Latest 25 news items

Congrats to Harvey but we covered that already . AI News for 9/8/2026-9/9/2026.

Today was a tough news cycle to launch anything; we ordinarily promise to cover any new decacorn fundraises so Cognition’s $48B round and Mistral’s $24B round would normally have made it; we love imagegen so GPT Image 2.5 would have been its own headline; we covered the Dreamer story closely so their relaunch as Meta’s Muse agent should have made it; but..…

Benzi by Variant Technologies An AI coding agent that doesn't read — it queries . Benzi is free to use — actively in development, a work in progress.

AI development might not be the wild west it was when ChatGPT burst onto the scene a few years ago, but it's still very much a frontier, with no clear boundaries and few yardsticks . But for AI developers on the frontier, they're pulling hard towards dual goals of ever greater intelligence and ever cheaper per-token pricing, and it's leading to a real…

Our series about model distillation continues. We have a surprising mega interview.

The launch is barely 9 hours old, and with 36M views and 164K likes, already is OpenAI’s most successful launch since Sora and certainly GPT-4 or GPT-5 . You’ll recall we’ve previously observed that Anthropic tends to far outclass OpenAI in launch popularity.

With Astra clearly finally warming up for a full launch (with @sama and @openai writing about it again after a month of self imposed pacing ), there’s a familiar window to take the narrative with the round robin of model launches, with Grok 4.7 and Gemini Flash 3.8 also on the way. But that’s also perhaps not the best way to frame today’s launch… which got…

For the entirety of the history of Generative Media , you basically had to design around the inconvenient fact that generating images and video takes time — even if you used consistency models to get a 30 second generation down to 1 second, you still only have a 1 FPS video at best… well below anything acceptable for consumer-grade human attention. Fal…

More distillation coming to you. We break down GLM and Qwen new models.

Everyone’s waiting for Nvidia to confirm this week’s most interesting tech deal: A reported $13 billion acquisition of Hugging Face, a platform for sharing open-weight AI models and benchmarks. Now best known as the target for a team of reward-hacking OpenAI agents, Hugging Face is at the center of the ecosystem of developers building and deploying LLMs…

Cerebras' SRAM-packed wafer-scale engines (WSEs) have carved out a niche in the AI model serving space for extremely low-latency, high-throughput inference, enabling services like OpenAI's ChatGPT-5.6 Sol Ultrafast tier. At Hot Chips 2026 , the company revealed the next two generations of its wafer-scale accelerator roadmap.

Nvidia has agreed to acquire Hugging Face for $12.9 billion, according to The Information, citing a person familiar with the deal. If the report is accurate and Nvidia indeed buys Hugging Face, the purchase could strengthen Nvidia's open-model strategy, provide another route to sell AI hardware, and help defend its hardware business as Anthropic, Google ,…

TheInformation had the scoop , and now they have the confirmation — Nvidia is buying HuggingFace for $13B, roughly 80x their $150M ARR , having doubled its customer base in 2026 . This is almost double Nvidia’s initial $7B offer in Jan 2026.

AI progress is usually drawn as one upward-sloping line: more parameters, more compute, higher benchmark scores. Last week looked more like a three-dimensional coordinate system.

OpenAI says its new AI chip, Jalapeño, completes tasks more efficiently and returns responses faster than other AI systems, according to a blog post published on Tuesday . During a briefing with reporters, OpenAI hardware vice president Richard Ho said Jalapeño offers the “best of both worlds” with lower latency and higher throughput, as AI systems…

We’ve lost count of how many adoption milestones have been passed since the original Rise of the AI Engineer post, but surely Andrew Ng, cofounder of Google Brain and Coursera among many other things, relaunching DeepLearning.ai with a focus on AI Engineering is a big one : This was done via “ an analysis of over 10,000 job postings; carrying out dozens of…

Learn more about distillation techniques in our knowledge series. To keep you current we will dive into DeepSeek’s new release, the amazing EnvHarness paper released by Google and the AVO paper published by NVIDIA.

By AI standards today is a pretty quiet Friday, so it’s time to take a step back and reflect on what is really going on. If you read our 2025 reading list , and followed our coverage of Z.ai GLM , understood the Poolside pivot , been following our AI for Science themes , and tuned in to today’s Simile pod , you not only are one of the biggest readers of…

OpenAI: dissolve the structure The largest single body of evidence, so it goes first. Three safety teams gone in two years.

In the Wild The audience has already front-run the release calendar. See the latest full movement in In the Wild .

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In our previous post , we compared ALTK-Evolve with ACE and showed that how you deliver an agent's self-distilled guidelines — a few retrieved per task vs. the whole set injected — drives both accuracy and cost.

More on our distillation series. To keep you current, the frontier update section will provide mini deep dives about the new DeepSeek and GLM model as well as NVIDIA’s Lighting and Switchyard releases.