Michael Kao is a veteran macro investor, former hedge fund manager, and founder of Akanthos Capital Management, now running his family office. A UC Berkeley EE/CS and Wharton MBA graduate who traded commodities at Goldman Sachs and co-founded Canyon Capital Arbitrage Fund, he built his career on a proprietary framework called 'Alpha With Asymmetry.' Known online as @UrbanKaoboy, he publishes the Kaoboy Musings newsletter on Substack - covering finance, macroeconomics, geopolitics, and thrash metal - and co-hosts the KAOS THEORY podcast with Grant Williams.
Josh Tobin is a machine learning infrastructure pioneer who spent three years as a research scientist at OpenAI - contributing to the famous Rubik's cube robot hand - before earning his PhD from UC Berkeley under Pieter Abbeel. He co-founded Gantry, an ML monitoring and continual learning startup that raised $28.3M, and created Full Stack Deep Learning, the first course focused on production ML engineering. His domain randomization technique, which transfers neural networks trained in simulation to the real world, has been cited over 600 times and reshaped how robotics teams build perception systems. He runs a newsletter focused on ML infrastructure and ops.
Shreya Shankar is a PhD candidate at UC Berkeley's EPIC Lab building AI-powered data systems that are reliable and cost-efficient. A Stanford-trained engineer who worked at Google Brain and Meta, she bridges academic research and industry practice through DocETL (an open-source LLM data processing system with 3.5K+ GitHub stars used by 30+ S&P 500 companies), an O'Reilly book on AI evals co-authored with Hamel Husain, and a Maven course that has reached 4,500+ professionals. She is on the CS faculty job market and gave a faculty candidate talk at Carnegie Mellon in March 2026.