From award-winning science writer Anil Ananthaswamy (@anilananth.bsky.social): To learn about the future of computer science, math and AI, read Kevin Hartnett's (@kevinhartnett.bsky.social) THE PROOF IN THE CODE. Available June 9.
Anil Ananthaswamy
@anilananth.bsky.social
Journalist with bylines in Nature, Quanta, Scientific American, New Scientist, and many more; former deputy news editor at New Scientist Author of 4 popular science books, including WHY MACHINES LEARN: The Elegant Math Behind Modern AI; TED speaker
The AI community is pivoting to world models, to overcome the limitations of LLMs. But "world models" have a storied history in psychology and cognitive science. My first in a series exploring world models, for the WHERE MACHINES THINK substack. wheremachinesthink.substack.com/p/the-case-f...
The Case For World Models, Part I: The Neuroscientific Reason
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
wheremachinesthink.substack.com
To understand how the Transformer came to be, we need to understand why ML researchers focused their attention on, well, attention. Part II of the primer on LLMs and Transformers, on RNNs and the Era Before Attention. The WHERE MACHINES THINK Substack. wheremachinesthink.substack.com/p/rnns-and-t...
RNNs and the Era Before Attention: Part II of Primer on LLMs and Transformers
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
wheremachinesthink.substack.com
Transformer-based LLMs are the most significant technology of the past decade. This is the first in a series of posts for the WHERE MACHINES THINK Substack, exploring Transformers/LLMs at various levels of abstraction, digging deeper with each post. wheremachinesthink.substack.com/p/a-primer-o...
A Primer on Large Language Models and Transformers. Part I: A High-Flying Bird's Eye-View
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
wheremachinesthink.substack.com
I'm starting a Substack newsletter, WHERE MACHINES THINK (just imagine scare quotes around the word think, to maintain appropriate skepticism). The welcome post is here: wheremachinesthink.substack.com/p/welcome-to...
Welcome to WHERE MACHINES THINK
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
wheremachinesthink.substack.com
Starting the New Year at my alma mater, IIT-Madras, where I did my BTech decades ago. I've joined @iitmadras.bsky.social as Professor of Practice, Dept. of Data Science & AI. Campus feels the same yet different! Deer, monkeys, banyan trees, they are all there, as are more students, new buildings...
This was excellent, with notably clear explanations. Well done @anilananth.bsky.social
Sean Carroll@seanmcarroll.bsky.social · 8mo agoMindscape 336 | Anil Ananthaswamy @anilananth.bsky.social on the Mathematics of Neural Nets and AI. Everyone is talking about AI these days, why not impress your friends with some math? #MindscapePodcast www.preposterousuniverse.com/podcast/2025...
Mindscape 336 | Anil Ananthaswamy @anilananth.bsky.social on the Mathematics of Neural Nets and AI. Everyone is talking about AI these days, why not impress your friends with some math? #MindscapePodcast www.preposterousuniverse.com/podcast/2025...
An AI model called V-JEPA is capable of “intuiting” the physical properties of the real world, gaining a sense of object permanence, the constancy of shape and color, and the effects of gravity. @anilananth.bsky.social reports: www.quantamagazine.org/how-one-ai-m...
How One AI Model Creates a Physical Intuition of Its Environment | Quanta Magazine
The V-JEPA system uses ordinary videos to understand the physics of the real world.
quantamagazine.org
This book by @anilananth.bsky.social is great — perfect for those, like me, who have an intuitive and geometric grasp of math but unfortunately no formal training. Highly recommended!
A nice article by @anilananth.bsky.social on using AI to explore design spaces, find unexpected solutions, (re)discover symmetries, and propose new relationships featuring @yuqirose.bsky.social @mariokrenn.bsky.social & myself. Note AI ≠ LLMs in this piece. www.quantamagazine.org/ai-comes-up-...
AI Comes Up with Bizarre Physics Experiments. But They Work. | Quanta Magazine
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.”
quantamagazine.org
"AI Comes Up with Bizarre Physics Experiments. But They Work." by @anilananth.bsky.social @quantamagazine.bsky.social: www.quantamagazine.org/ai-comes-up-... Covering our work with Rana Adhikari @ligo.org on discovering GW detectors & work by @yuqirose.bsky.social & @kylecranmer.bsky.social on ...
AI Comes Up with Bizarre Physics Experiments. But They Work. | Quanta Magazine
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.”
quantamagazine.org
Thank you, David
David Abuín Eichinger@davideichinger.bsky.social · last yr.Finished reading @anilananth.bsky.social's book, Why Machines Learn. This was an excellent read. I feel that the context and history for which science develops helps my understanding. His prose and explanations were better than anything else I have yet to encounter in my Computer Science education.
