🧠 Nvidia to sell Meta millions of chips in multiyear deal ↗
Nvidia says it has signed a multiyear agreement to supply Meta with millions of AI chips - Blackwell now, Rubin later - plus Grace and Vera CPUs as part of the package.
The money figure wasn’t disclosed (as usual), but the sharper angle is Nvidia pitching those CPUs as more than “GPU sidekicks.” This reads like a clean bid for data center CPU territory, with a heavy emphasis on efficiency for everyday workloads like databases, not only the headline-grabbing AI training runs.
Meta is still doing its own silicon homework and keeping other options in sight, but this deal has the feel of: we need capacity, and we need it to be tangible.
🚨 Spain to investigate social media firms over AI-generated child sexual abuse material ↗
Spain says it will ask prosecutors to investigate X, Meta, and TikTok over allegations tied to AI-generated child sexual abuse material, including deepfakes and manipulated images.
The argument is basically that these platforms can enable rapid, opaque distribution that’s harder to detect and prosecute - which, grimly, is exactly what makes it so dangerous.
This also connects to broader plans to tighten child-safety rules online, with regulators and governments increasingly treating “AI content” as a multiplier for the worst kinds of abuse.
💸 Here are the 17 US-based AI companies that have raised $100M or more in 2026 ↗
TechCrunch counted 17 U.S.-based AI startups that have already pulled in $100M+ rounds - and yes, several of them land in the “wait - that’s the number” category.
What stands out is the spread: model labs, media-generation, decisioning tools, robotics-ish efforts, and the infrastructure glue that quietly attracts the biggest checks. It’s not one crowded lane - it’s a whole motorway, slightly fogged over, everyone accelerating.
It’s exhilarating, and it also locks in a lot of pressure to turn compute into revenue quickly, which doesn’t always end in calm, rational product decisions.
🌍 We need to act with urgency to address the growing AI divide ↗
Microsoft says AI adoption is accelerating but uneven, with usage in the Global North running about twice the Global South - and that gap is widening.
They’re also flagging a big investment push aimed at expanding AI access across the Global South, framing it as infrastructure plus skills plus practical deployment - not just “ship models and hope.”
It’s part moral argument, part strategy, and… both can be true at once, awkwardly, like a ladder made of two different metals.
🤝 Anthropic and Infosys collaborate to build AI agents for telecommunications and other regulated industries ↗
Anthropic and Infosys announced a collaboration to bring Claude (and Claude Code) into regulated enterprise workflows, starting with telecom and expanding into areas like financial services, manufacturing, and software delivery.
The whole pitch is “agentic AI” - systems that don’t just answer questions, but can carry out multi-step work like processing claims, running compliance-style reviews, or modernizing legacy systems with more governance baked in.
This is the point where the chatbot stops being a chatty mascot and starts touching real business plumbing - exciting, and a tiny bit “please don’t break production.”
🧩 Introducing Claude Sonnet 4.6 ↗
Anthropic rolled out Claude Sonnet 4.6 as an upgrade across coding, long-context reasoning, agent planning, and “computer use” - the click-and-type-on-a-screen kind, not just API tool calls.
Key bits: a 1M token context window in beta, plus Sonnet 4.6 becoming the default model in Claude for some plans, with pricing staying aligned with the prior Sonnet tier.
They’re also stressing stronger resistance to prompt injection, which is reassuring, because letting a model drive a browser without that is like giving the steering wheel to a raccoon with opinions.
🗓️ Get ready for Google I/O 2026 ↗
Google put out the official “I/O is happening” post and made it pretty clear AI is the headline act - Gemini, agentic coding, and product updates spread across the usual Google empire.
They’re teeing up keynotes and demos that sound very “AI-first,” which is not exactly shocking anymore, but still - it’s like every developer event got dipped in the same neon Gemini paint.
The key issue is how much of it lands as polished demos versus practical developer tooling, and in what mix.
FAQ
What does the Nvidia–Meta multiyear AI chip deal actually signal?
It signals that Meta wants dependable, concrete AI compute capacity over multiple years, beginning with Blackwell GPUs and later shifting to Rubin. Nvidia also bundled Grace and Vera CPUs, which hints it’s positioning itself as a broader data center platform provider, not simply “just GPUs.” Meta continues to explore its own silicon and other options, but this looks like a pragmatic step to lock in supply.
Why is Nvidia bundling Grace and Vera CPUs with its GPUs for Meta?
The bundle reads like Nvidia elevating its CPUs to first-class infrastructure for everyday data center work, not merely GPU “helpers.” The emphasis is on efficiency for common workloads like databases and general compute, alongside AI training and inference. In many deployments, tighter CPU + GPU integration can simplify architecture decisions and vendor relationships, which matters when you’re scaling quickly.
What is Spain investigating about AI-generated child sexual abuse material on social platforms?
Spain says it will ask prosecutors to investigate platforms including X, Meta, and TikTok over allegations linked to AI-generated child sexual abuse material, such as deepfakes and manipulated images. The core concern is that large platforms can enable rapid, opaque distribution that is harder to detect and prosecute. This ties into broader efforts to tighten online child-safety rules as AI content increases the scale and speed of abuse.
What does the 2026 surge in $100M+ funding rounds tell us in AI tech news?
It suggests investor appetite is spread across many lanes, not just “model labs.” The list includes areas like media generation, decisioning tools, robotics-adjacent efforts, and the infrastructure “glue” that quietly draws big checks. The upside is fast experimentation and scaling, but the pressure is tangible: companies that raise huge rounds often need to convert compute and market expectation into revenue sooner than ideal.
What is the “AI divide,” and what approach is Microsoft advocating?
The AI divide refers to uneven adoption, with Microsoft arguing that usage in the Global North is roughly double the Global South and the gap is widening. Their framing is that closing it takes more than shipping models: it’s infrastructure, skills, and practical deployment. That approach treats AI access like a systems problem - compute, connectivity, training, and local use cases - rather than a single product rollout.
How do Anthropic’s Claude Sonnet 4.6 and “agentic AI” change enterprise workflows?
Claude Sonnet 4.6 is positioned as stronger at coding, long-context reasoning, planning, and “computer use,” including a very large context window in beta and more emphasis on resisting prompt injection. In parallel, the Anthropic–Infosys collaboration targets regulated industries with agent-style systems that can execute multi-step work with more governance. In AI tech news terms, this is the shift from chatbots to tools that touch production systems - valuable, but demanding careful controls.