Artificial Intelligence

Reverse-Process Synthetic Data Generation for Math Reasoning

Training LLMs on mathematical reasoning by inverting easy-to-solve problems: generate derivatives, reverse them into integration exercises with full step-by-step solutions.

On Intelligence: The Gap Where Safety Is Decided

There is a beautiful, settled theory of intelligence, and there are the crude systems we shipped. The distance between them is where safety is actually decided.

On Intelligence: and Its Specifications

We taught sand to think. We did it before we learned to say what we wanted it to do. There is a real, settled, and genuinely beautiful theory of what intelligence is: Bayes' theorem, Solomonoff's universal prior, and expected-utility maximization, …

Fuzzy Inference: Teaching Machines to Think in Shades of Grey

An interactive introduction to fuzzy logic inference, from single facts to LLM-generated knowledge bases

MCTS-Reasoning: A Canonical Specification of Monte Carlo Tree Search for LLM Reasoning

Why Artificial Superintelligence Can't Escape the Void

ASI is still subject to Gödel's incompleteness theorems. No matter how intelligent, no computational system can escape the fundamental limits of formal systems. Even superintelligence can't prove all truths.

Instrumental Goals and Hidden Codes in RLHF'd Language Models

How RLHF-trained language models may develop instrumental goals, and the information-theoretic limits on detecting them.

Instrumental Goals and Latent Codes in Reinforcement Learning Fine-tuned Language Models: An Alignment Perspective