Uploaded June 2024 | Updated September 2026, 3 weeks ago
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![Learning To See [Part 1: Introduction]](https://i.ytimg.com/vi/i8D90DkCLhI/mqdefault.jpg "Learning To See [Part 1: Introduction]
In this series, well explore the complex landscape of machine learning and artificial intelligence through one example from the field of computer vision: using a decision tree to count the number of fingers in an image. Its gonna be crazy.
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Supporting Code: https://github.com/stephencwelch/LearningToSee
welchlabs.com
@welchlabs")
![Imaginary Numbers Are Real [Part 8: Math Wizardry]](https://i.ytimg.com/vi/iecUL8_OxrU/mqdefault.jpg "Imaginary Numbers Are Real [Part 8: Math Wizardry]
More information and resources: http://www.welchlabs.com
Imaginary numbers are not some wild invention, they are the deep and natural result of extending our number system. Imaginary numbers are all about the discovery of numbers existing not in one dimension along the number line, but in full two dimensional space. Accepting this not only gives us more rich and complete mathematics, but also unlocks a ridiculous amount of very real, very tangible problems in science and engineering.
Part 1: Introduction
Part 2: A Little History
Part 3: Cardans Problem
Part 4: Bombellis Solution
Part 5: Numbers are Two Dimensional
Part 6: The Complex Plane
Part 7: Complex Multiplication
Part 8: Math Wizardry
Part 9: Closure
Part 10: Complex Functions
Part 11: Wandering in Four Dimensions
Part 12: Riemanns Solution
Part 13: Riemann Surfaces
Want to learn more or teach this series? Check out the Imaginary Numbers are Real Workbook: http://www.welchlabs.com/resources.")
![Yann LeCuns $1B Bet Against LLMs [Part 1]](https://i.ytimg.com/vi/kYkIdXwW2AE/mqdefault.jpg "Yann LeCuns $1B Bet Against LLMs [Part 1]
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Welch Labs Book: https://www.welchlabs.com/resources/ai-book-ezrzm-msrmc
Patreon: https://www.patreon.com/c/welchlabs
Part 2: https://www.youtube.com/watch?v=v_jDvpEGTIg
Sections
0:00 - Intro
2:28 - The Problem with Deep Learning
4:17 - Intelligence is a Cake
5:15 - The Rise of Generative AI
8:00 - Blurry Images
8:54 - HRT is an awesome place to work
11:16 - But why so Blurry?
13:30 - Do our models need to be generative?
15:16 - Siamese Networks
17:53 - Representation Collapse
19:54 - Yann’s Epiphany & Barlow Twins
27:22 - DINO
28:58 - JEPA & World Models
34:09 - But is JEPA good?
36:19 - Welch Labs Book
Special thanks to: Yann LeCun, Stephane Deny, David Fan, Nicolas Ballas
Clip of Yann from 1989: https://www.youtube.com/watch?v=FwFduRA_L6Q
CNN Paper: http://yann.lecun.com/exdb/publis/pdf/lecun-89e.pdf
LeNet-5 paper: http://vision.stanford.edu/cs598_spring07/papers/Lecun98.pdf
Dashcam video
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Image Credits
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V-JEPA2 Robot Arm Videos
https://ai.meta.com/research/vjepa/
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Supporting code: https://github.com/WelchLabs/videos
Created by: Sam Baskin, Pranav Gundu, and Stephen Welch
Content ID: CFAQJOTYQHT7JYIT")
![Learning to See [Part 7: There is no f]](https://i.ytimg.com/vi/klWUOO4sHaA/mqdefault.jpg "Learning to See [Part 7: There is no f]
In this series, well explore the complex landscape of machine learning and artificial intelligence through one example from the field of computer vision: using a decision tree to count the number of fingers in an image. Its gonna be crazy.
Supporting Code: https://github.com/stephencwelch/LearningToSee
welchlabs.com
@welchlabs")
