFE skates.

Late last week, we reported on a new series of rowhammer bit-flip attacks targeting GDDR6-based NVIDIA GPUs. Most of these attacks can be mitigated by enabling IOMMU through the BIOS, which restricts the memory regions the GPU can access on the host system, thereby closing the primary attack path. However, researchers from the University of Toronto have introduced "GPUBreach," which can bypass IOMMU and enable CPU-side privilege escalation, unlike the previous "GDDRHammer" and "GeForge" attacks. In most typical server, workstation, and even PC configurations, IOMMU restricts the GPU's access to the CPU's physical addresses, preventing direct memory access. These are the typical DMA-based attacks that the Input-Output Memory Management Unit protects users from. However, the new "GPUBreach" operates differently.

For example, "GPUBreach" exploits memory-safe bugs in the actual GPU driver and corrupts them. When IOMMU confines the GPU's direct memory access to driver-assigned buffers, the new exploit corrupts metadata within these permitted buffers. This causes the driver, which has kernel privileges enabled on the CPU host, to perform out-of-band writes to the buffer, effectively bypassing any protection IOMMU can offer. This logic is built into the kernel by default, as the GPU driver is one of the most trusted components of the operating system. Hence, IOMMU bypass is possible when the metadata is corrupted. Since "GPUBreach" grants an attacker full root privilege escalation, the attack differs significantly from previous rowhammer attacks.

Speaking to Windows users on X this week, Microsoft's Director of Design, March Rogers, said the company is working to address several UI issues across Windows 11. To that end, all settings options are being consolidated in a single location, ensuring users will no longer need to switch between the...

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The 2TB SanDisk Extreme Pro UHS-II SD card costs $2,000, bringing its price per GB to nearly $1, making it more than four times more expensive than much faster microSD Express cards.

A compact office mini PC powered by Intel's 12th Gen Core i5-12600H processor with plenty of upgrade potential and power enough for a three-monitor setup.

A bombed casino complex near the Cambodia–Thailand border reveals how modern scam factories mimic official institutions to deceive victims.

There are simple steps everyone can take to identify a fake video - and most include pixel hunting.

The research-backed 'body saw' exercise should be your summer six-pack builder.

HP OmniDesk Desktop features a 20-core Core Ultra 7-265 processor, 32GB of DDR5 memory, a fast 1TB SSD, and a woodgrain finish, and it's now $770 off.

The AirTag-rival packs three handy safety features, including a siren, strobe light, and alerts to selected contacts.

Xbox has unveiled the batch of Xbox Game Pass titles for the month of April, and it includes some absolute bangers like The Elder Scrolls 4: Oblivion Remastered, Day Z, and more.

Walmart's latest streamer isn't official but it's already in some stores and the full specs are now here

Sea of Stars just launched for mobile with a special early discount.

The FBI's new IC3 report dissects the state of ransomware, and discusses attacks on hospitals and critical infrastructure firms.

Here's how to watch Sporting Lisbon vs Arsenal in the first leg of their Champions League 2025-26 quarter-final at the José Alvalade Stadium.

In his guidelines, Russia's Ministry of Digital Development highlighted some limitations in VPN detection, which could also help residents navigate the crackdown.

After a wave of screen-only cameras and even the removal of viewfinders in recent updates of various models, I asked you if you'd buy a camera without a viewfinder. Here's what you said.

Sony has revealed more about its 2026 True RGB TV tech, which replaces the traditional backlight with individually controlled red, green, and blue LEDs for greater brightness, color accuracy, and control.

Here's how to watch Real Madrid vs Bayern Munich in the first leg of their Champions League 2025-26 quarter-final at the iconic Santiago Bernebeu.

What happens when a controversial lawyer rewrites rules of justice with dangerous brilliance? Here's how to watch Avvocato Ligas from anywhere in the world.

Amazon launched a big tech sale over the Easter bank holiday weekend, but there's still time to score several of the best deals before they're gone — I've picked out the 18 top offers.

Fancy Bear, also known as APT28, has taken over thousands of residential home routers to steal passwords and authentication tokens in a wide-ranging espionage operation.

Google Chrome's latest update brings vertical tabs and a cleaner Reading Mode to help manage cluttered browsing.

The app uses iPhone Live Activities to alert you when scary scenes are about to happen, while also tracking what to watch and where to stream it.

Uber is expanding its AWS contract to run more of its ride-sharing features on Amazon's chips. This is a thumb-of-the nose at Oracle and Google.

Anthropic bulked up its compute deal with Google and Broadcom as the company has seen its run-rate revenue surge to $30 billion.

Google doesn’t train Gemini using personal emails. Here’s how Google keeps private data secure in Gmail amid new AI model upgrades.

Android XR adds spatial conversion for 2D apps, the ability to pin apps to your walls and more ways to watch, create, and explore.

The new Google Educator Group will make AI training available to 146,000 educators who will in turn serve 1.6 million students.

We’re making it easier for people to share photos and videos, and keep track of their progress.

Google is rolling out new Google Maps features that make it easier to contribute photos, reviews, and local insights, while adding Gemini-powered caption suggestions.

Local Guides redesign. Contributor profiles are getting more visibility. Total points now appear more prominently, Local Guide levels are easier to spot, and badge designs have been refreshed.

• Top contributors will also stand out more in reviews with new gold profile indicators.

AI caption drafts. Google is also introducing AI-generated caption drafts. Gemini analyzes selected images and suggests text you can edit or discard.

• Caption suggestions are available in English on iOS in the U.S., with Android and broader global expansion planned.

Media sharing. Google Maps now shows recent photos and videos directly in the Contribute tab, making uploads faster.

• If you enable media access, Google Maps will suggest images from your camera roll that are ready to post with a tap.
• This feature is now live globally on iOS and Android.

Why we care. Google is making it easier to create and scale fresh local content, which can directly affect rankings and visibility. At the same time, stronger contributor signals may influence which reviews users trust and which businesses win clicks.

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Google once attributed two of Barry Schwartz’s Search Engine Land articles to me — a misclassification at the annotation layer that briefly rewrote authorship in Google’s systems.

For a few days, when you searched for certain Search Engine Land articles Schwartz had written, Google listed me as the author. The articles appeared in my entity’s publication list and were connected to my Knowledge Panel.

What happened illustrates something the SEO industry has almost entirely overlooked: that annotation — not the content itself — is the key to what users see and thus your success.

How Google annotated the page and got the author wrong

Googlebot crawled those pages, found my name prominently displayed below the article (my author bio appeared as the first recognized entity name beneath the content), and the algorithm at the annotation gate added the “Post-It” that classified me as the author with high confidence.

This is the most important point to bear in mind: the bot can misclassify and annotate, and that defines everything the algorithms do downstream (in recruitment, grounding, display, and won). In this case, the issue was authorship, which isn’t going to kill my business or Schwartz’s.

But if that were a product, a price, an attribute, or anything else that matters to the intent of a user search query where your brand should be one of the obvious candidates, when any aspect of content is inaccurately annotated, you’ve lost the “ranking game” before you even started competing.

Annotation is the single most important gate in taking your brand from discover to won, whatever query, intent, or engine you’re optimizing for.

What annotation is and why it isn’t indexing

Indexing (Gate 4) breaks your content into semantic chunks, converts it, and stores it in a proprietary format. Annotation (Gate 5) then labels those chunks with a confidence-driven “Post-It” classification system.

It’s a pragmatic labeler and attaches classifications to each chunk, describing:

• What that chunk contains factually.
• In what circumstances it might be useful.
• The trustworthiness of the information.

Importantly, it’s mostly unopinionated when labeling facts, context, and trustworthiness. Microsoft’s Fabrice Canel confirmed the principle that the bot tags without judging, and that filtering happens at query time.

What does that mean? The bot annotates neutrally at crawl time, classifying your content without knowing what query will eventually trigger retrieval. 

Annotation carries no intent at all. It’s the insight that has completely changed my approach to “crawl and index.”

That clearly shows you that indexing isn’t the ultimate goal. Getting your page indexed is table stakes. Full, correct, and confident annotation is where the action happens: an indexed page that is poorly annotated is invisible to each of the algorithmic trinity.

The annotation system analyzes each chunk using one or more language models, cross-referenced against the web index, the knowledge graph, and the models’ own parametric knowledge. But it analyzes each chunk in the context of the page wrapper. 

The page-level topic, entity associations, and intent provide the frame for classifying each chunk. If the page-level understanding is confused (unclear topic, ambiguous entity, mixed intent), every chunk annotation inherits that confusion. Even more importantly, it assigns confidence to every piece of information it adds to the “Post-Its.”

The choices happen downstream: each of the algorithmic trinity (LLMs, search engines, and knowledge graphs) uses the annotation to decide whether to absorb your content at recruitment (Gate 6). Each has different criteria, so you need to assess your own content for its “annotatability” in the context of all three.

And a small but telling detail: Back in 2020, Martin Splitt suggested that Google compares your meta description to its own LLM-generated summary of the page. When they match, the system’s confidence in its page-level understanding increases, and that confidence cascades into better annotation scores for every chunk — one of thousands of tiny signals that accumulate.

Annotation is the key midpoint of the 10-gate pipeline, where the scoreboard turns on. Everything before it is infrastructure: “Can the system access and store your content?” Everything after it is competition:

When you consider what happens at the annotation gate and its depth, links and keywords become the wrong lens entirely. They describe how you tried to influence a ranking system, whereas annotation is the mechanism behind how the algorithmic trinity chooses the content that builds its understanding of what you are.

The frame has to shift. You’re educating algorithms. They behave like children, learning from what you consistently, clearly, and coherently put in front of them. With consistent, corroborated information, they build an accurate understanding.

Given inconsistent or ambiguous signals, they learn incorrectly and then confidently repeat those errors over time. Building confidence in the machine’s understanding of you is the most important variable in this work, whether you call it SEO or AAO.

In 2026, every AI assistive engine and agent is that same child, operating at a greater scale and with higher stakes than Google ever had. Educating the algorithms isn’t a metaphor. It’s the operational model for everything that follows.

For a more academic perspective, see: “Annotation Cascading: Hierarchical Model Routing, Topical Authority, and Inter-Page Context Propagation in Large-Scale Web Content Classification.”

5 levels of annotation: 24+ dimensions classifying your content at Gate 5

When mapping the annotation dimensions, I identified 24, organized across five functional categories. After presenting this to Canel, his response was: “Oh, there is definitely more.”

Of course there are. This taxonomy is built through observation first, then naming what consistently appears. The [know/guess] distinctions follow the same logic: test hypotheses, eliminate what doesn’t hold up, and keep what remains.

The five functional categories form the foundation of the model. They are simple by design — once you understand the categories, the dimensions follow naturally. There are likely additional dimensions beyond those mapped here.

What follows is the taxonomy: the categories are directionally sound (as confirmed by Canel), while the specific dimension assignments reflect observed behavior and remain incomplete.

Level 1: Gatekeepers (eliminate)

• Temporal scope, geographic scope, language, and entity resolution. Binary: pass or fail. 
• If your content fails a gatekeeper (wrong language, wrong geography, or ambiguous entity), it is eliminated from that query’s candidate pool instantly. The other dimensions don’t come into play.

