Friday Seminar Series- Gillian Hadfield: AI Alignment and Human Normativity

About this video

Editorial review · 85% confidence

Round-15 hunt: picked; source: deeper uploads from a strong round 1-9 channel; channel already live on Lumen; strict per-title check + final strict pass; title rules; oEmbed verified.

A 51-minute video from Vector Institute: “Friday Seminar Series- Gillian Hadfield: AI Alignment and Human Normativity”.

Programming & CS

Video by Vector Institute, played through YouTube's embedded player.

56:58

April 24 Visitor Talk: Natural Language Processing for Real World Evidence Generation Vector InstituteProgramming & CS

19:35

VectorLM Optimizing LLM Workloads on Vector Compute - Vector's NLP Workshop Vector InstituteProgramming & CS

Advanced

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

Intro25.1M views

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

Intro4.41M views

Let's build GPT: from scratch, in code, spelled out.Andrej KarpathyProgramming & CS

8.21M views

Transformers, the tech behind LLMs | Deep Learning Chapter 5 3Blue1BrownProgramming & CS

Intro11.6M views

24:26

The Beauty of Bézier Curves Freya HolmérProgramming & CS

2.23M views

2:27:41

CS50x 2024 - Lecture 1 - C CS50Programming & CS

Intro1.41M views

2:04:55

CS50x 2024 - Lecture 0 - Scratch CS50Programming & CS

Intro2.2M views

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

5.85M views

15:51

How semiconductors work Ben EaterEngineering

488K views

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

65.7K views

56:58

April 24 Visitor Talk: Natural Language Processing for Real World Evidence Generation

Vector Institute

A 57-minute video from Vector Institute: “April 24 Visitor Talk: Natural Language Processing for Real World Evidence Generation”.

19:35

VectorLM Optimizing LLM Workloads on Vector Compute - Vector's NLP Workshop

Vector Institute

Advanced

A 20-minute video from Vector Institute: “VectorLM Optimizing LLM Workloads on Vector Compute - Vector's NLP Workshop”.

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.

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.

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.

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.

2:04:55

CS50x 2024 - Lecture 0 - Scratch

CS50

Intro2.2M views

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

“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'.

15:51

How semiconductors work

Ben Eater

488K views

How semiconductors work: doping, P-type and N-type silicon and the PN junction.

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.