▶ ai·
The Sequence Knowledge - Issue 937: RSI in Post-Training: The Loop That Already Shipped
Inside the RSI post-training pipeline
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▶ gemini·
The Sequence Radar - Issue 936: Last Week in AI: Gemini Talks, Astra Practices Law, Figure Folds Laundry, and Crusoe Powers It All
Google tackles real-time interaction, OpenAI targets legal workflows, Figure tests unfamiliar homes, and investors double down on compute.
▶ ai·
The Sequence Opinion - Issue 935: Chinese Algorithmic Efficiency vs. American Scale in Frontier AI
How Chinese and American labs pursue the next generation of intelligence
▶ deepseek·
The Sequence Learning Loop - Issue 934: Understanding DeepSeek V4.1 Flash, DeepMind’s AlphaGenome Atlas and Muse
How architecture and system design turn model capability into useful work
▶ ai·
The Sequence Knowledge - Issue 933: When the Factory Starts Building Itself
Three frontier labs have now said out loud that their models help build their models. The interesting part is not the percentage. It is which half of the job got automated, and why.
▶ deepseek·
The Sequence Radar - Issue 932: Last Week in AI: DeepSeek V4.1-Flash, AlphaGenome Atlas, Meta Muse, and OpenAI’s Proposed Math Breakthrough
Faster models, nine billion genetic predictions, personal agents, and a proof that could make mathematical history.
▶ gpt·
The Sequence Opinion - Issue 931: Robotics Is Waiting for Its ChatGPT Moment
Generalist models are expanding what robots can do. The real breakthrough will be how easily we can teach them something new.
▶ ai·
The Sequence Chat - Issue 930: Arena’s Anastasios Angelopoulos on Chatbot Arena, Evaluation, and What Models Actually Measure
From Berkeley’s Chatbot Arena to Agent Arena: preference rankings, cost-per-task frontiers, and the hard problems in measuring real-world AI utility.
▶ gemini·
The Sequence Learning Loop - Issue 929: Learn About Meta Muse Spark, World Labs’ Atlas and Gemini 3.8 Flash
Three releases that deserve your attention.
▶ ai·
The Sequence Knowledge - 928: The Missing 5%: Why Distillation Is Harder Than It Looks
Distillation can make models smaller, faster, and cheaper. The difficult part is deciding what the student cannot afford to forget.
▶ ai·
The Sequence Radar - Issue 927: Last Week in AI: Model Madness: The Frontier Has a Refresh Button
Every lab decided to release models last week.
▶ ai·
The Sequence Opinion - Issue 926: AI Moats in the Age of Scaling Laws
Capital, compute, process, distribution, and the search for durable Power
▶ qwen·
The Sequence Learning Loop - Issue 925: Learn About Fable and Mythos 5.1, GLM-5.3-Flash, and Qwen 3.8
Three releases, three different bets. Let’s dive in.
▶ ai·
The Sequence Knowledge- Issue 924: The Distilled Models You Need to Know About
From DistilBERT and Gemini Flash to Gemma, Llama, Qwen, DeepSeek, Phi, Ministral, and PrismML’s Bonsai 27B.
▶ ai·
The Sequence Radar-Issue #923: Last Week in AI: AI’s Industrial Turn
NVIDIA, Anthropic, NScale, and a16z show how the AI race is moving from models to infrastructure.
▶ ai·
The Sequence Robotics - Issue #922: Learning About LeRobot: The Transformers Moment for Robots
Robotics Gets Its PyTorch Stack.
▶ ai·
The Sequence Opinion #921: AI’s Sixth Layer Is Finance
Jensen Huang’s five-layer cake explains how intelligence is manufactured. The missing layer explains how quickly - and by whom - it can scale.
▶ deepseek·
The Sequence Learning Loop - Issue #921: Learn About DeepSeek New Model, the Env Harness Paper and the Amazing Etched
Distilling three major AI releases to keep you current.
▶ ai·
The Sequence Knowledge #920: The Physics of Teaching: Distillation Scaling Laws
The Sequence — Distillation Series
▶ ai·
The Sequence Radar - Issue 919: Last Week in AI: Stripe Wants to Own the Token Economy
OpenRouter, Ramp, Etched, and DeepSeek reveal the emerging economic stack beneath modern intelligence.
▶ ai·
The Sequence Opinion- Issue 918: The Energy Scaling Laws of AI
Why the next frontier in intelligence will be constrained not only by algorithms and chips, but by megawatts, transmission lines, and the physics of heat.
▶ nemotron·
The Sequence Frontier Learning - Issue 917: Understanding DeepSeek V4-Pro, GLM-5.3, NVIDIA Nemotron 3.5 Lightning and NeMo Switchyard
A mini deep dive into some of the most important AI releases of last week.
▶ ai·
The Sequence Knowledge - Issue 916: From Thinking Longer to Learning Better
Why test-time compute distillation could turn inference-time reasoning into permanent model capability.
▶ grok·
The Sequence Radar- Issue 915: Last Week in AI: The Cursor Acquisition, New Grok and GLM Models, Anthropic’s Latest Deal, and River AI
New models, major acquisitions, and a new generation of AI companies are reshaping where the real competitive advantage lives.
