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Check out the (early) project and source code on GitHub.
This paper introduces a methodology for generating high-quality, diverse training data for Language Models (LMs) in complex problem-solving domains. Our approach, termed …
In The Policy, SIGMA doesn’t work like most modern AI systems. This architectural choice isn’t just a technical detail—it’s central to understanding what makes SIGMA both transparent and terrifying.
A logic programming system that alternates between wake and sleep phases—using LLMs for knowledge generation during wake, and compression-based learning during sleep.
A novel approach that learns fuzzy membership functions and inference rules automatically through gradient descent on soft circuits.
Applying Monte Carlo Tree Search to large language model reasoning with a rigorous formal specification.
Using Fisher information and information geometry for optimization problems.
A minimal implementation of automatic differentiation for educational purposes.
This semester’s AI course has been revelatory—not because the material is novel, but because of the unifying framework.
The organizing principle: intelligence is utility maximization under uncertainty.
This simple idea connects everything from …
This blog post is from a chat I had with a ChatGPT, which can be found here and here.
I’m not sure if this is a good blog post, but I’m posting it anyway. It’s remarkable how quickly you can slap stuff like this together, and …
I finally noticed ChatGPT this week. Everyone’s been talking about it for weeks, but I was buried in cancer treatment, chemo recovery, surgery prep, and thesis work on Weibull distributions.
When I finally tried it, my reaction wasn’t …