Level 2: Core identity (define)

• Entities, attributes, relationships, sentiment. 
• This is where the system decides what your content means:
  • Who is being discussed.
  • What facts are stated.
  • How entities relate.
  • What the tone is. 
• Without clear core identity annotations, a chunk carries no semantic weight in any downstream gate.

Level 3: Selection filters (route) 

• Intent category, expertise level, claim structure, and actionability. 
• These determine which competition pool your content enters.
  • Is this informational or transactional? 
  • Beginner or expert? 
• Wrong pool placement means competing against content that is a better match for the query, and you’ve lost before recruitment or ranking begins.

Level 4: Confidence multipliers (rank)

• Verifiability, provenance, corroboration count, specificity, evidence type, controversy level, and consensus alignment. These scale your ranking within the pool. 
• This is where validated, corroborated, and specific content outranks accurate but unvalidated content. 
• The multipliers explain why a well-sourced third-party article about you often outperforms your own claims: provenance and corroboration scores are higher.
• Confidence has a multiplier effect on everything else and is the most powerful of all signals. Full stop.

Level 5: Extraction quality (deploy)

• Sufficiency, dependency, standalone score, entity salience, and entity role. These determine how your content appears in the final output. 
• Is this chunk a complete answer, or does it need context? Is your entity the subject, the authority cited, or a passing mention? 
• Extraction quality determines whether AI quotes you, summarizes you, or ignores you.

Across all five levels, a confidence score is attached to every individual annotation. Not just what the system thinks your content means, but how certain it is.

Clarity drives confidence. Ambiguity kills it.

Canel also confirmed additional dimensions I had not initially mapped: audience suitability, ingestion fidelity, and freshness delta. These sit across the existing categories rather than forming a sixth level.

In 2022, Splitt named three annotation behaviors in a Duda webinar that map directly onto the five-level model. The centerpiece annotation is Level 2 in direct operation: 

• “We have a thing called the centerpiece annotation,” Splitt confirmed, a classification that identifies which content on the page is the primary subject and routes everything else — supplementary, peripheral, and boilerplate — relative to it. 
• “There’s a few other annotations” of this type, he noted. 

Annotation runs before recruitment, which means a chunk classified as non-centerpiece carries that verdict into every gate that follows. Boilerplate detection is Level 3: content that appears consistently across pages — headers, footers, navigation, and repeated blocks — enters a different competition pool based on its structural role alone. 

• “We figure out what looks like boilerplate and then that gets weighted differently,” Splitt said 

Off-topic routing closes the picture. A page classified around a primary topic annotates every chunk relative to that centerpiece, and content peripheral to the primary topic starts its own competition pool at a disadvantage before Recruitment begins. 

Splitt’s example: a page with 10,000 words on dog food and a thousand on bikes is “probably not good content for bikes.” The system isn’t ignoring the bike content. It’s annotating it as peripheral, and that annotation is the routing decision.

---

The multiplicative destruction effect: When one near-zero kills everything

In Sydney in 2019, I was at a conference with Gary Illyes and Brent Payne. Illyes explained that Google’s quality assessment across annotation dimensions was multiplicative, not additive. 

Illyes asked us not to film, so I grabbed a beer mat and noted a simple calculation: if you score 0.9 across each of 10 dimensions, 0.9 to the power of 10 is 0.35. You survive at 35% of your original signal. If you score 0.8 across 10 dimensions, you survive at 11%. If one dimension scores close to zero, the multiplication produces a result close to zero, regardless of how well you score on every other dimension.

Payne’s phrasing of the practical implication was better than mine: “Better to be a straight C student than three As and an F.”

The beer mat went into my bag. The principle became central to everything I’ve built since.

The multiplicative destruction effect has a direct consequence for annotation strategy: the C-student principle is your guide. 

• A brand with consistently adequate signals across all 24+ dimensions outperforms a brand with brilliant signals on most dimensions and a near-zero on one. The near-zero cascades. 
• A gatekeeper failure (Level 1) eliminates the content entirely. 
• A core identity failure (Level 2) misclassifies it so badly that high confidence multipliers at Level 4 are applied to the wrong entity. 
• An extraction quality failure (Level 5) produces a chunk that the system can retrieve but can’t deploy usefully. The failure doesn’t have to be dramatic to be fatal.

At the annotation stage, misclassification, low confidence, or near-zero on one dimension will kill your content and take it out of the race.

Nathan Chalmers, who works at Bing on quality, told me something that puts this in a different light entirely. Bing’s internal quality algorithm, the one making these multiplicative assessments across annotation dimensions, is literally called Darwin. 

Natural selection is the explicit model: content with near-zero on any fitness dimension is selected against. The annotations are the fitness test. The multiplicative destruction effect is the selection mechanism.

How annotation routes content to specialist language models

The system doesn’t use one giant language model to classify all content. It routes content to specialized small language models (SLMs): domain-specific models that are cheaper, faster, and paradoxically more accurate than general LLMs for niche content. 

A medical SLM classifies medical content better than GPT-4 would, because it has been trained specifically on medical literature and knows the entities, the relationships, the standard claims, and the red flags in that domain.

What follows is my model of how the routing works, reconstructed from observable behavior and confirmed principles. The existence of specialist models is confirmed. The specific cascade mechanism is my reconstruction.

The routing follows what I call the annotation cascade. The choice of SLM cascades like this:

• Site level (What kind of site is this?)
• Refined by category level (What section?)
• Refined by page level (what specific topic?)
• Applied at chunk level (What does this paragraph claim?)

Each level narrows the SLM selection, and each level either confirms or overrides the routing from above. This maps directly to the wrapper hierarchy from the fourth piece: the site wrapper, category wrapper, and page wrapper each provide context that influences which specialist model the system selects.

The system deploys three types of SLM simultaneously for each topic. This is my model, derived from the behavior I have observed: annotation errors cluster into patterns that suggest three distinct classification axes. 

• The subject SLM classifies by subject matter — what is this about? — routing content into the right topical domain. 
• The entity SLM resolves entities and assesses centrality and authority: who are the key players, is this entity the subject, an authority cited, or a passing mention? 
• The concept SLM maps claims to established concepts and evaluates novelty, checking whether what the content asserts aligns with consensus or contradicts it.

When all three return high confidence on the same entity for the same content, annotation cost is minimal, and the confidence score is very high. When they disagree (i.e., the subject SLM says “marketing,” but the entity SLM can’t resolve the entity, and the concept SLM flags the claims as novel), confidence drops, and the system falls back to a more general, less accurate model.

The key insight? LLM annotation is the failure mode. The system wants to use a specialist. It defaults to a generalist only when it can’t route to a specialist. Generalist annotation produces lower confidence across all dimensions. 

The practical implication 

Content that’s category-clear within its first 100 words, uses standard industry terminology, follows structural conventions for its content type, and references well-known entities in its domain triggers SLM routing. 

Content that’s topically ambiguous or terminologically creative gets the generalist. Lower confidence propagates through every downstream gate.

Now, this may not be the exact way the SLMs are applied as a triad (and it might not even be a trio). However, two things strike me:

• Observed outputs act that way.
• If it doesn’t function this way, it would be.

First-impression persistence: Why the initial annotation is the hardest to correct

Here is something I’ve observed over years of tracking annotation behavior. It aligns with a principle Canel confirmed explicitly for URL status changes (404s and 301 redirects): the system’s initial classification tends to stick.

When the bot first crawls a page, it selects an SLM, runs the annotation, assigns confidence scores, and saves the classification. The next time it crawls the same page, it logically starts with the previously assigned model and annotations. I call this first-impression persistence. 

The initial annotation is the baseline against which all subsequent signals are measured. The system doesn’t re-evaluate from scratch. It checks whether the new crawl is consistent with the existing classification, and if it is, the classification is reinforced.

Canel confirmed a related mechanism: when a URL returns a 404 or is redirected with a 301, the system allows a grace period (very roughly a week for a page, and between one and three months for content, in my observation) during which it assumes the change might revert. After the grace period, the new state becomes persistent. I believe the same principle applies to content classification: a window of fluidity after first publication, then crystallization.

I have direct evidence for the correction side from the evolution of my own terminologies. When I first described the algorithmic trinity, I used the phrase “knowledge graphs, large language models, and web index.” Google, ChatGPT, and Perplexity all picked up on the new term and defined it correctly.

A month later, I changed the last one to “search engine” because it occurred to me that the web index is what all three systems feed off, not just the search system itself. At the point of correction, I had published roughly 10 articles using the original terminology. 

I went back and invested the time to change every single one, updating every reference, leaving zero traces. A month later, AI assistive engines were consistently using “search engine” in place of “web index.”

The lesson is that change is possible, but you need to be thorough: any residual contradictory signal (one old article, one unchanged social post, and one cached version) maintains inertia proportionally. Thoroughness is the unlock, rather than time.

A rebrand, career pivot, or repositioning is the practical example. You can change the AI model’s understanding and representation of your corporate or personal brand, but it requires thoroughly and consistently pivoting your digital footprint to the new reality.

In my experience, “on a sixpence” within a week. I’ve done this with my podcast several times. Facebook achieved the ultimate rebrand from an algorithmic perspective when it changed its name to Meta.

The practical implication

Get your annotation right before you publish. The first crawl sets the baseline. A page published prematurely (with an unclear topic or ambiguous entity signals) crystallizes into a low-confidence annotation, and changing it later requires significantly more effort than getting it right the first time.

Annotation-time grounding: The bot cross-references three sources while classifying your content

The system doesn’t annotate in a vacuum. When the bot classifies your content at Gate 5, it cross-references against at least three sources simultaneously. This is my model of the mechanism. The observable effect — that annotation confidence correlates with entity presence across multiple systems — is confirmed from our tracking data.

The bot carries prioritized access to the web index during crawling, checking your content against what it already knows: 

• Who links to you.
• What context those links provide.
• How your claims relate to claims on other pages. 

Against the knowledge graph, it checks annotated entities during classification — an entity already in the graph with high confidence means annotation inherits that confidence, while absence starts from a much lower baseline. 

The SLM’s own parametric knowledge provides the third cross-reference: each SLM compares encountered claims against its training data, granting higher confidence to claims that align, flagging contradictions, and giving lower confidence to novel claims until corroboration accumulates.

This means annotation quality isn’t just about how well your content is written. It’s about how well your entity is already represented across all three of the algorithmic trinity. An entity with strong knowledge graph presence, authoritative web index links, and consistent SLM-domain representation gets higher annotation confidence on new content automatically. 

The flywheel: better presence leads to better annotation, which leads to better recruitment, which strengthens presence, and which improves future annotation.

Once again, better to have an average presence in all three than to have a dominant presence in two and no presence in one.

And this is why knowledge graph optimization (what I’ve been advocating for over a decade) isn’t separate from content optimization. They are the same pipeline. Your knowledge graph presence directly improves how accurately, verbosely, and confidently the system annotates every new piece of content you publish.

If you’re thinking “Knowledge graph? That’s just Google,” think again.

In November 2025, Andrea Volpini intercepted ChatGPT’s internal data streams and found an operational entity layer running beneath every conversation: structured entity resolution connected to what amounts to a product graph mirroring Google Shopping feeds. 

