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6 diapositivas15:33EN
JSJane Street· 26 oct 2026Figgie Strategy: Reading Hands, Winning Majorities and Pricing CardsBradley, Mike · Jane StreetJane Street traders Bradley and Mike analyze three games to show how private information, market competition and timing affect card prices.Decision MakingMathematicsFintech
7 diapositivas19:43EN
AI Engineer· 26 oct 2026Jack Wotherspoon on Building a Team of Managed AgentsJack Wotherspoon · Google DeepMindGoogle DeepMind’s Jack Wotherspoon introduces Gemini Managed Agents: cloud sandboxes that let teams run coding and research agents with a single API call. He explains how persistent environments, reusable skills, proxy-injected credentials, schedules, and specialized agents fit together.Ingeniería de agentesAgent orchestrationSandboxes & isolation+2
5 diapositivas20:55EN
AI Engineer· 26 oct 2026Jesse Hall: Build Voice Agents for Conversations, Not LeaderboardsJesse Hall · LiveKitLiveKit’s Jesse Hall explains how to evaluate voice agents as real-time systems: understand callers, handle interruptions, keep talking while tools run, and measure the delay people actually hear.IA de vozIngeniería de agentesEvaluaciones+2
8 diapositivas18:27EN
AI Engineer· 26 oct 2026Daksh Gupta on Building a Better AI Code Review AgentDaksh Gupta · GreptileGreptile co-founder Daksh Gupta explains why a webhook plus a coding agent is not enough for reliable pull-request review—and how targeted prompts, incident data, model inversion, codebase context, browser testing, and task-specific model routing can help.Code review & verificationAgentes de programaciónFlujos de desarrollo y pruebas+2
12 diapositivas17:56EN
AI Engineer· 25 oct 2026How Bridgewater Keeps Its AI Analyst Inside Permission BoundariesNikhil Benesch, Aaron Linsky · turbopufferAaron Linsky and Nikhil Benesch explain why search over an enterprise vault must honor document permissions without sacrificing recall or speed. Their solution combines vector indexing with native filtering to search hundreds of millions of vectors in roughly 120 milliseconds.IA empresarialPrivacy & data governanceSearch & retrieval+2
9 diapositivas20:58EN
AI Engineer· 25 oct 2026Vinoo Ganesh on Making Financial AI Cite Every NumberVinoo Ganesh · KeplerKepler CEO Vinoo Ganesh explains why financial AI should retrieve and cite figures while deterministic software handles the math. His design makes traceability, retrieval quality, and tenant security part of the answer itself.IA en finanzasIA empresarialGeneración aumentada por recuperación+2
10 diapositivas18:31EN
AI Engineer· 25 oct 2026Janie Gu and Suyeol Yun: Why Frontier Models Fail as Buy-Side AnalystsJanie Gu, Suyeol Yun · Google DeepMindJanie Gu explains why benchmark scores can mislead, while Suyeol Yun presents MandateBench, which tests whether a model can turn a fund mandate into a defensible investment memo. The two talks show why real workflows, reproducible grading, and evidence-backed reasoning matter.IA en finanzasBenchmarksEvaluaciones+2
8 diapositivas15:27EN
AI Engineer· 25 oct 2026What AI Engineers Do Now: Build the Loop Around AgentsAparna Dhinakaran · Arize AIAparna Dhinakaran argues that AI engineers are moving from shipping individual features to building systems that let agent teams improve them. At Arize, that means tracing agent behavior, evaluating its work against human judgment, and feeding those signals back into an always-on agent.Ingeniería de agentesEvaluacionesObservabilidad y fiabilidad+2
7 diapositivas19:37EN
AI Engineer· 25 oct 2026Jay Sahnan and Arik Bird on Building Financial Agents for the Whole WebJay Sahnan, Arik Bird · BrowserbaseBrowserbase’s Jay Sahnan and Arik Bird show how browser agents reach financial data hidden behind logins and bot defenses. Their Ramp, Bill, and Stripe examples connect reliable cloud browsers with Stagehand’s more adaptive controls.Ingeniería de agentesComputer useWorkflow automation+2
