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Vsevolod Leonov Has Spent a Career Moving Toward the Machine Room
He learned the internet through portals, games and partnerships. Now the former Google executive is testing the economics and infrastructure of open-source AI with his own hands.
Ramu Arunachalam
Ramu Arunachalam is a General Partner at A.Capital Ventures, the San Francisco-based VC firm known for a founder-friendly approach and a portfolio spanning Notion, Anthropic, Databricks, Coinbase, and Replit. An engineer turned product manager turned investor, Ramu brings a rare depth of technical credibility to the table - he helped build VMware's first virtual switch, shaped a16z's Cloud and Big Data thesis during his time as Partner there, and now leads A.Capital's $180M Fund V with a focus on AI and crypto-native companies.
Byung-Gon Chun
Byung-Gon Chun is the CEO and Co-founder of FriendliAI, and a professor of Computer Science and Engineering at Seoul National University currently on leave. A systems researcher turned founder, he is best known for inventing continuous batching - the scheduling technique that became the default standard in every major LLM inference engine, from vLLM to TensorRT-LLM. His lab published the foundational ORCA paper at OSDI 2022, and he then turned that academic insight into FriendliAI, an enterprise AI inference platform that raised $26.7M and supports over 550,000 models from Hugging Face. With a career spanning Intel, Yahoo!, Microsoft, and Facebook, Chun brings rare depth across both research and production AI infrastructure.
David Cahn
David Cahn is a Partner at Sequoia Capital and one of the most closely-watched voices in AI infrastructure investing. A former General Partner and COO of Venture at Coatue Management, he backed foundational AI companies including HuggingFace, Runway, and Supabase before joining Sequoia in 2023. Known for his sharp, data-driven essays — most notably 'AI's $600B Question' — Cahn argues that the durability of the AI wave depends not on clever applications but on who controls the physical stack: servers, steel, and power. A University of Pennsylvania graduate, NYC native, and self-described iterative thinker, he is backing the next generation of AI-native companies from Sequoia's Menlo Park headquarters.
Nathan Lambert
Nathan Lambert is a Senior Research Scientist and Post-Training Lead at the Allen Institute for AI (Ai2), where he leads open-source language model development on the OLMo and Tulu series. A UC Berkeley PhD, he previously led the RLHF team at Hugging Face, co-building the TRL library and the Zephyr model. He runs Interconnects AI, a Substack newsletter read by tens of thousands covering post-training, open models, and AI policy, and is the author of The RLHF Book (Manning Publications). With roughly 8,000 academic citations and a reputation for demystifying the hardest parts of modern AI, Lambert is one of the most trusted voices at the intersection of open-source AI research and public education.
Daniel Bourke
Daniel Bourke is an Australian machine learning engineer, educator, and content creator who teaches over 230,000 students worldwide through the Zero to Mastery Academy. Operating under the brand 'mrdbourke', he built a self-designed AI education path from a film degree and zero coding experience, and now creates courses on PyTorch, TensorFlow, and Hugging Face. He co-founded Nutrify, an AI-powered food tracking app, with his brother Joshua, and published his debut novel 'Charlie Walks' in 2024. His newsletter 'Eat, Move, Learn, Make' blends personal philosophy with technical insight.