OpenAI is building its own knowledge graph inside the LLM. My bet is that they will externalize it for several reasons: a knowledge graph in an LLM doesn’t scale, an LLM will self-confirm, so the value is limited, a standalone knowledge graph can be easily updated in real time without retraining the model, and it’s only useful at scale when it stays current.

The algorithmic trinity isn’t a Google phenomenon. It’s the architectural pattern every AI assistive engine and agent converges on, because you can’t generate reliable recommendations without a concept graph, structured entity data, and up-to-date search results to ground them.

Why Google and Bing annotate differently from engines that rent their index

Google and Bing own their crawling infrastructure, indexes, and knowledge graphs. They can afford grace periods, schedule rechecks, and maintain temporal state for URLs and entities over months.

OpenAI, Perplexity, and every engine that rents index access from Google or Bing operate on a fundamentally different model. They have two speeds: 

• A slow Boolean gate (Does this content exist in the index I have access to?)
• A fast display layer (What does the content say right now when I fetch it for grounding?)

The Boolean gate inherits Google’s and Bing’s annotations. Whether your content appears at all depends on whether it was recruited from the index those engines draw from, and that recruitment depends on annotation and selection decisions made by the algorithmic trinity. But what these engines show when they cite you is fetched in real time.

The practical implication

For Google and Bing, you’re optimizing for annotation quality with the benefit of grace periods and gradual reclassification. For engines that don’t own their index, the Boolean presence is inherited from the rented index and is slow to change, but the surface-level display changes every time they re-fetch.

That means what you are seeing in the results is not a direct measure of your annotation quality. It’s a snapshot of your page at the moment of fetch, and those two things may have nothing to do with each other.

How to optimize for annotation quality: The six practical principles

The SEO industry has spent two decades optimizing for search and assistive results — what happens after the system has already decided what your content means. We should be optimizing for annotation. 

If the annotation is wrong, everything downstream suffers. When the annotation is accurate, verbose, and confident, your content has a significant advantage in recruitment, grounding, display, and, ultimately, won.

1. Trigger SLM routing

Make your topic category obvious within the first 100 words. Use standard industry terminology. Follow structural conventions. Reference well-known entities. The goal: specialist model, not generalist.

2. Write for all three SLMs

Clear signals for subject (what is this about?), entity (who is the authority?), and concept (what established ideas does this connect to?). Ambiguity on any axis reduces confidence.

3. Get it right before publishing

First-impression persistence means the initial annotation is the hardest to change. Publish only when topic, entity signals, and claims are unambiguous.

4. Build the flywheel

Knowledge graph presence, web index centrality, LLM parameter strengthening, and correct SLM-domain representation all feed annotation confidence for new content. Invest in entity foundation, and every future piece benefits from inherited credibility.

5. Eliminate noise when correcting

Change every reference. Leave zero contradictory signals. Noise maintains inertia proportionally.

6. Audit for annotation, not just indexing

A page can be indexed and still misannotated. If the AI response is wrong about you, the problem is almost certainly at Gate 5, not Gate 8.

Annotation is the gate where most brands silently lose. The SEO industry doesn’t yet have a vocabulary for it. That needs to change, because the gap between brands that get annotation right and brands that don’t is the gap between consistent AI visibility and permanent algorithmic obscurity.

Why annotation matters so much and why it should be your main focus

You’ve done everything within your power to create the best possible content that maps to intent of your ideal customer profile, you have methodically optimized your digital footprint, your data feeds every entry mode simultaneously: pull, push discovery, push data, MCP, and ambient, so they are all drawing from the same clean, consistent source

So, content about your brand has passed through the DSCRI infrastructure phase, survived the rendering and conversion fidelity boundaries, and arrived in the index (Gate 4) intact. Phew!

Now it gets classified. Annotation is the last moment in the pipeline where you have the field to yourself. Every decision in DSCRI was absolute: you vs. the machine, with no competitor in the frame. 

Annotation is still absolute. The system classifies your content based on your signals alone, independently of what any competitor has done. Nobody else’s data changes how your entity is annotated.

But this is the last time you aren’t competing. From recruitment onward, everything is relative. The field opens, every brand that passed annotation enters the same competitive pool, and the advantage you carried through the absolute phase becomes your starting position in the competitive race you have to win.

That means: 

• Get annotation right, and you start ahead, with confidence that compounds through every downstream gate in RGDW. 
• Get it wrong, and the multiplicative destruction effect does its work — a near-zero on one annotation dimension cascades through recruitment, grounding, display, and won. No amount of excellent content, structural signals, or entry-mode advantage recovers it.

Warning: First-impression persistence (remember, the first time you are annotated is the baseline) means you don’t get a clean retry. Changing the baseline requires thoroughness, time, and more effort than getting it right on the first crawl.

Annotation isn’t the gate that most brands focus on. It’s the gate where most brands silently lose.

This is the eighth piece in my AI authority series. 

• The first, “Rand Fishkin proved AI recommendations are inconsistent – here’s why and how to fix it,” introduced cascading confidence. 
• The second, “AAO: Why assistive agent optimization is the next evolution of SEO,” named the discipline. 
• The third, “The AI engine pipeline: 10 gates that decide whether you win the recommendation,” mapped the full pipeline. 
• The fourth, “The five infrastructure gates behind crawl, render, and index,” walked through the infrastructure phase.
• The fifth, “5 competitive gates hidden inside ‘rank and display’,” covered the competitive phase.
• The sixth, “The entity home: The page that shapes how search, AI, and users see your brand,” mapped the raw material.
• The seventh, “The push layer returns: Why ‘publish and wait’ is half a strategy,” extended the entry model. 
• Up next: “The engine’s recruitment decision: What topical ownership actually means.”

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Many of today’s PPC tools were designed to be easily accessible to ecommerce. That doesn’t mean lead gen can’t take advantage of them, but it does mean more intentional application is required.

Lead gen with AI still requires a creative approach, and many conventional ecommerce tools still apply — but not always in the same way.

Here are the priorities that matter most for succeeding with lead gen using AI.

Disclosure: I’m a Microsoft employee. While this guidance is platform-agnostic, I’ll reference examples that lean into Microsoft Advertising tooling. The principles apply broadly across platforms.

1. Fix your conversion data first

This is the single most important thing you can do as AI becomes more embedded in media buying.

Between evolving attribution models, privacy changes, different platform connections, and shifts in how consumers engage with brands, it’s reasonable to ask whether your data is still telling an accurate story.

Start by auditing your CRM or lead management system. Make sure the data you pass back to advertising platforms is clean, consistent, and intentional.

In most cases, data issues stem from human choices rather than technical failures. Still, there are a few technical checks that matter:

• Confirm conversions are firing consistently.
• Regularly review conversion goal diagnostics.
• Validate that lead status updates and downstream signals are actually flowing back.

If AI systems are learning from your data, you want to be confident that the feedback loop reflects reality.

Dig deeper: How to make automation work for lead gen PPC

2. Make landing pages easy to ingest and easy to understand

Lead gen campaigns often have multiple conversion paths, which can be helpful for users. But from an AI perspective, ambiguity is a risk.

Your landing pages should make it clear:

• What action you want the user to take.
• What happens after action is taken.
• Which conversions matter most.

Redundant or unclear conversion paths can confuse both users and systems. If AI crawlers detect that anticipated outcomes are inconsistent, they may begin to question the accuracy of what your site claims to do. That can limit eligibility for certain placements.

Language clarity matters just as much. Avoid jargon, eccentric terminology, or internally focused phrasing when describing your services. Clear, plain language makes it easier for AI systems to understand who you are, what you offer, and how to match creative to the right audience.

A practical test: Put your website content into a Performance Max campaign builder and review how the system attempts to position your business. If you agree with the messaging, imagery, and framing, your site is likely easy to understand. If not, that feedback is valuable.

You can also paste your site content into AI assistants and ask them to describe your business and services. If the response aligns with reality, you’re in a good place. If it doesn’t, that’s a signal to refine your content.

Behavioral analytics tools, like Clarity, can help you understand exactly how humans are engaging with your site and how often AI tools are crawling your site.

Dig deeper: AI tools for PPC, AI search, and social campaigns: What’s worth using now

3. Budget across the entire funnel

Lead gen has always struggled with long conversion cycles. That challenge doesn’t go away, and in some ways, it becomes more pronounced.

AI-driven systems increasingly weigh sentiment, visibility, and contextual signals, not just last-click performance. If all of your budget and reporting focuses on immediate traffic, you may miss meaningful impact higher in the funnel.

That means:

• Budgeting intentionally across awareness, consideration, and conversion.
• Applying the right metrics at each stage.
• Looking beyond traffic as the primary success indicator.

In many lead gen models, citations, qualified leads, and eventual revenue tell a more accurate story than clicks alone.

Dig deeper: Lead gen PPC: How to optimize for conversions and drive results

---

4. Clean up your feeds and map data

You may not think you have a “feed” in your lead gen setup, but that absence can put you at a disadvantage.

Feeds help AI systems understand your business structure, services, and site architecture. Even if you don’t have hundreds of pages, a simple, well-maintained feed in an Excel document can provide valuable context when uploaded to ad platforms.

Feed hygiene matters. Use clear, specific columns. Follow platform standards for text, images, and categorization. Make sure all relevant categories are represented.

On the local side, claim and maintain all map profiles. Ensure information is accurate and consistent. If you use call tracking in map placements, review your labeling carefully. AI systems may pull data from map listings or your website, and mismatches can create attribution confusion, particularly for phone leads.

Account for potential AI-driven inflation in reporting, whether you’re looking at map pack data, direct reporting, or site-level performance. Any changes you make should also be reflected correctly in your conversion goals.

5. Pressure-test your creative for clarity

Creative assets may be mixed, matched, or shortened using AI. In some cases, you may only get one headline to explain who you are and why someone should contact you.

If your value proposition requires three headlines, or a headline plus a description, to make sense, that’s a risk.

Review your existing creative and identify assets that stand on their own. You should have at least some options where a single headline clearly communicates:

• What you do
• Who you help
• Why it matters

If that clarity isn’t there, AI-driven placements can quickly become confusing.

Dig deeper: Why creative, not bidding, is limiting PPC performance

The fundamentals that still move the needle

Lead gen today doesn’t need to be complicated.

Most of the actions that matter today are things strong advertisers already do: clean data, clear messaging, intentional budgeting, and disciplined execution. What changes is how attribution may shift, and how much weight systems place on different signals.

The fundamentals still win. The difference is that AI makes weaknesses more visible and strengths more scalable.

If you focus on clarity, accuracy, and alignment across your funnel, you give both people and systems the best possible chance to understand your business — and that’s where sustainable performance comes from.

We got our hands on the new ASUS Zenbook A16 for in-depth testing, and it's clear that the new Windows laptop is gunning for Apple's lightweight MacBook Air 15. Here's how the two devices compare in terms of design, features, displays, performance, efficiency, and pricing.

A combination of Qualcomm's phenomenal generational performance gains and refinements to ASUS' already stellar Zenbook design has crafted a practically perfect Windows laptop.

