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Latent Space’s December 2023 recap follows the competition over training data, inference economics, multimodal products, and application tooling—then turns to coding agents and personal-context hardware.
A Kyiv-based robotics company developing AI autonomy modules and drones for Ukraine’s defense, beginning with terminal guidance and expanding into interception and broader autonomous capabilities.
AI economics, inference bandwidth and chip design in Latent Space’s November 2023 conversation with Dylan Patel—ending with the question of whether training can escape a single data center.
Part 2 of 3 follows Lila Sciences from improving drug-development odds to connecting instruments, shortening experimental cycles, and training scientific models—then asks where simulation still falls short.
From a bot over Notion and Slack to SQL agents and application traces, LangChain addresses the work surrounding a model call.
Tulu’s practical post-training recipe leads to harder questions: how models learn to use tools, choose plans, recognize success, and remain useful as rewards become more complex.
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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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