Where I express personal thoughts in words
Stanford published 9 lectures from CS 329A, its graduate course on self-improving AI agents, and I spent 3 weeks last month working through them. One argument runs underneath all 9: the generator has raced ahead of the verifier. More samples put a correct answer somewhere in the pile. Nothing tells you which one it is. This recap walks the lectures in the order they were taught, and nearly every number in it came out of a PDF rather than off a slide.
Jason Risch is an investor on the enterprise team at Greylock - investing in security, AI/ML, data, infrastructure, and developer tools. Before joining Greylock, he incubated ML companies at AI Fund and was a management consultant at McKinsey. Jason is a Bay Area native, graduated from Stanford, and when not working, can be found reading, hiking, playing Age of Empires, and cheering on Stanford Football.
Chetan Sharma is the Founder & CEO of Eppo, a next-gen A/B experimentation platform that is designed to spur entrepreneurial culture.
As the 4th data scientist at Airbnb and an early data scientist at companies like Webflow, Chetan has been focused on the maturity curve of growth-stage companies and how to establish data as a central stakeholder in decision-making. He previously led the team that developed Airbnb's knowledge repo and has led data teams focused on production machine learning and instrumentation integrity.
Frank Liu is the Director of Operations at Zilliz with nearly a decade of industry experience in machine learning and hardware engineering. Prior to joining Zilliz, Frank co-founded an IoT startup based in Shanghai and worked as an ML Software Engineer at Yahoo in San Francisco. He presents at major industry events such as Open Source Summit and writes tech content for leading publications such as Towards Data Science and DZone. Frank holds MS and BS degrees in Electrical Engineering from Stanford University.
Alexa Grabell is the co-founder and CEO of Pocus, a Revenue Data platform that is purpose-built for GTM teams to analyze, visualize, and action data about their prospects and customers without needing engineers.
Alexa’s passion for Product-Led Sales started when she led sales strategy & operations at Dataminr, where she built internal solutions to equip sales teams with data. She studied engineering at Vanderbilt University and received her MBA from Stanford University.
Nnamdi Iregbulem, a Partner at Lightspeed Venture Partners, is a self-taught programmer and lifelong technology nerd. His mission is to increase total software output by supporting entrepreneurs building technical tools for technical people. He focuses on investments in technical enterprise software such as developer tools, application infrastructure, and machine learning.
Grace Isford is a Partner based in Lux Capital's New York City office. She invests in companies innovating at the nexus of the computational sciences – data, AI and ML infrastructure, network and compute infrastructure, and cutting-edge technological applications, especially in healthcare and financial services. She focuses on data and machine-learning startups that are hyper-personalizing user experiences and transforming legacy industries, as well as fintech and blockchain infrastructure companies building the next-gen developer stack and payment rails.
Astasia Myers is a Partner on Quiet Capital's enterprise team leading investments in ML, data infrastructure, open-source, developer tools, and security. She focuses on pre-seed, seed, and Series A.
Prior to joining Quiet, Astasia was an investor in Redpoint's early-stage enterprise team, where she partnered with Dremio, LaunchDarkly, Solo.io, Preset, Hex, Cyral, among others. Before that, she worked at Cisco Investments, where she focused on cloud-infrastructure M&A and investments, including Cohesity, Datos IO, Elastifile, Guardicore, Springpath, and the funding of internal stealth projects.
Cody Coleman is the Founder and CEO of Coactive AI. He is also a co-creator of DAWNBench and MLPerf and a founding member of MLCommons. His work spans from performance benchmarking of hardware and software systems to computationally efficient methods for active learning and core-set selection. He holds a Ph.D. in Computer Science from Stanford University, where Professors Matei Zaharia and Peter Bailis advised him, and an MEng and BS from MIT.