Major suppliers are continuing to phase out production of mature products below DDR4, according to TrendForce's latest research on the memory industry. As supply tightens structurally, DRAM prices have already posted significant cumulative increases in recent months.

TrendForce forecasts that consumer DRAM contract prices will continue to rise by 45-50% QoQ in 2Q26 after taking into account ongoing supply reductions, order transfers, and the slower pace of capacity expansion among Taiwanese suppliers.

StarTech.com, a global provider of performance connectivity solutions for IT professionals, announced the release of its next-generation Driverless Multi-monitor USB-C Docking Stations for Windows environments utilizing multi-stream transport (MST) with HDMI and DisplayPort compatible models. Built for enterprise Windows environments, the docks support enterprise mixed hardware platforms including Intel, AMD and Snapdragon-based systems while enabling driverless deployment and up to 100 W of power delivery.

Key features include:

• Dual 4K 60 Hz display support or Dual 4K 60 Hz + one 4K 30 Hz with the triple display dock.
• Driverless deployment for faster rollout and less troubleshooting.
• USB ports up to 10 Gbps.
• Mountable design with integrated security lock slots.

Introducing GHS Eternal and GHS Eternal RGB, wired gaming headsets that prove great gear doesn't have to cost a fortune. GHS Eternal and GHS Eternal RGB are the first entry into the new Gaming Headset line, and round out the Glorious product portfolio, covering keyboards, mice, accessories, and now gaming audio.

GHS Eternal and GHS Eternal RGB add to the Glorious Eternal product lineup alongside Model O Eternal, to bring high-quality and affordable gear to gamers around the world. The Eternal lineup exists because great gear shouldn't cost a fortune, and GHS Eternal and GHS Eternal RGB extend that ethos into the world of gaming audio.

ASUS today announced the U.S. availability of its latest Zenbook lineup, headlined by the all-new Zenbook A16. Setting a new standard for groundbreaking performance, the Zenbook A16 debuts as the fastest Snapdragon -powered laptop on the market, equipped with the top-of-the-line Snapdragon X2 Elite Extreme processor for unprecedented local AI capabilities. The new Zenbook series—which also features the Zenbook A14, Zenbook S16, and Zenbook S14—is unified by Ceraluminum, an ASUS-exclusive material that combines the refined touch of ceramic and strength of aluminium to offer a unique tactile experience and lasting durability. As fully certified Copilot+ PCs, these devices are built to harness the full potential of local AI, furthering ASUS's commitment to deliver future-ready computing today and beyond.

ASUS Zenbook A16
ASUS Zenbook A16 (UX3607)—featuring the latest Snapdragon X2 Elite Extreme processor, which combines 18 cores and up to 80 TOPS NPU performance to unlock the next era of AI-enhanced computing—bridges the gap between ultra-portability and uncompromised performance. With a remarkable leap in CPU and GPU performance, while also optimized for superior battery efficiency, Zenbook A16 delivers fluid, lag-free performance across every scenario including media editing and rendering as well as productivity tasks. The laptop also features a vibrant 16-inch 3K 120 Hz ASUS Lumina OLED display, six super-liner speakers, and a comprehensive array of full-size I/O ports. Despite its expansive display, the laptop's sleek, all-Ceraluminum 2.65lbs.

Every year, the moto g stylus stands apart as the only smartphone in its price tier to offer a true stylus experience, giving users a precise, intuitive way to capture ideas the moment inspiration strikes. This year, Motorola builds on that foundation with the new moto g stylus - 2026, now featuring a built-in active stylus, and marks an important expansion of its portfolio with the moto pad - 2026. Together, these devices are designed to support creativity, productivity, and play across screens.

moto g stylus - 2026: Active pen within reach
From focused study sessions to well-earned downtime, today's devices need to move as fast as inspiration does. The integrated active stylus on the moto g stylus - 2026 delivers next-level precision for note-taking, gaming, and creative expression. The new active stylus responds to tilt and pressure in supported apps, enabling broader shading, finer lines, and more natural strokes, bringing a pen‑on‑paper feel to everyday tasks.

Corsair is proud to unveil the newest additions to the modular FRAME Series Case family; the FRAME 4000X RS and the FRAME 4000D WOOD RS. The FRAME 4000X features an all-new ventilated front panel with built-in RGB lighting and 64 RGB LEDs for a customizable light show, while the FRAME 4000D WOOD sports a front panel made with real wood for great airflow and a natural look. Both cases deliver new aesthetic options to the FRAME 4000 Series lineup while offering excellent cooling performance and easy upgradeability.

The all-new FRAME 4000X RS was created for DIY PC builders who want a great looking PC with RGB lighting and excellent airflow. It includes the new RGB Flow front panel that features 64 built-in RGB LEDs for a customizable light show with effective airflow. The RGB lights on the front panel can be connected to the motherboard's +5V RGB header for easy lighting management via motherboard software.

ZOWIE, a leading global esports brand and part of BenQ Corporation, has been named by Riot Games as the official monitor for the VALORANT Champions Tour Americas (VCTA). This collaboration is grounded in a shared commitment to competitive performance and player-first standards. Trusted by professional FPS players worldwide, ZOWIE monitors are engineered for precision, responsiveness, and consistency under tournament conditions, delivering a performance benchmark that meets the demands of top-tier competition.

ZOWIE's best in class XL2566X+ Gaming Monitor will be used on stage during VCT Americas competitions, giving pro players elite performance when it matters most. The XL2566X+ features a 400 Hz Fast TN Panel with native FHD and DyAc 2 technology to deliver industry-leading motion clarity, and clear, sharp visuals with enhanced color modes. Designed specifically for FPS games, ZOWIE monitors provide stable, predictable performance, empowering players to Strive for Perfection.

H.264 has so far carried a flat annual cap of $100,000 for large subscription platforms. That may sound like a lot, but for these companies, the numbers are so small that most of them probably forgot it even existed on their balance sheet. Well, that comfortable arrangement just got a...

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The company is already adjusting pricing for high-capacity SSDs and memory-heavy configurations as supply costs increase.

The Asus Zenbook A16 is a lightweight housing for Qualcomm's Snapdragon X2 Elite Extreme, but comes with compromises in build quality and battery life.

A city councilor's home has been shot up for allegedly supporting a data center project in Indianapolis. Opposing neighborhood groups condemn the shooting, while the authorities have yet to determine who's behind the crime.

ByWordy is an AI writing workspace for creating contracts, articles, and other documents in your own voice. The platform offers jurisdiction-aware legal documents generated from templates, with e-sign capabilities. You can draft, rewrite, and refine with an AI editor. Legal templates are free to use, and credits are offered upon signing in.

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CloverNut centralizes operations for music labels, publishers, workshops, and other creative businesses. Manage artists, products, and releases; build public homepages; and support eight languages with real-time API sync. Handle streaming links for Spotify and Apple Music, create press kits, and control team access with roles. Flexible plans scale from solo creators to enterprises.

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Vala is an AI financial intelligence app that turns transactions into clear insights and practical actions. It connects bank accounts, categorizes expenses, tracks subscriptions, and helps manage shared spending for a simple, complete view of your finances.

Vala also offers goal tracking, budget savings tools, and real-time alerts for bills or unusual spending. With visual insight cards and guided suggestions, it helps individuals, couples, and families understand patterns and make better decisions without manual tracking or complex budgeting.

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An active campaign has been observed targeting internet-exposed instances running ComfyUI, a popular stable diffusion platform, to enlist them into a cryptocurrency mining and proxy botnet. "A purpose-built Python scanner continuously sweeps major cloud IP ranges for vulnerable targets, automatically installing malicious nodes via ComfyUI-Manager if no exploitable node is already

Use this code to save $150 on 64GB of super-fast G.SKILL Flare X DDR5-6000 RAM — at under $750 that's a solid saving.

In a world exclusive, TechRadar can reveal one of this year's must-buy items from Star Wars Day 2026's merch range.

I couldn't be more disappointed by XO, Kitty season 3 and its ending — so take my advice and stream Netflix's best teen drama to date instead.

Polaroid's Hi-Print 3x3 portable printer-cum-frame breathes analog life into your smartphone pics, producing and giving a home to display square prints

Scrubs season 10's penultimate episode will be released later this week — here's when and where you can watch it.

A fan has discovered what appears to be the early model for the main character for Rockstar Games' canceled project, Agent, within the leaked source code for Grand Theft Auto 5.

The budget proposal would force CISA to operate with a significantly lower budget than previous years, citing the government's claims that the election misinformation programs were used to "target the President."

Merino Energy has simplified the heat pump dramatically in a quest to make them cheaper and easier to install.

On a recent episode of Equity, we talked to Arena Private Wealth to explore a growing trend: family offices bypassing VCs to gain direct exposure to AI startups, turning them from passive investors into active participants.

Adobe Acrobat Student Spaces is a free tool for students to use AI and create different kinds of study material from documents.

Waymo now operates commercial robotaxi services in 11 cities, with various methods to hail.

For most people, “Mad Men” means the TV show. But the phrase points to something more specific: Madison Avenue in the 1950s and ‘60s, when agencies grew brands through persuasion, positioning, and earned trust in a world of scarce media channels and powerful gatekeepers. If you wanted attention, you bought your way in, then made your product the obvious choice.

When the internet arrived and Google made the chaos navigable, an entire industry was built on getting brands found. Search and SEO became one of the most commercially valuable disciplines in marketing.

That model isn’t disappearing. But something new is taking shape on top of it — and most of the industry is still using the wrong language to describe what’s happening.

AI is exposing everything SEO has neglected. Brands that win recommendations from AI systems won’t do so by publishing more content. They’ll win through positioning, persuasion, and corroborated proof.

In other words, they’ll win the way Madison Avenue always did.

SEO was never really about content

One of the strangest things about the current industry conversation is how many people talk as if the job of SEO is to create content. It isn’t. Not for most businesses.

If you’re a publisher, content is the product. Traffic is the commercial engine. But for most brands, content never did what people thought.

Early on, people wrote content for customers, and it worked. Then it changed. Content became a keyword vehicle. “Get people to our site” replaced good marketing comms.

Traffic became a proxy for exposure. It worked because search rewarded retrieval: type a query, get a page, get a click. All you needed to sell that model was the belief that any traffic was good traffic. That traffic somehow led to revenue that your agency could keep delivering.

That model is now under serious pressure. 

Google and ChatGPT are increasingly taking the click. Every serious large language model is trying to satisfy informational intent before the user reaches the source. They aren’t trying to be better search engines. They’re trying to make search engines unnecessary — and that’s the entire point.

There’s too much information on the web. People don’t want to open 10 tabs and read five near-identical blog posts to find a basic answer. They want the answer. The AI systems exist precisely to give it to them.

So if informational retrieval gets absorbed into the interface, what remains? Marketing. That’s the part many SEOs are still not fully grappling with.

Dig deeper: The three AI research modes redefining search – and why brand wins

From place to preference

The cleanest way to understand this shift is through the “4 Ps” of marketing: product, price, place, and promotion.

Traditional SEO has been, almost entirely, a place discipline. It’s been about getting your products, services, or information onto the digital shelf when people go looking.

Keyword rankings are shelf position. Paid search is just a more expensive version of the same principle. In commercial search, you pay for premium placement in a digital aisle.

