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Imbue’s approach starts with a recruiting product’s trust problem and asks what it takes to make models dependable enough to delegate work to.
Pushmeet Kohli and Sal Candido on protein structure, biological data, and the work required to make models useful for science and medicine.
Falling model prices weakened OpenPipe’s distillation business. Reinforcement learning offered a new opportunity: improve agents through experience, provided their training environments behave like production.
Narrow tests and leaked repository knowledge make higher scores harder to trust. The next coding evaluations need harder work and credible judgments of quality.
Creator of Verifiers and a Prime Intellect researcher working on reinforcement learning for agents that use tools across multiple turns.
Exa co-founder whose work and public arguments center on neural search and the retrieval needs of AI systems.
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A conversation with Greg Brockman about OpenAI’s path to AGI, alongside our analysis of GPT-5, Codex, and the shift to agentic coding.
Thariq Shihipar on Claude Code’s next era: prompts, harnesses, plugins, and agents—and what it takes to keep pace with the frontier.
Marc Andreessen on the future of the browser, Pi and OpenClaw, and why this wave of AI feels different.
Priscilla Chan and Mark Zuckerberg on Biohub’s plans for frontier AI and virtual biology, and the ambition to cure or prevent disease.
Anima Anandkumar on modeling the physical world, from weather to fusion reactors, and why physics needs more than language models.
John Platt on automating science, tackling climate change, and how the next generation can contribute in the age of AI.
Anthropic brings interactive apps into Claude with an open MCP standard for richer AI interfaces.
What Sam Altman’s town hall reveals about building startups in the age of AI.
Moonshot’s multimodal model brings competitive coding, native image and video understanding, and parallel agents.
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