Anthropomorphizing aside, should we be legitimately concerned over the “emergence” of unforeseen capabilities in groups of interacting agents?

Fei-Fei Li, Yann LeCun, Demis Hassabis and others are pushing for AIs that learn world models, to plan & predict accurately. Neuroscientists have known for decades that our brains must be doing this

Well before attention became a thing, deep learning researchers were focused on recurrent neural networks for processing sequences—but there was an elephant in the room, a huge bottleneck

Transformer-based LLMs are the most significant technology of the past decade. This is first in a series of posts exploring Transformers at various levels of abstraction, digging deeper with each post

Exploring and understanding the mathematical spaces that enable artificial (and maybe natural) intelligence. Essays and analyses at the intersection of machine learning, neuroscience and physics

The V-JEPA system uses ordinary videos to understand the physics of the real world.

Artificial intelligence software is designing novel experimental protocols that improve upon the work of human physicists, although the humans are still “doing a lot of baby-sitting.”

Artificial intelligence software is designing novel experimental protocols that improve upon the work of human physicists, although the humans are still “doing a lot of baby-sitting.”

It’s hard to overstate just how important Bayes’s Theorem — something that Thomas Bayes, English minister and mathematician, came up with in the 1700s — is for making sense of machine learning. Bu...

A long-simmering disagreement over the universe’s present-day expansion rate shows no signs of resolution, leaving experts increasingly vexed

YouTube video by Simons Institute

Explaining the basic ideas behind reinforcement learning. In particular, Markov Decision Process, Bellman equation, Value iteration and Policy Iteration algorithms, policy iteration through linear alg...

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If you feel overwhelmed by the jargon of machine learning and wonder how it all ties together, you aren’t alone. Training vs test data, supervised vs unsupervised vs self-supervised learning...

Linear Algebra , Calculus, and Probability & Statistics often get mentioned as the minimum math you need to start on your machine learning journey. But why these? Here’s an intuition for why: ...

A rich, narrative explanation of the mathematics that has brought us machine learning and the ongoing explosion of artificial intelligence. Machine learning systems are making life-altering decisions for us: approving mortgage loans, determining whether a tumor is cancerous, or deciding if someone gets bail. They now influence developments and discoveries in chemistry, biology, and physics—the study of genomes, extrasolar planets, even the intricacies of quantum systems. 

“Through Two Doors at Once  offers beginners the tools they need to seriously engage with the philosophical questions that likely drew them to quantum mechanics.” — Science ( full review here ...

A rich, narrative explanation of the mathematics that has brought us machine learning and the ongoing explosion of artificial intelligence Machine learning systems are making life-altering decisions...