That still matters enormously.

Buyer-intent search remains valuable. Google hasn’t solved its commercial transition to a fully AI-led interface, and won’t overnight. Search is too important to Google’s revenue to disappear fast. But another layer is emerging above it, and this is the layer that most agencies aren’t yet equipped to compete on.

As AI systems become the first interaction point for more users, the game shifts from being present to being preferred.

Users don’t just search. They ask. They describe a problem. They want the best CRM for a mid-market SaaS company, the best estate agent in their area, the best sandwich shop near the office. And the system responds with recommendations.

If classic SEO was about rankings, the next phase is about recommendations. If classic SEO was about digital placement, the next phase is about shaping preference. And recommendation, in practice, is advertising.

Not a display banner. Not a 30-second TV spot. But advertising in the oldest and most commercially powerful sense: influencing the choice someone makes before they’ve even consciously made it.

An AI-generated recommendation is an invisible ad unit. It doesn’t bill by impression.

Why AI recommendations hit differently

When an LLM recommends a brand, it can’t know with certainty what will work best. So it infers. It weighs signals: past success, prominence, reviews, case studies, corroborating sources, and repeated associations between a brand and a specific type of problem.

Humans do something almost identical. 

Where performance is clearly bounded, we can identify a winner. We know who won the Oscar. We know which film topped the box office.

But when performance isn’t obvious in advance, we rely on proxies. We ask friends, read reviews, and scan for authority. We use familiarity, logic, and social proof to estimate what is likely to be right.

That’s exactly the territory AI recommendation is now entering — the consideration set problem. If I ask an LLM to find me a reliable accountant for a small business, I’m not asking it to retrieve a blog post. I’m asking it to build me a shortlist. 

Unlike traditional search, the recommendation layer is invisible to brands unless they test for it actively. You don’t see the prompt or the source chain. You don’t even know why one brand made the cut and another didn’t.

But the commercial effect is real, possibly stronger than anything traditional search produced. If you’re in the recommendation set, you’re in the running. If you’re absent, you’ve lost the sale before the conversation started.

Dig deeper: Rand Fishkin proved AI recommendations are inconsistent – here’s why and how to fix it

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Your website is now an argument for preference

The first practical consequence: your website can no longer function like a polite digital brochure. Despite being optimized for search, many commercial web pages simply:

• Introduce the company.
• Gesture vaguely at services.
• Bury differentiation under generic corporate language.
• Treat the page as an endpoint for a ranking rather than a persuasive asset.

Still, they’re weak where it matters most: actual selling.

In the Mad Men era of SEO, your landing pages and service pages need to function like sales pages, not in a cheesy direct-response way, but in the strategic sense that they must clearly answer four things:

• Who is this for?
• What problem does it solve?
• Why is it different?
• Why choose it over the alternatives?

This comes down to positioning, which is key to GEO. If seven brands do broadly the same thing, the model needs distinctions. It needs enough clarity to say: this brand is best for X kind of buyer with Y kind of problem because it does Z better than everyone else.

Your website copy must surface real performance attributes: the specific things you genuinely do better or more distinctively than competitors. Your pages must become machine-readable arguments for preference.

Copywriting is back

Actual commercial copywriting — not fluffy brand storytelling or word count for its own sake — identifies a target customer, sharpens the problem, articulates the value, and makes the offer easy to recommend.

Good copy isn’t optional.

Take a local sandwich shop. The old SEO conversation runs to “best sandwich near me,” local pack, and review acquisition. It’s useful, but limited. 

The GEO version starts with the shop’s actual performance attributes. 

• Is it the speed? 
• The handmade bread? 
• The office catering? 
• The locally sourced produce?

Those claims must be clear on the website first. Then they need corroboration everywhere else:

• Reviews that mention the sourdough specifically.
• A local food blogger’s write-up.
• Inclusion in “best lunch spots” roundups.

They’re specific, repeated, retrievable evidence of why this shop is the right recommendation for a particular type of customer.

Scale that logic to a B2B software company, and the principle holds. Pages that clearly explain who the product is for, which problems it solves, and why it outperforms rivals. Then build mentions, customer reviews, and gain trade-press coverage — the body of evidence to support recommending you to buyers — and let the AI find it.

That’s pretty much GEO in a nutshell.

Keywords don’t disappear, but they lose their throne

Keywords are a human workaround. Approximations of intent, built for a retrieval system that needed exact string matching. LLMs process fuller context, layered needs, and comparative requirements. They move from keyword matching toward problem understanding.

Keyword research still matters for classic search, paid search, and buyer-intent pages. But the center of gravity shifts.

Instead of asking only “what terms should we rank for?”, the better question is: what attributes make us the right recommendation for the buyer we actually want, and what evidence exists across the web to support that claim?

The future of SEO is starting to look like the old agency model, as the work is increasingly promotional. Once your website clearly expresses your positioning, the challenge becomes promoting that position across the wider web through credible, repeated, relevant signals.

• Digital PR. 
• Traditional PR. 
• Expert commentary. 
• Case studies. 
• Reviews. 
• Listicles.
• Awards. 
• Trade press.
• Brand mentions. 
• Conference speaking. 
• Events. 
• Creator coverage. 
• Product comparisons. 
• Original data studies that other people actually cite. 

These are the things you go after, create, and encourage. Sadly, many “AI visibility” conversations flatten this into nonsense.

The goal isn’t merely to have content cited by AI. It’s to gather enough market evidence that AI systems repeatedly encounter your brand in the right contexts, with the right associations.

The work stops being optimization and becomes maximization: building the largest possible volume of persuasive, corroborated, retrievable evidence that your brand is a sensible recommendation for a specific kind of buyer.

That’s a fundamentally different model from anything the SEO industry has been selling. It’s promotional and strategic brand marketing.

Dig deeper: How to design content that AI systems prefer and promote

Where SEO still fits

SEOs need to grow up. There’s still significant value in buyer-intent search, technical site architecture, entity clarity, internal linking, and structured data. SEOs are well placed to monitor recommendation environments, test prompts, and identify where visibility is being won or lost.

But the identity crisis is real. Many agencies were built for a world of rankings, informational blogs, and monthly traffic graphs. They aren’t equipped to lead a world defined by positioning, copy, PR, brand evidence, and recommendation science.

Tracking brand citations inside AI outputs isn’t a complete strategy. It’s a temporary metric. 

The new agency model

Winning agencies look like hybrid commercial strategy firms: part SEO, part copywriting, part PR, part brand strategy, part technical infrastructure. They know how to protect buyer-intent search revenue today while building the fame, clarity, and corroborated authority that earns recommendation tomorrow.

This is the Mad Men model of SEO. Persuasion, positioning, and clear claims backed by public proof matter again. And the job is to become recommended by AI.

LG Electronics, the #1 OLED Gaming Monitor Brand in the USA, today announced pricing and availability for two new additions to its 2026 UltraGear Evo gaming monitor lineup: the LG UltraGear Evo GX9 (model: 39GX950B-B), the world's first 39-inch 5K2K curved OLED gaming monitor, and the LG UltraGear Evo GM9 (model: 27GM950B-B), a 27-inch 5K Hyper Mini LED gaming monitor. Both monitors bring next-generation display performance and AI-powered features to competitive and immersive gaming, giving players sharper visuals, faster response times, and smarter connectivity than previous generations. Both monitors are available for pre-order today at LG.com - The LG UltraGear GX9 at $1,799.99 and the LG UltraGear Evo GM9 for $1,199. Pre-orders placed through May 3 include the option to add LG Premium Care, extending the standard warranty by two years, for only $1.

LG UltraGear Evo GX9—World's First 39-Inch 5K2K Curved OLED
From the #1 OLED Gaming Monitor Brand in the USA the LG UltraGear Evo GX9 brings impeccable OLED picture performance to a size and scale not previously available, with near-instant 0.03 ms (GtG) response time and a 39-inch 5K2K canvas. As the world's first 39-inch 5K2K (5120×2160) curved OLED gaming monitor, its 21:9 ultrawide format with 1500R curve and 143 PPI pixel density, offering a wider, more panoramic view and crisp text clarity that pulls players deeper into the action.

Zyxel Networks, a leader in delivering secure and AI-powered cloud networking solutions, today announced the launch of the WBE665S BE22000 12-stream Wi-Fi 7 Triple-Radio NebulaFlex Pro ruggedized access point. The new solution presents MSPs and installers with an opportunity to address the rising demand for fast, reliable wireless connectivity within industrialized and challenging environments. Combining a durable IP67-rated weatherproof design and AI-powered cloud management, the WBE665S is designed for professional installers deploying networks in demanding locations.

In warehousing and distribution, manufacturing, cold storage, large-scale retail and other sectors, Wi-Fi is now being extended into zones that were once considered too harsh for wireless connectivity. Forklift trucks run connected tablets, while IoT sensors track the movement of consignments and goods, and handheld barcode scanners are used to drive greater efficiency and accuracy. In these environments, hazards such as extreme temperatures, humidity and dust are common and dropped connections, downtime and hardware failures can disrupt operations.

Indianapolis City-County Council member Ron Gibson, a Democrat who has held his position since 2023, recently expressed support for rezoning related to a proposed $500 million data center project. Two large buildings, from Los Angeles-based startup Metrobloks, will be built on a 14-acre site located in the Martindale-Brightwood neighborhood of...

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TSNC is being positioned as a practical path for developers who already ship BC-compressed assets and want to squeeze more data into the same storage, bandwidth, or VRAM budgets without rethinking their pipelines.

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Save $200 on this awesome AMD build from iBuyPower, featuring an AMD Ryzen 7 7800X3D, RTX 5070, 32GB of DDR5 RAM, and a 2TB SSD, all for just $2,049 right now.

In the rapid evolution of the 2026 threat landscape, a frustrating paradox has emerged for CISOs and security leaders: Identity programs are maturing, yet the risk is actually increasing. According to new research from the Ponemon Institute, hundreds of applications within the typical enterprise remain disconnected from centralized identity systems. These "dark

When talking about credential security, the focus usually lands on breach prevention. This makes sense when IBM’s 2025 Cost of a Data Breach Report puts the average cost of a breach at $4.4 million. Avoiding even one major incident is enough to justify most security investments, but that headline figure obscures the more persistent problems caused by recurring credential

USPS will retain around 80% of its Amazon parcels, however the ecommerce giant wants to use its own growing network.

Stranger Things' Gaten Matarazzo makes Pizza Movie well worth your time, as he steals the show here.

Mint Mobile's new 'Unf*! your bills' deal gets you home internet and an unlimited 5G phone plan for just $45/mo - pretty incredible value.

Avoid atrophy and build strength for life with these 3 PT-approved exercises.

Are you a pop head or a weird science enthusiast? Spotify now lets you create playlists of podcast episodes on your favorite topics.

Amazing photos and videos continue to come back from the Orion spacecraft as it rounds the Moon and heads home.

Turns out that the PS5 price hike hasn't filtered through yet as loads of retailers are still selling hardware at the 'old' prices.

Samsung Messages is shutting down, and Galaxy owners aren't happy with the proposed alternative.

