5.19.2025
Prototype Computer Uses Noise to Its Advantage

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3.27.2025
ChatGPT's Hunger for Energy Could Trigger a GPU Revolution

With AI projects booming and the physical limits of silicon looming, some startups are challenging Nvidia's dominance and say it’s time to reinvent the computer chip entirely.

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12.23.2024
How to fix computing's AI energy problem: run everything backwards

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10.31.2024
Normal Computing Selected for ARIA's £50M Scaling Compute Programme to Revolutionize AI Hardware Costs

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5.22.2024
Introducing Fuji-Web

Fuji-Web is an intelligent AI partner that understands the user’s intent, navigates websites autonomously, and executes tasks on the user’s behalf while explaining each action step.

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4.16.2024
posteriors: Normal Computing’s library for Uncertainty-Aware LLMs

Online learning and hallucination detection are understood as frontier problems in AI and with LLMs. posteriors is a new open source Python library from Normal Computing that provides tools for uncertainty quantification and Bayesian computation using PyTorch and its functional API.

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1.23.2024
Normal Computing Unveils the First-ever Thermodynamic Computer

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1.16.2024
First 'thermodynamic computer' uses random noise to calculate

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11.9.2023
A First Demonstration of Thermodynamic Matrix Inversion

Thermodynamic computing offers a natural approach for fast, energy-efficient computations. 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.

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11.5.2023
Developing Advanced Reasoning and Planning Algorithms with LLMs

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.

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10.24.2023
Supersizing Transformers: Beyond RAG with Extended minds for LLMs

In this blog we discuss how the transformer architecture naturally extends over external memories, and share empirical results which leverage this capability. These methods are innate (don't require fine tuning) and outperform popular retrieval augmented generation methods.

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10.20.2023
Explainable Language Models: Existing and Novel Approaches

We review key aspects of explainability for language models and introduce some Normal innovations.

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9.11.2023
Computers that use heat instead of electricity could run efficient AI

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8.4.2023
Eliminating hallucinations (fast!) in Large Language Models with Finite State Machines

In this blog, we introduce our method for regex-guided generation implemented in Outlines

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6.13.2023
Normal Computing Raises $8.5M in Seed Funding to Enable AI Solutions For Critical Enterprise and Government Applications

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