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MLST
By and about MLST
MLST: Mechanistic Interpretability - NEEL NANDA (DeepMind)
A deep dive with Neel Nanda on mechanistic interpretability: reverse-engineering neural networks, grokking, superposition, transformer circuits, world models, and why understanding model internals matters for AI safety.
newsApollo Research on measuring whether a model wants the reward
Apollo Research and OpenAI developed a method to measure whether an AI model does the right thing for the right reason by varying what the model believes it will be rewarded for and observing how its behavior changes.
newsAdam Becker: every exponential ends
Astrophysicist Adam Becker tells MLST that Kurzweil's law of accelerating returns rests on cherry-picked data, LLMs are "pocket calculators for language", and the doomers are sincere but wrong — and feeding the same growth story.
newsMLST: AI is learning at the wrong level of abstraction
Physicist Matthieu Wyart argues deep networks succeed because real data has hidden hierarchies—parts within parts—and that predicting latent representations rather than raw tokens could make learning far more sample-efficient.
blogAI Socratic April 2026 — The Era of Mythos
Mythos, Claude Code leak, Anthropic surpass OpenAI on MRR
newsThe Abstraction Fallacy: Can AI Be Conscious?
An argument that computational functionalism commits the "Abstraction Fallacy" by assuming consciousness emerges from abstract computation alone, when physical substrate may be essential to generating rather than merely simulating experience.
blogAI Socratic Jan 2026
Claude Code, Ralph Wiggum, DeepSeek mHC, Platonic Representation Hypothesis and more
newsStanford CME295 Lecture on Transformers & LLMs, plus more videos and pods
Stanford's CME295 course offers a lecture series on transformers and large language models, plus curated videos and podcasts from December and January featuring discussions on AI fundamentals, neuroscience approaches to AI, and reinforcement learning.
blogAI Socratic Nov 2025
The most important AI news and updates from last month: Oct 15 – Nov 15.
newsMLST — AI benchmarks are broken! [Prof Melanie Mitchell]
Melanie Mitchell argues that AI benchmarks fail to measure what matters: whether large language models truly understand or merely exploit statistical patterns.
newsMLST — Google Researcher Shows Life "Emerges from Code"
Google researcher Blaise Agüera y Arcas argues that intelligence and life emerge from the same underlying principles of information and code.
blogAI Socratic July-Sep 2025 Part 1 — The Genie3 Is Out of The Box 🍌
This time around we’ll have 2 events, one in New York, and one for the first time in San Francisco at the Frontier Tower. We’ll discuss the top news and updates from this blog post using the Socratic
newsMLST: DeepMind Genie 3 - Simulate The World
DeepMind's Genie 3 is a general-purpose world model that generates interactive environments in real time at 30fps and 720p, with emergent properties like parallax and the ability to maintain consistent details across several minutes of simulation.