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System Two: The Normal Computing Blog
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: Normal Computing’s library for Uncertainty-Aware LLMs
engineering
research
Scalable uncertainty quantification with PyTorch and Bayes
Apr 16, 2024
Sam Duffield
A First Demonstration of Thermodynamic Matrix Inversion
computing
research
We report on the first-ever experiment towards thermodynamic artificial intelligence: solving matrix inversion problems by allowing a system of coupled electrical oscillators to thermally equilibrate with its environment.
Nov 9, 2023
Denis Melanson, Max Hunter Gordon, Maxwell Aifer, Kaelan Donatella, Thomas Ahle, Gavin Crooks and Patrick J. Coles
Developing Advanced Reasoning and Planning Algorithms with LLMs
research
In this post we introduce Branches, our tool for prototyping and visualizing advanced LLM reasoning and planning algorithms. We apply Branches to the problem of generating Python code for HumanEval.
Nov 5, 2023
Arun Patro, Rami Sbahi, and Thomas Ahle
Infinite Context LLMs: Going Beyond RAG with Extended Minds
research
In this blog we discuss how the transformer architecture naturally extends over external memories, and share empirical results which leverage this capability to succeed where RAG has struggled. These methods are innate (don’t require fine tuning) and outperform popular retrieval augmented generation methods.
Oct 24, 2023
Phoebe Klett, Thomas Ahle
Explainable Language Models: Existing and Novel Approaches
research
We review key aspects of explainability for language models and introduce some Normal innovations.
Oct 20, 2023
Sam Duffield, Arun Patro, and Phoebe Klett
Eliminating hallucinations (fast!) in Large Language Models with Finite State Machines
engineering
In this blog, we introduce our method for regex-guided generation implemented in Outlines
Aug 4, 2023
Rémi Louf, Phoebe Klett, and Dan Simpson
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