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1:48:29EN
JSJane Street· 16 oct. 2026How AI Is Changing Programming: John Krazit and Ron MinskyRon Minsky, John Krazit · Jane StreetJane Street’s AI tooling lead and the Signals and Threads host examine agent infrastructure, security, code review and the changing experience of writing software.Agents de codeDeveloper productivityÉvaluations+2
1:36:37EN
JSJane Street· 23 sept. 2026Aaron Bauer on Teaching Software Engineering in the Age of AIRon Minsky, Aaron Bauer · Jane StreetHow learning goals, active practice and editor design shape engineering education when models can generate the code.AI in EducationSoftware engineeringEducation+2
9 diapositives1:05:45EN
JSJane Street· 11 sept. 2026Cyrus Omar on Live Programming and a Computational Commons for Humans and AICyrus OmarA demonstration of Hazel shows how immediate feedback, structured collaboration and carefully scoped permissions could support people and AI agents working together.Programming LanguagesHuman-AI CollaborationWorkflows de développement et tests+2
1:25:00EN
JSJane Street· 2 sept. 2026Eric Mannes on Turning Messy External Data Into Trading ResearchRon, Eric Mannes · Jane StreetFrom commodity futures and an Excel risk system to point-in-time datasets and AI, Eric Mannes explains the domain knowledge behind data engineering at Jane Street.Data quality & curationWorkflows de développement et testsInvesting+2
7 diapositives1:16:29EN
JSJane Street· 26 août 2026Grant Sanderson and Alok Puranik: Positional Encodings Through Group TheoryGrant Sanderson, Alok Puranik · 3Blue1BrownStarting with assumptions about attention, they derive matrix exponentials and connect rotations, decay and Jordan blocks to RoPE and ALiBi.Transformers & attentionMathematicsFondamentaux du ML+1
1:34:29EN
JSJane Street· 24 juin 2026Jacob Baskin on Building Superstore and Scheduling the HiveYaron Minsky, Jacob Baskin · Jane StreetThe Jane Street engineer traces the design choices behind a distributed analytical database and the challenge of allocating a growing research cluster.Infrastructure et déploiementSoftware engineeringDecision Making+1
1:34:36EN
JSJane Street· 1 juin 2026Nate Foster: Treating the Network as a ProgramYaron Minsky, Nate Foster · Jane StreetFrom programmable switches to BGP, a programming-languages researcher explains how higher-level policies and formal models can make networks easier to change.Infrastructure et déploiementProgramming LanguagesSoftware engineering+2
5 diapositives1:08:22EN
JSJane Street· 10 avr. 2026Mark Doss on Production Engineering for High-Stakes TradingMark Doss · Jane StreetWhy every order matters, how event-based monitoring detects unexpected failures, and what a realistic incident reveals about trading operations.Observabilité et fiabilitéInfrastructure et déploiementSoftware engineering+2
7 diapositives46:35EN
JSJane Street· 25 mars 2026Jon Gjengset on the Cost of Concurrency CoordinationJon GjengsetWhy shared cache lines can make even read-heavy locks slow, and how a different data structure trades writer work for scalable reads.Software engineeringProgramming Languages
1:48:21EN
JSJane Street· 17 mars 2026Will Wilson on Deterministic Simulation and the Hard Problems of Software TestingYaron Minsky, Will Wilson · Jane StreetThe Antithesis co-founder explains how replayable simulations explore complex software, why properties matter and where testing meets its limits.Workflows de développement et testsSoftware engineeringCode review & verification+2
5 diapositives1:22:49EN
JSJane Street· 31 janv. 2026Bryan Cantrill: Why Software and Hardware Must Be Designed TogetherBryan Cantrill · Oxide Computer CompanyFrom a stubborn CPU reset to disappearing drives, Oxide’s cofounder makes the case for designing and debugging computing systems across the hardware–software boundary.Software engineeringInfrastructure et déploiementObservabilité et fiabilité+2
7 diapositives1:20:57EN