Sony has delisted even more alleged shovelwarePS4andPS5games from its storefronts.

A Microsoft exec is promising work on the design front to 'help Windows 11 feel more polished and coherent'.

Infimobile discounts all their plans with the 5GB package costing just $49 per year

The Bigme Hibreak Dual is a phone and ereader all in one, with two screens and no folds.

The defense aviation startup is coming off two successful flight demonstrations, and with the next one, it's aiming to go supersonic.

Spotify will now allow users to input natural language prompts to create a podcast playlist.

Google explains why it doesn't matter if websites are getting heavier and the takeaway has everything to do with SEO.

The post Google Explains Why It Doesn’t Matter That Websites Are Getting Larger appeared first on Search Engine Journal.

I’m getting a mid-career executive MBA. Last week, in class, we discussed the interaction between automation and advertising. The lecture covered why A/B testing in Meta is less valuable now, since Facebook can auto-optimize faster and better than marketers can on their own.

A classmate took the logical leap and asked the professor, “If digital channels have more data and more processing power, why don’t advertisers just give them a URL and a credit card and let them go wild?”

The argument has real merit. Google, Meta, and LinkedIn have access to more data than any agency ever will. Their optimization engines are improving fast. Handing them a budget and a URL and walking away isn’t entirely crazy.

But that means we’d need to have faith in the channels to optimize media in a business’s best interests, and there’s a long, proud history of that not being the case.

1. The opt-in that wasn’t

About six years ago, we met with a Google rep who pitched a product that introduced broader, more aggressive targeting and bidding. We listened to the pitch and said no. We didn’t want to try it. The reps turned it on anyway.

What happened next was what we predicted. The campaigns spent significantly more money and didn’t generate any additional conversions.

We had to comp the client for the wasted spend, which was bad enough. But what made it worse was the principle of the thing: we hadn’t agreed to this. Google made unauthorized changes to our account.

When I tried to get the money back, Google’s position was that we’d set our campaign budgets at a certain level, and they were within their rights to spend up to that amount. That framing ignores that a budget cap is a ceiling, not an invitation. 

Our agency methodology is to never hit a budget cap. We set those numbers based on the strategy we’d approved, not the one they decided to test. I hounded them for weeks, but never got any resolution. It still makes me angry.

The reps were clearly incentivized to get adoption of the new feature. When it didn’t work, there was no accountability and no recourse. We were left covering the cost of a decision we explicitly declined.

What’s being misrepresented

Budget caps were treated as implicit consent to spend. A product we declined was activated without authorization, and when it failed, the platform pointed to our own settings as justification.

The incentive structure rewarded the reps for turning it on. There was no corresponding mechanism to make the advertiser whole when it didn’t work.

Dig deeper: Google rep’s unauthorized ad changes spark advertiser concerns

2. The profit maximization pitch

This was years ago for a successful retainer. A pair of senior Google reps sat across from us and asked what our client’s gross margin was. Around 50%, we said. They went to the whiteboard and wrote out: if overall revenue/2 – overall media cost >= 0, then we should keep spending money on ads.

On the surface, the math sounds right. In practice, it has two problems.

• It assumes the reported conversions are incremental, meaning they wouldn’t have happened without the paid ad. A substantial portion of any Google campaign’s reported conversions, particularly in brand and retargeting, are users who were already going to convert.
• The model assumes a flat cost curve, where the 500th conversion costs the same as the 50th. It does not. Marginal returns fall as you scale. The last dollars of spend are always the least efficient, but they’re exactly what this pitch is designed to help Google access. (They should have said marginal revenue/2 – marginal cost = 0 is profit maximization.)

What’s being misrepresented

The model treats all reported conversions as incremental and assumes cost per conversion is constant across spend levels. Both assumptions are wrong, and together they can justify significant overspend.

3. The ‘higher CPCs buy better clicks’ pitch

This one still happens all the time. The pitch is that if you raise your CPCs, you’ll get access to higher-quality traffic. The implied logic is that conversion rate is influenced by CPC, and that if your investment isn’t high enough, you’re missing the best clicks.

There’s a version of this that has some truth to it. Higher CPCs can mean higher ad positions, which can mean higher impression frequency against the same users. More frequency can drive higher aggregate conversion rates, because repeated exposure matters.

But the argument glosses over the other side of that equation. 

• Higher frequency has diminishing marginal returns. 
• The third impression is worth less than the first. The tenth is worth a lot less.
• The cost curve isn’t flat. You’re paying more per click at every step.

In practice, raising CPCs to chase quality traffic is almost always correlated with substantially worse overall return on ad spend.

This is a variant of the marginal return problem seen across these cases. The pitch frames the upside without acknowledging the cost curve. More spend gets positioned as access to better outcomes, when it often delivers the same outcomes at a higher price.

What’s being misrepresented

CPC and conversion rate are presented as if higher bids unlock better traffic. In most cases, the incremental cost outpaces the incremental return. The pitch frames diminishing returns as an opportunity, rather than a constraint.

Dig deeper: Dealing with Google Ads frustrations: Poor support, suspensions, rising costs

4. The learning phase as a get-out-of-jail card

“If your Meta campaigns are underperforming, it’s because the algorithm just needs more time to learn.”

“Don’t make changes, and don’t reduce budget, just give the platform more data.” 

This is sometimes true. Machine learning systems need volume to optimize effectively, and premature intervention can reset progress.

But “it needs to learn” has become a catch-all explanation that’s almost impossible to disprove in the short run. It explains away poor CPAs, delays accountability, and keeps spend flowing when a reasonable advertiser might otherwise pull back and reassess.

There’s rarely a clear definition of when the learning phase ends, which makes it a moving target. The learning phase ends when performance improves. If performance doesn’t improve, more learning is prescribed.

What’s being misrepresented

A real technical concept is being used in ways that resist falsification. When there’s no defined endpoint and no stated criteria for success, “it needs to learn” serves as a blank check for budgetary continuity.

5. The metric pivot: When conversions fail, sell sentiment

In many cases, YouTube or display campaigns aren’t driving measurable conversions. The rep’s suggestion: let’s look at brand measurement. We can measure recall rates, positive sentiment, and intent to purchase. These are real signals of brand health, and they matter in the long run.

But the shift from conversion to sentiment metrics tends to occur when conversion metrics are poor, not as a principled measurement strategy. Brand lift surveys measure awareness under controlled conditions, but they rely on self-reported intent and don’t connect to downstream revenue.

Recall is almost never translated into a cost per point of lift that can be compared across the media plan. You end up with a number that’s positive and presented as evidence of success, with no agreed-upon framework for what sufficient lift would look like.

What’s being misrepresented

A softer metric is substituted for a harder one after the harder one fails. Brand lift is a legitimate measurement tool when defined upfront as a success criterion. Introduced afterward, it functions as a consolation prize.

Dig deeper: PPC mistakes that humble even experienced marketers

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6. Upper funnel combined with lower funnel for a blended average

Upper-funnel and lower-funnel campaigns serve different purposes and perform differently on a cost-per-acquisition basis. When a channel reports blended CPA across all campaign types, an average that looks acceptable can hide the fact that some portion of the media plan is wildly inefficient at the margin.

The argument for blending is that upper-funnel spend creates the conditions for lower-funnel performance. That is plausible, but plausibility isn’t the same as demonstrated causality. 

Often, it’s assumed the upper funnel is directly contributing and that, in aggregate, the system is profitable and fully incremental. This is never the case.

What’s being misrepresented

Aggregate CPA can look fine while specific segments of spend have no measurable return. Blending is a reporting choice, and it can obscure where money is and isn’t working.

7. View-through conversions: The numbers that shouldn’t count

A view-through conversion is counted when a user sees an ad, doesn’t click it, and then converts within some attribution window, often 24 hours or more. Platforms report these alongside click-through conversions by default. 

For retargeting campaigns, which by definition serve ads to people who have already visited your site, view-through attribution is particularly problematic. These users were likely going to return and convert regardless. The ad may have had nothing to do with it.

The issue isn’t that view-throughs aren’t meaningful. For a cold audience, some brand-influenced conversions happen without clicks.

The issue is that those conversions are almost never broken out proactively (you have to ask). And when you remove view-throughs from retargeting campaigns, the ROAS numbers can change dramatically. 

We’ve seen cases where removing VTAs cuts reported conversions by more than half. I would note that by moving to incremental measurement options, Meta has become substantially more transparent.

What’s being misrepresented

View-through conversions inflate reported performance, particularly in retargeting, where incrementality is already low. Default reporting includes them without flagging the methodological problem.

Dig deeper: Outsmarting Google Ads: Insider strategies to navigate changes like a pro

8. The competitor benchmark as a spending lever

This one is a pattern. A channel rep brings industry benchmark data to a meeting showing that your competitors are spending at a level above your current budget. The implication is clear: you’re being outspent, and you should close the gap.

Industry benchmarks are among the most valuable inputs a channel can provide. Knowing where you sit relative to the market is useful context for planning. The problem is how they get deployed. More often than not, benchmark data shows up as a tool to expand media spend, not as a neutral input into strategy.

And it works. CEOs and CMOs are particularly susceptible to this framing. Nobody wants to hear that a competitor is outspending them.

The emotional pull of “they’re investing more than you” is hard to counter with a measured conversation about marginal returns or strategic fit. The benchmark becomes the argument, and the argument is almost always “spend more.”

What gets lost is any discussion of whether:

• The competitor’s spend is actually working for them.
• Your business model and margins support the same level of investment.
• The benchmark even reflects an apples-to-apples comparison.

Competitive spend data without context is just a number that makes your budget feel inadequate.

What’s being misrepresented

Benchmark data is real, but it’s selectively introduced to justify budget increases rather than treated as one input among many. The framing skips over whether the comparison is meaningful and relies on competitive anxiety to sell.

9. The default settings trap

This one is hard to frame as a single incident because it’s everywhere. I’ve talked to so many people trying to break into the industry, or launch their first campaigns, and the story is almost always the same. 

They follow the platform’s setup guide, accept the default settings, and end up opted into programs that have close to zero chance of being successful.

This is true across pretty much every major channel. 

• LinkedIn defaults you into audience network inventory that runs outside the LinkedIn feed. 
• Google opts you into display inventory when you’re trying to run search. Broad match keywords are set way too far out of the box. Suggested CPCs are astronomical. 
• Google’s geographic targeting defaults to “presence or interest” rather than actual location. 

Each of these defaults, taken individually, could be defended as a reasonable starting point. Taken together, they create a setup that maximizes the platform’s revenue from day one, before the advertiser knows what’s happening.

A new advertiser following the guided setup is accepting a configuration that the platform designed, and the platform’s incentives aren’t aligned with efficient spend.

This one is genuinely difficult to solve. Platforms need to provide default settings, and they can’t expect every new advertiser to understand every option. 

But there’s something predatory about the gap between what people think they’re signing up for and what they’re getting. The defaults are revenue-optimized for the channel, not performance-optimized for the advertiser.

What’s being misrepresented

Setup guides and default settings are presented as best practices when they’re actually configurations that favor the platform’s revenue. New advertisers trust the guided experience, and have no reason to suspect the defaults are working against them.

Dig deeper: Are you being manipulated by Google Ads?

