Bookmarks

George Hotz | Programming | twitchchess | a simple neural chess AI | Part1

Live coding session where George Hotz designs and trains a simple neural-network chess engine, examining model architecture, training loop, and gameplay integration.

Simple Artificial Neural Network entirely in assembly language

Demonstrates building and training a single-layer neural network entirely in x86-64 assembly language, covering forward pass, MSE loss, back-propagation, and low-level numeric routines.

What Matters for Model Merging at Scale?

Technical summary of a current arXiv paper on large-scale model merging, providing up-to-date insights for ML practitioners.

AI for science with Sir Paul Nurse, Demis Hassabis, Jennifer Doudna, and John Jumper

Panel discussion with leading scientists on how AI accelerates scientific discovery; offers strategic and technical perspectives on AI applications in research.

Can Latent Program Networks Solve Abstract Reasoning?

LSTM: The Comeback Story?

Autoencoders | Deep Learning Animated

17.12.2024: Flow-based Models (Part 2)

When AI Is Designed Like A Biological Brain

Dense Associative Memory in Machine Learning

Research talk on Dense Associative Memory networks, exploring high-capacity energy-based models for pattern storage and retrieval.

1 - Introduction

The Most Important Algorithm in Machine Learning

H-Nets - the Past

H-Nets - the Future

Neural Scaling Laws by Data Manifold Dimensions

Continuous Thought Machines

How To Scale

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Greg Yang

Using neural nets to recognize handwritten digits

ai

KAN: Kolmogorov-Arnold Networks

Root Mean Square Layer Normalization

Root Mean Square Layer Normalization

Deep Learning Course

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