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⚡️ Prism: OpenAI's LaTeX "Cursor for Scientists" — Kevin Weil & Victor Powell, OpenAI for Science

Jan 27, 2026 · 36:00

Kevin Weil (VP of OpenAI for Science) and Victor Powell (Prism product lead) launch Prism, a free AI-native LaTeX editor that embeds GPT-5.2 directly into the scientific writing workflow, eliminating copy-pasting between ChatGPT and Overleaf and turning weeks of LaTeX formatting into minutes of natural language instruction. The origin story reveals Kevin discovered Victor's stealth company Cricket on Reddit and DM'd him to bring the team into OpenAI. In the live demo, Prism proofreads papers paragraph by paragraph, converts a whiteboard commutative diagram photo into TikZ code, generates 30 pages of general relativity lecture notes in seconds, and verifies complex symmetry equations in parallel chat sessions. They argue that LaTeX typesetting is the bottleneck diverting scientists from actual research, and that unlimited free collaboration and multi-line diff generation make Prism a 'tool for thought' rather than just a publishing tool. Kevin predicts 2026 will be for AI in science what 2025 was for AI in software engineering — a year when it becomes essential. The discussion also covers OpenAI's approach to accelerating science broadly, including the role of robotic labs and…

Training Llama 2, 3 & 4: The Path to Open Source AGI — with Thomas Scialom of Meta AI

Jul 23, 2024 · 1:04:34

Thomas Scialom, Llama 2 lead and Llama 3 post-training lead at Meta AI, explains why scaling laws must go beyond Chinchilla—training models longer on more tokens yields better inference efficiency than bigger models, a lesson that drove Llama 3's 15 trillion token pre-training. He details how synthetic data from Llama 2 bootstrapped Llama 3's post-training, eliminating human-written SFT data, and why RLHF outperforms imitation learning: humans are better discriminators than generators, enabling superhuman outputs. Scialom defends the dense 405B architecture over MoE, calls tokenizer vocab size underrated (128k tokens vs Llama 2's 32k), and reveals Llama 4's focus on agentic capabilities—tool use, multi-step reasoning—as the path to open-source AGI. Meta AI is hiring researchers with rigorous first-principles thinking.