Good morning, AI enthusiast.

Nvidia is reportedly developing a new, more powerful Blackwell AI chip specifically for the Chinese market. The move is designed to comply with U.S. export regulations while protecting its significant market share from domestic competitors.

This development highlights the tightrope Nvidia must walk between American export controls and the demands of the massive Chinese market. Will this new chip receive approval, and what will it signal about the future of U.S. tech strategy with China?

In today’s AI recap:

• Nvidia's new Blackwell chip for China

• Meta's superintelligence shake-up

• OpenAI's new physical AI assistant

• A controversial AI career warning

• 8 trending AI Tools

Nvidia's New China Chip

The Recap: According to a new report, Nvidia is developing a more powerful Blackwell-based AI chip for China, aiming to navigate complex U.S. export rules and protect its crucial market share.

Unpacked:

• The new chip, tentatively known as the B30A, will feature a single-die design based on the latest Blackwell architecture, delivering a significant performance boost over the current H20 model.

• This development follows recent signals from the U.S. government, which now takes a 15% cut of revenue from certain chip sales to China.

• Nvidia is also trying to keep Chinese developers from switching to domestic competitors like Huawei, whose chips are rapidly improving.

Bottom line: This move highlights Nvidia's delicate balancing act between complying with U.S. national security interests and serving the massive Chinese market. The chip's potential approval will signal how the U.S. plans to manage tech competition with China going forward.

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Meta's Superintelligence Shake-Up

The Recap: Meta is restructuring its AI division into a new group called Meta Superintelligence Labs (MSL), splitting it into four dedicated teams to accelerate its high-stakes pursuit of AGI.

Unpacked:

• The new structure features high-profile leaders, with former Scale AI CEO Alexandr Wang leading the overall group and a new LLM-focused lab, and former GitHub CEO Nat Friedman heading a team to turn research into consumer products.

• MSL is now divided into four focused teams: a lab for core models like Llama, the long-standing FAIR research group, a product and applied research team, and an infrastructure unit to support it all.

• This reorganization follows months of Meta aggressively recruiting top AI talent and aims to stabilize its efforts while racing to keep pace with competitors like OpenAI and Google.

Bottom line: Meta is creating a more streamlined structure to turn its massive investments in talent and computing into tangible product advantages. This aggressive focus signals the company is all-in on not just competing, but leading the race to build superintelligent systems.

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OpenAI's Physical AI

The Recap: OpenAI has open-sourced Reflect, an experimental AI assistant born from an internal hackathon. This screen-free device uses light, sound, and color to help users stay focused and in their workflow.

Unpacked:

• Reflect aims to communicate naturally using ambient cues instead of a display, with the user's phone acting as the key to control its state and information.

• The assistant is designed to handle tasks like reviewing your calendar, helping you study, or playing music, all of which you can see it in action.

• As a hackathon project, it's built to be cheap and easily modifiable, with current support for hardware like the M5Stack CoreS3 microcontroller and LIFX smart lights.

Bottom line: This project points to a future where AI interaction becomes more integrated into our physical environments. By open-sourcing the design, OpenAI invites developers to experiment with building the next wave of ambient, helpful AI.

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The AI Career Disruption

The Recap: A former Google AI leader has issued a controversial warning, arguing that pursuing long degrees in fields like law and medicine is a waste of time because AI will advance faster than students can graduate.

Unpacked:

• The argument is that these multi-year programs are too slow for the pace of AI, with curricula often based on memorization that AI can already automate.

• Despite this warning, the demand for AI expertise is at an all-time high, with an MIT study showing that 70% of AI doctoral graduates took jobs in the private sector last year.

• The sentiment echoes across the industry, with leaders like OpenAI's Sam Altman claiming that new models can perform as a PhD-level expert in nearly any topic.

Bottom line: This debate signals a major shift away from traditional credentials and toward uniquely human skills like creativity and emotional intelligence. Professionals must now prioritize continuous adaptation and lifelong learning to stay ahead.

The Shortlist

Adobe launched Acrobat Studio, a new platform that transforms collections of PDFs and web pages into conversational knowledge hubs using customizable AI assistants and integrated Adobe Express creation tools.

OpenAI introduced ChatGPT Go, its cheapest paid subscription tier rolling out in India, which offers extended access to GPT-5 and other premium features for under $5 per month.

Parachute emerged from YC's S25 batch with a governance platform designed to help hospitals safely evaluate, deploy, and continuously monitor clinical AI models for risks like bias and hallucinations.

A study published in The Lancet found that gastroenterologists’ ability to detect polyps without AI help dropped by 20% after just three months of using an AI-assisted system, raising concerns about rapid skill dependency.

Signing off,

David, Lucas, Mitchell — The Recap editorial team