In Today’s Issue:

🎥 OpenAI is folding Sora directly into ChatGPT

⚡ NVIDIA is teaming up with Mira Murati's new Thinking Machines Lab

🤝 Meta just acquired an entire social network run by autonomous AI agents

🧮 ChatGPT introduces interactive visual learning

✨ And more AI goodness…

Dear Readers,

OpenAI is pulling Sora into ChatGPT - a clear admission that standalone AI apps are losing the war for attention, and a bet that video generation embedded where 920 million people already hang out could be the feature that pushes past one billion. But that's just the opener today: NVIDIA is going all-in on Mira Murati's Thinking Machines Lab with a gigawatt-scale compute partnership, Meta just acquired an entire social network run by AI agents, and ChatGPT now lets you drag sliders on the Pythagorean theorem until the math actually clicks. Meanwhile, Google DeepMind is making the case that one game of Go played a decade ago quietly launched a scientific revolution - from solving protein folding to cracking olympiad-level math.

Grab your coffee and dig in.

All the best,

Kim Isenberg

Thinking Machines Lab and NVIDIA announced a multi-year partnership to deploy at least 1 gigawatt of next-generation NVIDIA Vera Rubin systems for large-scale AI training and deployment starting early next year. The company is led by CEO Mira Murati, former OpenAI CTO, and the collaboration will also build optimized AI training and serving systems while expanding access to frontier and open AI models for enterprises and researchers. With NVIDIA also making a significant investment in Thinking Machines Lab, the move signals a huge push toward scalable, customizable AI infrastructure.

Thinking Machines Lab builds large-scale AI systems and platforms designed to train frontier models and deliver customizable AI tools for enterprises, researchers, and developers.

Anthropic introduces Claude Code Review

OpenAI is making a bold move: the company is bringing its video generation tool Sora directly into ChatGPT. Instead of keeping it as a separate app, users will soon be able to create AI-generated videos right where they already chat, search, and create images.

The reasoning is straightforward. The Sora standalone app launched successfully and quickly reached the top of Apple's App Store, but usage dropped off soon after, it currently sits at rank 165. Meanwhile, ChatGPT's weekly active users have climbed to around 920 million, just short of the 1 billion target OpenAI set last year. Putting Sora inside ChatGPT is a consolidation play: meet users where they already are instead of asking them to download yet another app.

There's a clear precedent. Remember when ChatGPT's image generator went viral with Studio Ghibli-style portraits last March? That moment pushed OpenAI's computational resources to their limits and turned the chatbot into a go-to tool for AI-generated visuals. OpenAI is betting video could spark the same kind of excitement.

Of course, this comes at a price. The company has projected spending over $225 billion on inference costs between now and 2030, and video generation is significantly more resource-intensive than text or images. But with Google's Gemini already offering video generation through its Veo AI, standing still isn't really an option.

Why it matters: OpenAI's decision to fold Sora into ChatGPT signals a broader industry shift toward all-in-one AI platforms rather than fragmented single-purpose apps. If video generation catches on at ChatGPT's massive scale, it could redefine how millions of people create visual content, and reshape the competitive landscape between OpenAI and Google.

Sources:
🔗 https://www.theinformation.com/articles/openai-plans-launch-sora-video-ai-chatgpt-strategy-shift?rc=bfliih

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Gemini in Google Sheets has achieved a state-of-the-art benchmark, achieving a 70.48% success rate on the full SpreadsheetBench dataset.

Ten years ago, an AI beat the world's best Go player with a move so creative it stunned experts. That moment - AlphaGo's legendary Move 37 - wasn't just a gaming milestone. It launched a chain reaction that is now transforming how we do science.

Google DeepMind has since taken AlphaGo's core methods - reinforcement learning and search - and applied them far beyond board games. The most dramatic result: AlphaFold, which cracked the 50-year-old protein folding problem and predicted structures for all 200 million known proteins. Over three million researchers worldwide now use that database to accelerate work on everything from vaccine development to environmental cleanup. The achievement earned Demis Hassabis and John Jumper the 2024 Nobel Prize in Chemistry.

But the ripple effects go further. AlphaProof, a direct descendant of AlphaGo's architecture, reached silver-medal standard at the International Mathematical Olympiad. AlphaEvolve discovered a novel approach to matrix multiplication, a foundational operation behind virtually all modern neural networks. And an AI co-scientist system independently replicated a hypothesis on antimicrobial resistance that human researchers had spent years developing.

DeepMind's vision is clear: combine Gemini's multimodal world models with AlphaGo's search techniques and specialized AI tools to build toward AGI, systems that don't just solve narrow problems but find connections across disciplines, the way the best human scientists do.

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