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27:39EN3Blue1Brown and Jane Street on Trading, Machine Learning and CultureGrant Sanderson, Nitya, In Young, Craig, Alok · 3Blue1BrownGrant Sanderson talks with Jane Street colleagues about market making, shared compute, research and the paths that brought them to the firm.
4:41ENInside Jane Street’s Internship: Projects, Mentorship and LearningCody · Jane StreetInterns and employees describe collaborative interviews, learning finance from the basics, and working on projects used by the firm.
29:36ENJane Street on GPU Infrastructure, Trading and HiringDwarkesh Patel, Yaron Minsky, Daniel Pontecorvo · Dwarkesh PatelDwarkesh Patel speaks with Ron Minsky and Dan Pontecorvo about trading at different speeds, building data centers and expanding compute and teams.
59:46ENIn Young Cho on Trading Research and Finding Signal in Financial DataYaron Minsky, In Young Cho · Jane StreetIn Young Cho and Ron Minsky discuss the blurred lines between trading, research, and engineering, and why machine learning in markets is difficult.
1:03:21ENHorace He on Building ML Systems for Trillion-Trillion OperationsHorace He · MetaHow GPU bottlenecks, compiler design and distributed parallelism shape the systems behind large-scale model training.
3:16ENJP on Machine Learning and Trading at Jane StreetJP · Jane StreetA Hong Kong equities trader describes his changing workday, the growth of research infrastructure, and the distinctive challenges of machine learning in finance.
2:46ENMatt on Machine Learning and Trading at Jane StreetMatt · Jane StreetA Hong Kong equities trader describes the challenges of financial data, the firm’s ML roles and its collaborative culture.
2:41:47ENGeometry Is the Cilantro of MathGast: Jordan Ellenberg · Moderation: Lex FridmanJordan Ellenberg tells Lex Fridman that the last 150 years of mathematics have been about one question: when two things count as the same.
59:33ENLaurent Mazare on Python, OCaml and Machine LearningYaron Minsky, Laurent Mazare · Jane StreetA researcher compares exploratory notebooks with robust production systems, and explains how language interoperability and resource management connect the two.
1:49:51ENThe Idea Once Called a Devolution Now Powers Almost Every New ChipGast: David Patterson · Moderation: Lex FridmanTuring Award winner David Patterson talks with Lex Fridman about RISC, RAID, Moore's Law, open hardware, and why chips without a software stack die.
57:30EN400 Spins in a Pocket, and a Universe Too Small to Store ThemGast: Leonard Susskind · Moderation: Lex FridmanLeonard Susskind tells Lex Fridman why quantum computers are not faster laptops, why string theory is a tool rather than a citizenship, and why nobody should claim to have found the bottom of the well.
1:28:53ENMachine Learning for Business Students: Powerful, Narrow, and Easier to Fool Than You ThinkGast: MIT Sloan · Moderation: Lex FridmanLex Fridman's non-technical MIT Sloan lecture explains how machine learning works, why it is so capable at perception, and where it still breaks in the real world.
37:00ENInside the YouTube Algorithm: Related Graphs, Satisfaction Surveys and the Viewers Who Are Part of the CodeModeration: Lex FridmanYouTube's head of search and discovery, Cristos Goodrow, explains to Lex Fridman how search and recommendations work, which signals matter, and how the team measures whether viewers are better off.
10:39ENStatistics as Decision-Making: Michael I. Jordan on Bayesians, Frequentists and the Ideas Between ThemModeration: Lex FridmanBerkeley's Michael I. Jordan explains where statistics came from, why it is really about decisions, and how empirical Bayes and false discovery rate bridge two rival philosophies.