10. The tracking gap as a faith exercise

Privacy regulations and platform changes have created real limitations in conversion tracking. GDPR and Apple’s App Tracking Transparency aren’t invented problems. 

We have less visibility than we used to, and the platforms have responded by layering probabilistic modeling and modeled conversions on top of deterministic tracking.

But the tracking gap has also become a convenient shelter for underperformance. The argument goes like this:

• “The conversions are happening, we just can’t see them all yet. There’s latency in the data.”
• “There are limits to what can be tracked. We need a longer attribution window.”
• “We need more time for the modeled data to populate. And in the meantime, here are some proxy metrics that we think are directionally valid, so let’s keep pushing.”

Each of those can be true in isolation. Modeled conversions take time to appear. Attribution is harder than it was five years ago. Proxy metrics can be useful when direct measurement breaks down. 

The problem is when all of these caveats get stacked together and used to justify sustained spend in the absence of any measurable result. At some point, “the data will come in” stops being a reasonable expectation and becomes an article of faith.

The tracking gap is real, but it cuts both ways. If you can’t measure the result, you also can’t prove the spend is working. The platform’s default position is to assume it is, and keep going. The advertiser’s job is to ask what happens if the modeled conversions never materialize, and what the fallback plan looks like if they don’t.

What’s being misrepresented

Legitimate tracking limitations are used to defer accountability indefinitely. When measurement is hard, the platform’s recommendation is always to maintain or increase spend, never to reduce it. The uncertainty gets resolved in the channel’s favor by default.

What does this mean for AI-run campaigns?

None of this is an argument that agencies are irreplaceable in their current form. We used to question tCPA, and now it’s a preferred bidding strategy. Automation handles execution-level work that used to require skilled practitioners. In-house teams are viable for more companies than they used to be.

But the argument for fully autonomous, channel-run advertising assumes the channel will optimize for your outcomes rather than revenue. Even if we imagine new profit-sharing contracts, this assumption carries real risk.

And I’m not blaming reps or the channels. They believe in their products, but they’re also measured on metrics that create a predictable drift in how they frame data. I should note that agencies struggle with misaligned incentives as well.

The advertiser’s job, with or without an agency, is to keep asking the inconvenient questions.

• What is the marginal return at this spend level?
• What percentage of conversions are view-throughs?
• What does performance look like if we exclude brand search?
• Are we measuring incrementality, or are we measuring correlation, and calling it causation?

Maybe the answer to everything is eventually full automation. But the entity building the machine shouldn’t be the one telling you when it’s ready.

For years, Salesforce Marketing Cloud was the safe choice.

Powerful. Enterprise. Trusted.

But lately, we’re hearing something different:

• “Our data is too tangled to activate.”
• “We’re locked into contracts.”
• “We’re stuck sending the same emails on repeat.”
• “Everything is Band-Aids and duct tape — I don’t know how we can move without breaking everything.”
• “We feel stuck.”

Sound familiar? If so, this fireside chat is for you.

We’ve helped dozens of brands migrate off Salesforce and into modern, composable engagement architectures built for real CRM performance. Not because it’s trendy — but because marketers needed more speed, flexibility, and innovation.

In this April 14 session, we’ll cover:

• Why brands feel stuck (and why it’s more common than you think).
• What’s happening inside the Salesforce ecosystem.
• The biggest misconceptions about migrating.
• Understanding the martech landscape.
• What life actually looks like after moving to a modern platform like Braze.
• How CMOs and martech leaders should think about platform decisions over the next 3 to 5 years.
• How to get the rest of your org on board with making a move.
• The steps to take now to set yourself up for migration success.

To be clear: this isn’t a Salesforce-bashing session.

It’s a candid conversation about innovation velocity, marketing ownership, and what the next era of marketing actually requires.

Join us

Disclaimer: To ensure a candid and open conversation, the live session is open only to brand-side marketing leaders. Registrants who are not verified brand-side marketing leaders will not be permitted to attend the live session. However, the recorded session will be made available to all registrants upon completion of the event.

Intel’s first CPUs to integrate Nvidia graphics chiplets are reportedly called “Serpent Lake”, and they could launch in late 2028 Last year, Intel struck a deal with Nvidia that would allow them to “build and offer to the market x86 system-on-chips (SOCs) that integrate NVIDIA RTX GPU chiplets.” According to the leaker Jaykihn, Intel’s first […]

The post Intel “Serpent Lake” CPUs to integrate Nvidia graphics in 2028/2029 appeared first on OC3D.

Turtle Beach's VelocityOne Race KD3 Racing Wheel and Pedals is currently one of the company's best accessories for emulating real-life racing on Xbox and PCs, and it's now on sale for 44% off.

Microsoft is changing how OneDrive handles deleted files. Soon, cloud deletions won't hit your local Recycle Bin, forcing you to use the web for recovery.

An AI expert mapped more than 80 Copilot products, sparking debate over whether it’s branding brilliance or confusion.

Copilot's terms of use indicated that it's for entertainment purposes only. However, Microsoft has indicated that the phrasing is a legacy language from when Copilot originally launched as a search companion service in Bing.

Sonnet Technologies, a US-based long-time provider of connectivity solutions for Mac, Windows, and Linux systems, has released two new Thunderbolt 5 docking stations: the Echo 20 SecureDock and Echo 21 SuperDock. Both target professional users looking for high-speed I/O, with the key difference being built-in storage support on the higher-end model. The two docking stations are mostly identical in terms of connectivity. Both feature three Thunderbolt 5 ports, a host connection capable of up to 140 W of power, and two downstream ports for peripherals and daisy-chaining. There are also nine USB 3.2 Gen 2 ports split between Type-A and Type-C, a 10 Gigabit Ethernet port with backward compatibility, and dual display outputs via HDMI and DisplayPort. Depending on the host system, the docks can drive up to four displays, with support reaching 8K at 60 Hz on Windows systems.

The Echo 21 adds an internal M.2 NVMe slot taking drives up to 8 TB, with transfer speeds reaching 3,300 MB/s. This makes it suitable for local media storage or backup use cases without requiring external drives. Both models feature high-res audio I/O at up to 24-bit/192 kHz, plus full-size SD and microSD card readers. Compatibility covers Apple M-series Macs, older Intel Macs with Thunderbolt 3, and Windows or Chromebook machines with Thunderbolt 4, 5, or USB4. The Echo 20 SecureDock is available now at $449.99, with the Echo 21 SuperDock following in late May at $499.99.

Errol Segal has been a LA Dodgers season ticket holder for over 50 years, but that run has come to an end as the team transitions to all-digital for season tickets.

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Robert Hallock, Intel's vice president and general manager of client segment technical marketing, confirmed in an interview with Club386 that the Raptor Lake lineup remains "a big part" of Intel's client segment strategy and will stay in production alongside newer chips.

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Broadcom disclosed in a securities filing on Monday that it’ll supply Anthropic with roughly 3.5 gigawatts of Google TPU capacity starting in 2027.

The entire range of Apple's M5-powered 13-inch MacBook Air laptops receives the largest discounts to date. Save up to $150 off all models.

Intel is understood to be in active talks with Google and Amazon to provide advanced chip packaging services for their custom AI ASICs.

New academic research has identified multiple RowHammer attacks against high-performance graphics processing units (GPUs) that could be exploited to escalate privileges and, in some cases, even take full control of a host. The efforts have been codenamed GPUBreach, GDDRHammer, and GeForge. GPUBreach goes a step further than GPUHammer, demonstrating for the first time that

Investors are asking data center hyperscalers to release finer, site-specific details on water and energy consumption.

The new Soluppgång range starts at just $4

It looks like Mac mini and Mac Studio PCs have been hit by the 'RAMpocolypse', with delays of up to four months.

Most agentic AI pilots stall. Data quality, governance and integration determine whether they scale successfully.

What if AGI emerges not from one model, but millions of interacting AI agents?

Nintendo has confirmed that Tomodachi Life: Living the Dream won't support the Nintendo Switch 2's new resolution boost feature.

Europe’s AI ambitions risk stalling unless infrastructure evolves to share and scale GPU resources efficiently.

Microsoft promised to hone Windows 11's RAM usage — but confusingly the new Copilot app is a memory hog.

How highly organized, state-sponsored “espionage ecosystems” are disrupting global security and world economies.

Daredevil: Born Again season 2's new trailer has no problem dropping some big story-based spoilers.

We're a week away from what could be the most explosive finale on TV. But when is The Pitt season 2 episode 14 airing on HBO Max?

German police are looking for two Russians who allegedly ran GandCrab and REvil ransomware operations.

Issues in the iPhone Fold's development have apparently put the mass production timeline at risk, but we're still hopeful for a launch this year.

We’re sharing an update on our mental health work, including some new changes to better connect people with the right information.

STALKER 2 is getting some free content ahead of its Cost og Hope DLC this summer GSC Game World has confirmed that STALKER 2 is getting a free content update this month. This update is “Sealed Truth”, which will allow players inside the X-18 Lab. STALKER fans should already be aware of the Lab X-18, […]

The post STALKER 2 is getting a free content update this month called “Sealed Truth” appeared first on OC3D.

Based on the satirical novel and film franchise, Starship Troopers: Ultimate Bug War! puts the player in the shoes of Major Dietz as they fight back an army of alien arachnids. Or try things out from the bug’s perspective and destroy all humans. Either way, you’re in for a good time.

IBASE Technology Inc., a leading manufacturer of embedded and edge computing solutions, launches the MBB1002, a powerful AI-ready eATX motherboard engineered to accelerate next-generation edge AI and data-intensive applications. Powered by AMD EPYC Embedded 8004 series processors, it delivers exceptional multi-core performance and outstanding power efficiency, enabling faster AI inference, real-time analytics, and high-throughput computing at the edge.

Built for scalability and performance, the MBB1002 supports up to 576 GB DDR5-4800 ECC memory for reliable, high-speed data processing. Five PCIe Gen 5 x16 slots unlock unmatched flexibility for integrating GPUs and AI accelerators, empowering system integrators to scale performance based on evolving workload demands. With dual 10GbE LAN and high-speed NVMe storage support, the platform ensures ultra-fast data transfer and seamless system responsiveness for mission-critical deployments.

ASUS today announced the ProArt Router PRT-BE5000 and ProArt Switch PQG-U1080, introducing networking solutions into the ProArt family of Creator-First devices designed for modern studios. Joining the existing ProArt lineup of laptops, displays, graphics cards, motherboards, and other creator-focused products, these new devices help build a more complete studio infrastructure for creators. Combining dual-band Wi-Fi 7 connectivity, intelligent traffic prioritization, and high-speed multi-gigabit wired expansion, the ProArt Router PRT-BE5000 and ProArt Switch PQG-U1080 enable quick file transfers, cloud collaboration, and stable connections across multiple creative devices.

The ProArt Router PRT-BE5000 delivers dual-band Wi-Fi 7 with throughput performance of up to 5000 Mbps plus Multi-Link Operation (MLO), and dual 2.5G WAN/LAN connectivity for flexible, high-speed wired connections. Creator-First adaptive QoE intelligently prioritizes creative traffic in real time, helping to ensure fast file transfers, smooth cloud collaboration, and streaming across connected devices, in harmony with other network activity. ASUS Smart Home Master software further simplifies network segmentation through dedicated SSIDs for IoT devices and VPN connections, enabling more intuitive management across studio and personal environments.

