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3Blue1Brown· Oct 16, 2017Gradient Descent: How a Neural Network LearnsGrant Sanderson, Leisha Lee · 3Blue1BrownA visual introduction to minimizing training cost, and a look at what a digit classifier does and does not learn.
18:18EN3Blue1Brown· Jul 21, 2017Hilbert’s Curve: What an Infinite Path Reveals About Finite ImagesA recursive path through pixels leads to a continuous curve that fills a square.
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Jane Street· Jul 18, 2017Yudkowsky and Hanson Debate Whether an Intelligence Explosion Would Be LocalEliezer Yudkowsky, Robin HansonA historical debate about self-improving AI, accumulated knowledge, innovation and whether a first mover could gain a decisive lead.
52:51ENJane Street· Jun 20, 2017Caveat Configurator: When Configuration Becomes CodeDominick LoBraico · Jane StreetDominick LoBraico explains why flexible OCaml plugins created production problems at Jane Street, and how configuration generation and disciplined plugin management address them.
5:38EN3Blue1Brown· May 7, 2017Higher-Order Derivatives: Curvature, Acceleration and JerkGrant SandersonA visual introduction to derivatives of derivatives.
22:19EN3Blue1Brown· May 7, 2017Taylor Series: Turning Derivatives Into ApproximationsBuild a cosine approximation, see the quadratic term geometrically, and understand convergence.
12:39EN3Blue1Brown· May 6, 2017Why Average Height and Average Slope Connect Integrals and Derivatives3Blue1Brown uses the average of sin x to derive an intuitive link between area and the slope of an antiderivative.
16:50EN3Blue1Brown· Apr 29, 2017The Derivative and the Paradox of Instantaneous ChangeGrant SandersonA geometric introduction to difference quotients, limits and the derivative of a cubic.
59:14ENJane Street· Mar 15, 2017Arjun Guha on Verifying System ConfigurationsArjun Guha · UMass AmherstPuppet manifests can be declarative yet nondeterministic or non-idempotent. A verification tool models resource interactions to find those problems.
38:17ENJane Street· Mar 13, 2017How to Build a Reliable Exchange with Deterministic ReplayBrian Nigito · Jane StreetA matching engine, multicast and state-machine replication can turn a high-throughput exchange into a recoverable system. This talk explains the design and its tradeoffs.
25:44ENJane Street· Mar 9, 2017Why Functional Programming Matters at Jane StreetSebastian Funk · Jane StreetA Jane Street developer revisits John Hughes’s classic argument and explains why expressive static types rank highest for trading systems.
28:31ENJane Street· Mar 9, 2017Incremental: Self-Adjusting Computations in OCamlSebastian Funk · Jane StreetSebastian explains Jane Street’s dynamic dependency graph library and the algorithms behind efficient updates.
13:58EN3Blue1Brown· Nov 25, 2016Solving the Towers of Hanoi by Counting in BinaryKeith SchwarzBinary carries select the disk to move, and a recursive argument explains why the solution uses the fewest possible moves.
16:29EN3Blue1Brown· Nov 4, 2016Why Topology Matters: An Inscribed Rectangle ArgumentGrant SandersonGrant Sanderson turns pairs of points on a curve into a Möbius strip.
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Lex Fridman· Sep 27, 2016PodcastFrom Word Vectors to Memory Networks: The Building Blocks of Deep NLPHost Lex FridmanRichard Socher explains how word embeddings, recurrent models, GRUs, pointer mixtures, and dynamic memory networks turn language tasks into trainable end-to-end systems.
13:10EN3Blue1Brown· Sep 1, 2016Why Cross-Product Coordinates Match Their GeometryGrant SandersonA linear transformation and duality connect the determinant formula to area and direction.
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GOTO Conferences· Aug 29, 2016How Platforms Work: From Deployment to RecoveryCasey WestCasey West outlines six platform capabilities and demonstrates them with Cloud Foundry in 2016.
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Google DeepMind· Jul 5, 2016Mustafa Suleyman’s 2016 Vision for Technology in Patient CareMustafa Suleyman · DeepMindA historical talk on clinician-led design, kidney-injury alerts, eye-scan research and the need for scrutiny.
1:09:24ENJane Street· Apr 5, 2016Yaron Minsky on Effective ML: Writing OCaml for Code ReadersYaron Minsky · Jane StreetPractical lessons from Jane Street on using types, interfaces and abstraction to keep a large OCaml codebase understandable and correct.
16:01EN3Blue1Brown· Apr 1, 2016The Brachistochrone: Why the Fastest Descent Is a CycloidGrant Sanderson, Steven StrogatzGrant Sanderson and Steven Strogatz explore Bernoulli’s light analogy and a geometric proof.
1:06:39ENJane Street· Mar 31, 2016Why Jane Street Uses OCamlYaron Minsky · Jane StreetA Jane Street talk explains how functional programming and static types support reliable trading software, and examines the costs of choosing a less common language.
23:58ENJane Street· Mar 31, 2016Effective ML: Errors, Abstraction and Managing ComplexityYaron Minsky · Jane StreetA Jane Street engineer discusses explicit failure, boilerplate, type-system restraint and the practical role of side effects.
1:04:56ENJane Street· Mar 31, 2016Yaron Minsky on Incremental: From Research Idea to Production LibraryYaron Minsky · Jane StreetA history of the algorithms, memory problems and performance tradeoffs behind Jane Street’s OCaml library for self-adjusting computations.
1:12:41ENJane Street· Mar 31, 2016Ron Minsky on Trading, Correctness and Jane Street’s Shift to OCamlYaron Minsky · Jane StreetA Jane Street technologist explains the market-making business and why readability, types and predictable performance shaped the firm’s choice of OCaml.Load moreShowing 24 of 4,485