JSJane Street· 23 déc. 2025Matt Godbolt: Inside Skylake’s Out-of-Order PipelineMatt GodboltA guided tour of instruction decoding, register renaming, execution and memory ordering, grounded in reverse engineering and careful measurements.SemiconductorsSoftware engineeringBenchmarks
7 diapositives1:00:15EN
JSJane Street· 17 déc. 2025Arjun Guha on How Language Models Represent Code and How People Prompt ThemArjun Guha · Northeastern UniversityExperiments with activation steering and student-written prompts reveal how programming models behave—and why evaluating them requires more than a single benchmark score.Programming LanguagesModel InterpretabilityAgents de code+2
5 diapositives47:43EN
JSJane Street· 11 nov. 2025Making GPU Training Faster: Pipelines, Fusion and Custom KernelsCorwin · Jane StreetTwo Jane Street speakers explain how to diagnose idle GPUs, reduce memory traffic and build a parallel reduction kernel.GPU programming & kernelsModèles et entraînementSoftware engineering
9 diapositives55:03EN
JSJane Street· 29 oct. 2025Neil Mitchell: How Pyrefly Checks Python at ScaleNeil Mitchell, Roman · MetaA tour of Python's type system and the incremental architecture behind a fast, open-source checker and language server.Software engineeringOpen-source ecosystems
9 diapositives52:05EN
JSJane Street· 24 oct. 2025Corwin de Zahr: Exploring OCaml Runtime Safety Through a CTF ChallengeCorwin de Zahr · Jane StreetA deliberately restricted OCaml sandbox becomes a way to examine type safety, callbacks, memory representation and binary debugging.Programming LanguagesCybersecuritySoftware engineering
1:12:58EN
JSJane Street· 4 sept. 2025Chris Lattner on Mojo and the Search for Portable GPU PerformanceYaron Minsky, Chris Lattner · Jane StreetRon Minsky and Chris Lattner discuss the language and compiler design behind Modular’s effort to make accelerator programming both portable and fast.Programming LanguagesGPU programming & kernelsSoftware engineering+1
11 diapositives1:01:23EN
JSJane Street· 27 août 2025Will Crichton on Making Rust More UnderstandableWill Crichton · Brown UniversityOwnership visualizations, interactive trait diagnostics and program slicing illustrate an evidence-based approach to developer tools.Programming LanguagesSoftware engineeringWorkflows de développement et tests+1
58:47EN
JSJane Street· 28 juil. 2025Daniel Pontecorvo on Cooling Trading Infrastructure and WorkspacesYaron Minsky, Daniel Pontecorvo · Jane StreetFrom dense GPU racks to movable desks, Jane Street’s physical engineering team designs around heat, power, failure and human comfort.Infrastructure et déploiementEnergyObservabilité et fiabilité+1
4 diapositives1:27:41EN
JSJane Street· 24 juil. 2025Ron Minsky on the Saga of Multicore OCaml at Jane StreetRon Minsky · Jane StreetA production migration exposed garbage-collector regressions, led to a new pacing design, and illustrated the difficulty of turning research into reliable infrastructure.Programming LanguagesSoftware engineeringObservabilité et fiabilité
1:19:40EN
JSJane Street· 28 mai 2025Ian Henry on Building Trader Tools, Functional UIs and Creative CodingRon Minsky, Ian Henry · Jane StreetFrom high-density options interfaces to a 3D playground, Ian Henry and Ron Minsky explore the software choices that make complex tools usable.Software engineeringProduct engineeringProgramming Languages+2
10 diapositives47:08EN
JSJane Street· 3 avr. 2025Chris Casinghino on Making OCaml Safe for Performance EngineeringChris Casinghino · Jane StreetJane Street’s OCaml extensions use layouts and modes to offer more control over memory and parallelism while preserving safety and familiar programming patterns.Programming LanguagesSoftware engineering
59:46EN
JSJane Street· 12 mars 2025In Young Cho on Trading Research and Finding Signal in Financial DataRon 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.Machine LearningFintechSoftware engineering+2
4 diapositives1:03:21EN
JSJane Street· 9 déc. 2024Horace 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.GPU programming & kernelsDistributed training & inferenceMachine Learning+2
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