Motherboards, who needs them? Not Breadboarding Labs, which recently drafted plans for a retro Intel 80386 (i386) PC build using solderless breadboards.

Giraffe Gold lets you build ownership of a physical gold, silver, or platinum bar through small monthly contributions and automatic round-ups. Connect your bank and spending card, set a contribution starting at $50, and watch your bar balance grow in real time with market prices.

When you hit the bar price, Giraffe Gold purchases from certified refiners and ships your bar fully insured to your door. The platform uses Plaid for secure, read-only connectivity and partners with Upstate Coin & Gold and ShipSecure to ensure authenticity and safe delivery.

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Stay the Week helps homeowners privately share lake houses, cabins, beach houses, ski condos, and second homes with friends and family. Invite guests to a private booking page to see availability, request dates, and receive automatic confirmations and reminders. Owners control availability, blackout dates, and access from a simple dashboard, with directions and property info attached to each booking, replacing messy text threads with a clean, controlled process.

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Learn how to transform generic website templates into uniquely branded sites, from colors and layouts to custom elements.

The UK's cybersecurity workforce has nearly tripled, but headcount growth is masking a deeper crisis - privacy teams remain critically understaffed, underfunded, and underpowered just as threats intensify.

Cybersecurity teams must be prepared for attacks and disruption that accompany geopolitical events.

A new survey shows AI is becoming a source of emotional and romantic connection for some people, even as many recognize it reflects deeper loneliness

Taylor Sheridan and David Mackenzie might have created one of the best modern Western movies of the 2000s, but don't expect a reunion any time soon.

Google's John Mueller says that those who self-identify as SEO gurus are clueless imposters.

The post Google’s Mueller On SEO Gurus Who Are “Clueless Imposters” appeared first on Search Engine Journal.

FORMLOVA is a chat-first form service powered by MCP. Create forms from ChatGPT, Claude, or Cursor in under a minute, then manage response routing, follow-up emails, reminders, analytics, and CRM handoffs from the same conversation. It integrates with 118 tools across 24 categories, focusing on the 95% of form work that happens after the form exists.

Most AI form tools stop at creation. FORMLOVA was built by a solo founder with years in digital marketing who knew the real burden was in post-publish operations. It's free to start with unlimited forms and responses.

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If you're running a website on Cloudflare's free or pro plan and don't have time to babysit logs or tune WAF rules, Detect7 fits. It gives you automated, intelligent protection that works in the background without needing you to be a security expert. You set it up once, and it handles the rest: detecting threats, escalating from challenge to block, learning traffic patterns, and managing Cloudflare firewall rules and IP lists for you. It analyzes 100% of your origin logs in real time, learns your normal patterns, and auto-blocks threats with adaptive rules pushed to your Cloudflare integration.

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Battery dying? WiFi gone? Your Mac finally talks back.

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Live schedules on the Lock Screen for event crews

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Dedicated space to bring your personal health data together

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Claude Code as a Tech Lead with parallel Worker Agents

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A full navigation utility in ~2MB

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Watch 10K+ live flights move on a 3D globe in your browser

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Privacy-first AI finance tracker

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Studio-grade AI lip sync and visual dubbing

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Search, Reach and Connect - Find the perfect fit, 10x faster

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data analysis workspace for Claude Code/Codex

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Create forms and manage submissions inside ChatGPT

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Press Tab for AI anywhere you type on Mac

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Letters made of letters

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The IDE for video engineers

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Get seen in search, AI and beyond

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Turn your Mac notch into a native 6-in-1 command center

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Know when your automations run, fail, or go quiet.

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Real-time subtitles, translation, and dictation for Mac

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Track body measurements, fat%, lean Mass, progress & more

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Grow your vocabulary while you browse the web

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AI-native data catalog with search, lineage and MCP

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A world for kids to explore along their favorite characters

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The AI co-author for research papers

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Select any screen area, get text instantly

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A faster, simpler alternative to bulky VM managers.

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A night-vision smart camera that knows when you are dreaming

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AI architectural renders and interior design

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Connect AI agents to browser through raw CDP

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AI ensemble that scored #1 on Humanity's Last Exam

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Record your microphone, system audio simultaneously

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Smart dictation, AI assistant, + app control via voice

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A cozy productivity app to focus with others + vibe to lofi

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Your online couch for movies, games, and good times

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The intelligence layer for ChatGPT Ads

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Automate what APIs can't in one prompt done locally

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Fix your terrible posture

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App store connect data + subscription insights

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Native planetary imaging capture for macOS and Apple Silicon

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Ask your Playwright tests why they failed

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Give your agent tools to create beautiful, codebase-aware UI

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Cinematic UI mockups in the browser

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Google's offline-first AI dictation, powered by Gemma

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Record, edit, and brand screen recordings Metal powered

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Never lose anything you copy again

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A mindful way to measure and understand your body activity

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A China-based threat actor known for deploying Medusa ransomware has been linked to the weaponization of a combination of zero-day and N-day vulnerabilities to orchestrate "high-velocity" attacks and break into susceptible internet-facing systems. "The threat actor's high operational tempo and proficiency in identifying exposed perimeter assets have proven successful, with recent

Spawnbase turns recurring work into reliable AI-powered workflows. Teams describe goals in plain language, then build agentic flows with triggers, AI steps, and app actions across seven providers and 200+ models. Configure nodes, test each run, and deploy on schedules or events while monitoring performance. Connect Slack, GitHub, HubSpot, Notion, Jira, and more, and pay only for executions with credit-based pricing.

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Threat actors are exploiting a maximum-severity security flaw in Flowise, an open-source artificial intelligence (AI) platform, according to new findings from VulnCheck. The vulnerability in question is CVE-2025-59528 (CVSS score: 10.0), a code injection vulnerability that could result in remote code execution. "The CustomMCP node allows users to input configuration settings for connecting

Rocket's new AI platform combines strategy, product building, and competitive intelligence, aiming to move beyond code generation.

Axe:ploit signs up with its own email and phone, discovers APIs, and probes for over 7,500 issues including IDOR, auth bypass, and complex business logic flaws. Backed by a constantly updated CVE feed, large password and fuzzing datasets, and layout-aware crawling, it adapts as your UI and logic change.

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Simmerce lets e-commerce teams run synthetic customer simulations to validate features before launch. It generates diverse shopper personas—budget shoppers, brand loyalists, impulse buyers, and researchers—and simulates how they search, browse, and convert to reveal friction and opportunities. Upload a product pages, search results, or recommendations and get insights in minutes, including which segments convert, where users get stuck, and what content is missing. Use pay-as-you-go credits to test ideas fast and ship with confidence.

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The program invites creators to create original content with Picsart tools for a specific campaign, share it on their social channels, and earn revenue based on how their audience engages.

Waymo’s driverless taxis are making their way to London starting with a pilot starting in April 2026.

Intel Desk connects geopolitical events to market instruments every 30 seconds. It aggregates over 60 OSINT and wire sources, scores sentiment, and maps topics to instruments to surface directional trade signals with evidence trails for energy traders, macro researchers, and defense analysts. Users get live market data via Finnhub, portfolio impact alerts, and twice-daily briefings, with transparent source chains and low-latency delivery you can trace end to end.

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TrackACert.io is a simple tool for IT managers who need to know what certifications their team holds, what's about to expire, and where the gaps are. We connect GIAC, CompTIA, ISC², AWS, Microsoft, and more in one place. Key features include IT certification tracking, certification expiry notices for your team, skill gap analysis to identify missing skills and certifications, and full reports to help justify financing for more certifications.

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Sam Altman argues that AI labs and governments must work together, while also hinting at the difficult tradeoffs shaping OpenAI’s next phase.

Looking for NYT Strands answers and hints? Here's all you need to know to solve today's game, including the spangram.

Looking for Quordle clues? We can help. Plus get the answers to Quordle today and past solutions.

Looking for NYT Connections answers and hints? Here's all you need to know to solve today's game, plus my commentary on the puzzles.

Following the Artemis II mission sparked a closer look at LEGO’s space-themed sets, including an interactive rocket build and a wider collection inspired by real space exploration.

Keyspace delivers AI-powered inventory management and warehouse automation for teams of any size. It connects to your existing tools, monitors stock in real time, and drives decisions on forecasting, replenishment, and operations.

Use collaborative workflows, advanced analytics, and a customizable interface to streamline processes, cut stockouts, and reduce carrying costs while scaling with confidence.

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Despite its merger with xAI and the upcoming SpaceX initial public offering in June, running the app is costing Elon Musk more money than it’s bringing in.

The new profile will be used to share Japan-specific information for users as Meta continues to challenge X for dominance in the microcontent sphere.

Adam Mosseri said that reposting feed posts to Stories won’t increase reach.

The company plans to eventually offer open source versions as its Superintelligence group works to catch up with industry benchmarks, per Axios.

The extended partnership gives users of both platforms more tools to manage ad campaigns and measure ROI.

Several delisted Xbox and Xbox 360 games have recently appeared on the Xbox Store, leading many to wonder if they'll be made backwards compatible soon.

As the previously leaked launch date of Sony's upcoming PlayStation 6 approaches, leaks and rumors abound, with many claiming that the upcoming gaming console will launch later than initially expected. Now, reputable leaker, KeplerL2, has taken to the NeoGAF forums to dispel some of the doom and gloom surrounding the launch date and potential delays of the PS6. The leaker's reasoning stems not from some insider information, but rather from a simple application of logic, asking a fellow commenter "What copium? You think AMD is gonna waste resources doing validation on something they think will get delayed?"

The reasoning seems to be that, based on information like prior leaks, that AMD has already been working on custom APUs for both the living room version and the handheld model of the PlayStation 6, and that AMD would not continue validation of those APUs if it thought there were supply constraints that would lead to a delay ahead of the console family's expected launch date. It's also possible that AMD and Sony signed the supply contracts for the Canis and Orion APUs before the current DRAM crisis was in full swing, effectively making a launch delay impossible or at least less likely. However, this would mean that the console makers would have a batch of hardware ready for launch followed by intermittent or delayed supply—at least as long as the DRAM shortage holds. There have also been rumors that Sony will be drastically increasing the price of the PS6 consoles compared to the PS5 generation, although this appears to be at least somewhat contingent on Microsoft's Xbox Helix pricing strategy.

Stormgate, a free-to-play, StarCraft-style RTS developed by Frost Giant Studios, relies on a third-party "game server orchestration partner" to run its online modes. Frost Giant told players on Discord that the provider had been acquired by an AI company, forcing a planned outage that will take Stormgate's multiplayer modes offline...

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More than a dozen investors are pressuring Amazon, Microsoft, and Alphabet's Google to provide detailed data on water and energy consumption at their U.S. data centers.

Google research indicates quantum computers may break cryptocurrency encryption sooner, prompting urgency for post quantum cryptography adoption and coordinated disclosure strategies

Hyperscale AI data centers produce significant local heat, affecting over 340 million people and creating immediate environmental challenges globally.