Tasha Pais

on the atlas — 65

• Surgeons Should Not Look Like Surgeons | by Nassim Nicholas Taleb | INCERTO | Medium1 savers
• life updates, 2026 q0.5 - by Hardeep Gambhir3 savers
• Sulaiman Khan Ghori | Thiel Fellowship1 savers
• The month that triathlon took over my life | by Grace Gerwe | Medium1 savers
• Khan Space Industries1 savers
• Google’s Genie 3 Is What Science Fiction Looks Like1 savers
• Genie 3: A new frontier for world models — Google DeepMind1 savers
• Noam Brown | Innovators Under 351 savers
• Style-Aware Generative Models · Gwern.net1 savers
• How I Trained Action Chunking Transformer (ACT) on SO-101: My Journey, Gotchas, and Lessons1 savers
• 3 Challenges and 2 Hopes for the Safety of Unsupervised Elicitation1 savers
• Nikolaus West on X: "The data layer tax for robot learning" / X1 savers
• Careers | Fulcrum1 savers
• Keller Jordan on X: "Modded-NanoGPT Optimization Benchmark Hundreds of neural network optimizers have been proposed in the literature, recently including dozens citing Muon: MARS, SWAN, REG, ADANA, Newton-Muon, TrasMuon, AdaMuon, HTMuon, COSMOS, Conda, ASGO, SAGE, and Magma, to name a few. The https://t.co/y6RykqhzL2" / X1 savers
• Introducing HealthBench | OpenAI1 savers
• openai/parameter-golf: Train the smallest LM you can that fits in 16MB. Best model wins! ·1 savers
• Gaming Worlds Could Be The Answer To AI’s Data Problem1 savers
• Research Engineer/Scientist - Human Alignment, Consumer Devices @ OpenAI1 savers
• SoC #5: The Computer Was Only a Transition1 savers
• On Optimism for Interpretability3 savers
• Chess-GPT’s Internal World Model | Adam Karvonen1 savers
• Writing for LLMs So They Listen · Gwern.net2 savers
• Curius / Bookmarks for the extremely curious155 savers
• Gmail102 savers
• The Bitter Lesson74 savers
• i wish we’d grown up on the same advice - by vincent huang61 savers
• How I've run major projects | benkuhn.net50 savers
• finding the right people - by Nicole - startingfromnix49 savers
• Andrej's advice for success39 savers
• No one can teach you to have conviction | benkuhn.net38 savers
• Advice for Early Career — Celine Halioua38 savers
• Defeating Nondeterminism in LLM Inference - Thinking Machines Lab37 savers
• The Old World Is Dying: Advice for 2026 graduates36 savers
• The First Fully General Computer Action Model | blog35 savers
• On the Biology of a Large Language Model31 savers
• How To Scale Your Model26 savers
• Why We Think | Lil'Log22 savers
• Zoom In: An Introduction to Circuits21 savers
• The Gentle Singularity - Sam Altman21 savers
• You don't have to be busy to be prolific | thesephist.com20 savers
• Circuit Tracing: Revealing Computational Graphs in Language Models18 savers
• How to Land a Frontier Lab Job17 savers
• Dario Amodei — The Urgency of Interpretability17 savers
• The Shigalyovist Turn16 savers
• The Era of Experience Paper.pdf15 savers
• Neural Networks, Manifolds, and Topology -- colah's blog14 savers
• The discomfort of intimacy - by Kasra - Bits of Wonder14 savers
• the agony of eros: dating - by Ava - bookbear express13 savers
• Tips for Empirical Alignment Research — AI Alignment Forum13 savers
• Demystifying evals for AI agents \ Anthropic11 savers
• cdixon | The idea maze10 savers
• On neural scaling and the quanta hypothesis10 savers
• The Artificial Intelligence Revolution: Part 2 - Wait But Why9 savers
• Reward Hacking in Reinforcement Learning | Lil'Log9 savers
• An Ambitious Vision for Interpretability — AI Alignment Forum8 savers
• GenAI Handbook7 savers
• The Zero-Day Flaw in AI Companies7 savers
• Futarchy: Vote Values, But Bet Beliefs6 savers
• State of RL for reasoning LLMs | A. Weers6 savers
• What Google Learned From Its Quest to Build the Perfect Team - The New York Times5 savers
• ⭐️ Fast LLM Inference From Scratch4 savers
• vivek on X: "how to be good at research" / X4 savers
• Man-Computer Symbiosis3 savers
• Features as Rewards: Using Interpretability to Reduce Hallucinations2 savers
• Exclusive: Emmett Shear Is Back With a New Company and A Lot of Alignment2 savers