Finished reading @anilananth.bsky.social's book, Why Machines Learn. This was an excellent read. I feel that the context and history for which science develops helps my understanding. His prose and explanations were better than anything else I have yet to encounter in my Computer Science education.
1/4 These days most writers, including me, get asked: "Will you use AI to help you write?" My answer is: No. Not because I'm inherently against the idea, but because it undercuts the very reason I became a writer...
"Why machines learn" by @anilananth.bsky.social is an amazing book that teaches the fundamental math concepts behind machine learning and artificial intelligence. I lost count of the "aha!" moments I experienced while reading this masterpiece. I loved it! #AI #math
When I proposed WHY MACHINES LEARN in Oct 2020, to my then editor Stephen Morrow, @carpenter512.bsky.social, I was sure he'd say no to a book full of math & equations. But he saw something in the proposal that even I hadn't and said yes, and I'm grateful for that! Got to thank him today in person.
I have just started reading this fantastic book by @anilananth.bsky.social. I look forward to diving into the hardcore #math behind machine learning! It will be a challenging journey, but a rewarding one. 🤖
Thank you @ganyet.bsky.social. I love this line about WHY MACHINES LEARN: "This book is like an invitation to enter Mago Pop's workshop to realize that magic doesn't exist: that it's all mathematics, engineering, and a lot, a lot of human intelligence." I had to look up Mago Pop and Sant Jordi :-)
Josep M. Ganyet 🦋@ganyet.bsky.social · last yr.Els llibres q no em compraré a #SantJordi: -Entre el Paradís i l’Apocalipsi @xsalaimartin.bsky.social -Why Machines Learn @anilananth.bsky.social -El món interior @francescseres.bsky.social -Replay @jmechner.bsky.social -Història dels grecs. Indro Montanelli www.viaempresa.cat/opinio/lopin...
The Centrality of Bayes's Theorem for Machine Learning. It’s hard to overstate just how important Bayes’s Theorem — something that Thomas Bayes came up with in the 1700s — is for machine learning. But the theorem challenges our intuitions. Here’s a brief intro: anilananthaswamy.com/why-machines...
The Centrality of Bayes’s Theorem for Machine Learning — Anil Ananthaswamy
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...
anilananthaswamy.com
Came out of my AL/ML bubble to write a 'crisis in cosmology' story, about a new study that uses TRGB stars to scale a new cosmic distance ladder to measure the Hubble constant; the tension persists...for @scientificamerican.bsky.social @leebillings.bsky.social scientificamerican.com/article/the-...
The Hubble Tension Is Becoming a Hubble Crisis
A long-simmering disagreement over the universe’s present-day expansion rate shows no signs of resolution, leaving experts increasingly vexed
scientificamerican.com
"For the first time, we can...get performant neural networks that mimic complex human & animal cognition," said @suryaganguli.bsky.social speaking on the symbiosis of AI & neuroscience at the Simons Institute. "That's remarkable and exciting. Caveats...to follow" simons.berkeley.edu/talks/surya-...
I had a great time talking with @anilananth.bsky.social as part of the Simons Institute Polylogues. We cover universal learning, generalization phenomena, how transformers are both surprisingly general but also limited, and the difference between statistics and ML! www.youtube.com/watch?v=Aja0...
Andrew Gordon Wilson | Polylogues
YouTube video by Simons Institute
youtube.com
I went through my RL bookmarks, because it seems like finally the rest of the world has caught up to my world, I rediscovered this gem 💎 mpatacchiola.github.io/blog/2016/12... although I suspect nobody wants to learn RL this way now 😜
Dissecting Reinforcement Learning-Part.1
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...
mpatacchiola.github.io
Everyone is talking about DeepSeek's impact on industry. But another huge impact is the leveling of playing field between academia and industry: if these efficiency numbers bear out, then academia can both use LLMs and study/research them at scale!
These two books, by @anilananth.bsky.social and @tomchivers.bsky.social, are the first two books in a very long time that I read in their entirety without significant pause or other diversion along the way. I cannot recommend them enough! #booksky #dataSkyence
As always, @rao2z.bsky.social has a way with words and speaks his mind in this Machine Learning Street Talk episode: "We should be looking for secrets of Nature, because Nature won't tell us. But we are now looking for secrets of OpenAI." youtube.com/clip/UgkxCH1...
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This lecture is primarily about how animal brains have evolved, but in so doing Paul Cisek helps illuminate why artificial intelligence based on large-language models is fundamentally insufficent in reaching anything resembling human intelligence (perhaps even lampray intelligence).
Kevin Mitchell@wiringthebrain.bsky.social · 2y agoRethinking Brain Mechanisms in the Light of Evolution with Paul Cisek youtu.be/CnT7jaQX4X8?... - if you want to understand what brains are for (and their functional organisation), this is the way... 👍👏