I-X Breaking Topics in AI Conference: Flash Talk Papers

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What you'll learn

A 37-minute video from I-X: “I-X Breaking Topics in AI Conference: Flash Talk Papers”.

Programming & CS

Video by I-X, played through YouTube's embedded player.

1:02:13

I-X Seminar: Training large language models in an open & responsible way with Leandro von Werra I-XProgramming & CS

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I-X Seminar: Formulating and Evaluating Language Agents with Shunyu Yao I-XProgramming & CS

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But what is a neural network? | Deep learning chapter 1 3Blue1BrownScience & Math

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The spelled-out intro to neural networks and backpropagation: building micrograd Andrej KarpathyProgramming & CS

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24:26

The Beauty of Bézier Curves Freya HolmérProgramming & CS

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CS50x 2024 - Lecture 1 - C CS50Programming & CS

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“Hello, world” from scratch on a 6502 — Part 1 Ben EaterProgramming & CS

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Ruby Conf 12 - Y Not- Adventures in Functional Programming by Jim Weirich ConfreaksProgramming & CS

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CS50x 2024 - Lecture 0 - Scratch CS50Programming & CS

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RailsConf 2014 - All the Little Things by Sandi Metz ConfreaksProgramming & CS

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1:02:13

I-X Seminar: Training large language models in an open & responsible way with Leandro von Werra

I-X

Advanced

A 62-minute video from I-X: “I-X Seminar: Training large language models in an open & responsible way with Leandro von Werra”.

55:42

I-X Seminar: Formulating and Evaluating Language Agents with Shunyu Yao

I-X

Advanced

A 56-minute video from I-X: “I-X Seminar: Formulating and Evaluating Language Agents with Shunyu Yao”.

But what is a neural network? | Deep learning chapter 1

3Blue1Brown

Intro25.1M views

Builds up what a neural network actually is — neurons as numbers, layers, weights and biases — using handwritten-digit recognition as the running example.

Let's build GPT: from scratch, in code, spelled out.

Andrej Karpathy

8.21M views

Building a GPT-style language model from scratch in code, following 'Attention Is All You Need'.

Transformers, the tech behind LLMs | Deep Learning Chapter 5

3Blue1Brown

Intro11.6M views

How transformer models (the 'T' in GPT) turn text into vectors and predict the next token, step by step.

The spelled-out intro to neural networks and backpropagation: building micrograd

Andrej Karpathy

Intro4.41M views

Building micrograd, a tiny autograd engine, to understand backpropagation completely.

24:26

The Beauty of Bézier Curves

Freya Holmér

2.23M views

Freya Holmér builds Bézier curves from linear interpolation up, covering de Casteljau's algorithm, derivatives, arc length and their use in games and graphics.

2:27:41

CS50x 2024 - Lecture 1 - C

CS50

Intro1.41M views

CS50x 2024 lecture 1: an introduction to C — syntax, types, conditionals, loops and compiling.

“Hello, world” from scratch on a 6502 — Part 1

Ben Eater

5.85M views

Building a computer around the 6502 processor on a breadboard and running 'Hello, world'.

Ruby Conf 12 - Y Not- Adventures in Functional Programming by Jim Weirich

Confreaks

65.7K views

Jim Weirich derives the Y combinator live, step by step, using nothing but Ruby lambdas, and along the way teaches the refactorings of lambda calculus.

2:04:55

CS50x 2024 - Lecture 0 - Scratch

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CS50x 2024 lecture 0: how computers represent information, algorithms, and first programs in Scratch.

RailsConf 2014 - All the Little Things by Sandi Metz

Confreaks

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Sandi Metz refactors the notorious Gilded Rose kata live, showing how small, disciplined steps and duplication-over-wrong-abstraction lead to clean object-oriented code.