▶ ai·
The Sequence Opinion - Issue 914: From Prompt to Token: How AI Inference Really Works
A field guide to prefill, decode, KV caches, and the systems that turn model weights into a responsive product.
▶ ai·
The Sequence Frontier Update- Issue 913: Understanding Meta Muse Code, Prime Intelligct's Prime Agent and OpenAI's Astra
Deep diving into three major AI releases.
▶ nemotron·
The Sequence Chat - Issue 912: NVIDIA’s Chris Alexiuk Talks About Nemotron, GPUs and Agentic AI
NVIDIA’s new Nemotron 3.5 Lightning, other Nemotron models, architectures and more.
▶ ai·
The Sequence Knowledge - Issue 911: Distilling Diffusion and Multimodal Models
Compressing Time, Space, and Alignment
▶ ai·
The Sequence Radar - Issue 910: Last Week in AI: Google Rewires Its Brain and Meta Hires a Coding Swarm
Jeff Dean leaves, Demis Hassabis moves upstream, and Muse Code turns software development into an orchestration problem.
▶ ai·
The Sequence Opinion #909: Return on Token: The New Economics of AI-Native Engineering
Token maxing was the adoption phase. Intelligence resource planning is what comes next.
▶ gemini·
The Sequence AI of the Week #908: You Need to Learn About Gemini Robotics
Google put a walking humanoid inside a single policy, published the reasoning half as an API, and kept the motor half behind a partner gate. The numbers explain why.
▶ ai·
The Sequence Knowlege #907: The Brain Transplant: Distilling Transformers Into Other Architectures
Weird but more common than you think. The type of distillation you were not thinking about.
▶ ai·
The Sequence Radar #906: Last Week in AI: Open Models, Intelligent Robots, and the Price of Conviction
NVIDIA's letter, Gemini Robotics, Kimi release and more.
▶ ai·
The Sequence Robotics #905: Who Builds the Robot Brain?
Frontier Labs, Startups, and the Race for Physical Intelligence
▶ ai·
TheSequence Opinion #904: The Age of Research Is Overrated. AI Engineering Is Winning
Why AI’s next breakthroughs may come from the learning loop around the Transformer—not from replacing it.
▶ ai·
The Sequence AI of the Week #903: Laguna, the 118 Billion Parameters that Walks Into a Trillion-Parameter Bar
Poolside’s 118B coding model beats systems ten times its size. The interesting part is not the architecture.
▶ ai·
The Sequence Knowledge #902: Learning About Distillation: When the Dataset Becomes the Teacher
Once models can generate their own curricula, data stops being a static resource and becomes a transmission medium for intelligence.
▶ ai·
The Sequence Radar #901: Last Week in AI: Smarter Models, Physical Machines, and the Expanding AI Stack
Opus 5 pushed the intelligence frontier forward, Atoms brought AI deeper into the physical world, and the rest of the week revealed the infrastructure, capital, and security challenges forming around
▶ ai·
The Sequence Opinion #900: Beyond the GPU: Is Google the Only Full-Stack Rival to NVIDIA?
A thesis about the biggest AI rivarly nobody is talking about.
▶ ai·
The Sequence AI of the Week #899: Inside Inkling: A Trillion-Parameter Model That Only Wakes Up 41 Billion at a Time
Thinking Machine's new model revitalizes America's open source AI approach.
▶ ai·
The Sequence Knowledge #898: The Trace Is the Teacher: Distilling Reasoning Into Small Models
From the release of DeepSeek R1, distillation in reasoning models have become one of the most common techniques in frontier AI.
▶ ai·
The Sequence Radar #897: Last Week in AI: China, Compression and the Open-Model Race
Next Week in The Sequence:
▶ ai·
The Sequence Opinion #896: Spark, Compute, and the Two Metas
Can Meta compete with frontier AI labs.
▶ ai·
The Sequence AI of the Week #895: OpenAI's Show Us Where Coding Evals Break
A visual explanation for OpenAI's new science for coding evaluations and benchmarks.
▶ ai·
The Sequence Knowledge #894: When the Student Started Talking Back: Distillation in the LLM Era
A joiurney through the evolution of distillation for frontier models.
▶ gpt·
The Sequence Radar #893: Last Week in AI: GPT-5.6, Grok 4.5, Muse Spark 1.1 and the Post-Chatbot Stack
Next Week in The Sequence:
▶ ai·
The Sequence Opinion #892: The Anatomy of a Good Environment: When Verifiability is Not Enough
What properties make certain domains suitable for AI.
▶ ai·
The Sequence AI of the Week #891: Prompting a Spreadsheet : Inside Google’s TabFM for Tabular AI
Addressing one of the biggest use cases in enterprise AI.
▶ ai·
The Sequence Knowledge #890: A Brief History of Model Distillation
The papers and techniques that laid out the ground work to evolve distillation to this level.
▶ claude·
The Sequence Radar #889: Fable 5's Comeback, ZCode's Debut, Claude Science, and the $3.5B Deployment Land Grab
New models, agents and the evolution of the FDE landscape as the new battle field in AI.