2 diapositivas17:42EN
AI Engineer· 21 oct 2026Is a Faster Model Actually Faster? Measure the Finished Job, Not the TokensMorgan Suo · MiniMaxMiniMax's Morgan Suo takes the engineering changes inside M3.1 Flash one by one and asks the question that matters to users: does the job an analyst needs actually get done sooner, cheaper and correctly?AI cost & performanceInferenceQuantization+2
27:39EN
JSJane Street· 21 ago 20263Blue1Brown 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.Machine LearningFintechCompany Culture+2
29:36EN
JSJane Street· 21 may 2026Jane 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.GPU programming & kernelsInfraestructura y despliegueMachine Learning+2
5 diapositivas15:48EN
JSJane Street· 15 may 2026Inside Jane Street’s Texas AI Data CenterDwarkesh Patel, Yaron Minsky, Daniel Pontecorvo · Dwarkesh PatelDwarkesh Patel tours a 4,032-GPU training facility with Ron Minsky and Dan Pontecorvo, examining liquid cooling, power distribution and operational safeguards.Infraestructura y despliegueAI cost & performance
8 diapositivas27:16EN
JSJane Street· 15 nov 2024Tudor Brindus on Finding and Reducing System JitterTudor Brindus · Jane StreetA memory ping-pong benchmark reveals how virtualization, interrupts, CPU frequency changes and speculation can disrupt low-latency systems.Software engineeringObservabilidad y fiabilidadInfraestructura y despliegue
7 diapositivas15:59EN
JSJane Street· 7 may 2024Tail Calls and Local Regions in OCamlA list-counting example reveals why a local closure can escape at a tail call, and how regional mode and [@nontail] affect the result.Programming LanguagesSoftware engineeringDeveloper productivity
5 diapositivas23:25EN
JSJane Street· 20 feb 2024Richard Eisenberg: How OCaml Locals Reduce Garbage-Collected AllocationRichard Eisenberg · Jane StreetAn annotated list-processing example shows why locality must be preserved both when values are created and when functions consume them.Programming LanguagesSoftware engineering
3 diapositivas22:27EN
JSJane Street· 7 feb 2024How OCaml Infers LocalityA look at local and global mode inference, module signatures, mode crossing for integers, and conversions between function types.Programming LanguagesSoftware engineering
5 diapositivas15:17EN
JSJane Street· 31 ene 2024OCaml Locals, Modes, and SubmodingA worked explanation of how local and global modes control escaping values, and how those modes interact with function types.Programming LanguagesSoftware engineering
25:42EN
JSJane Street· 8 nov 2022Graham and Andrea Work Through a Trading Mock InterviewMichael, Graham, Andrea · Jane StreetA 20-sided die game shows how a trading interview can develop through clarification, quantitative estimates and collaborative problem-solving.MathematicsHiringCareers
7 diapositivas25:44EN
JSJane Street· 9 mar 2017Why Functional Programming Matters at Jane StreetA Jane Street developer revisits John Hughes’s classic argument and explains why expressive static types rank highest for trading systems.Programming LanguagesSoftware engineeringCoding Culture
8 diapositivas28:31EN
JSJane Street· 9 mar 2017Incremental: Self-Adjusting Computations in OCamlSebastian Funk · Jane StreetSebastian explains Jane Street’s dynamic dependency graph library and the algorithms behind efficient updates.Programming LanguagesSoftware engineeringDeveloper productivity
23:58EN
JSJane Street· 31 mar 2016Effective ML: Errors, Abstraction and Managing ComplexityA Jane Street engineer discusses explicit failure, boilerplate, type-system restraint and the practical role of side effects.Programming LanguagesSoftware engineeringCode review & verification