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Byte Models: Simulating the Digital World with bGPT

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Inspired by the success of next token prediction\nin natural language processing, we introduce bGPT, a model with next byte\nprediction to simulate the digital world. bGPT matches specialized models in\nperformance across various modalities, including text, audio, and images, and\noffers new possibilities for predicting, simulating, and diagnosing algorithm\nor hardware behaviour. It has almost flawlessly replicated the process of\nconverting symbolic music data, achieving a low error rate of 0.0011 bits per\nbyte in converting ABC notation to MIDI format. In addition, bGPT demonstrates\nexceptional capabilities in simulating CPU behaviour, with an accuracy\nexceeding 99.99% in executing various operations. 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Papers
arxiv:2402.19155

Beyond Language Models: Byte Models are Digital World Simulators

Published on Feb 29, 2024
· Submitted by AK on Mar 1, 2024
#3 Paper of the day
Authors:
,
Xu Tan ,
,
,

Abstract

bGPT, a model using next byte prediction, simulates various digital processes with high accuracy, matching specialized models in performance and offering insights into algorithm and hardware behavior.

AI-generated summary

Traditional deep learning often overlooks bytes, the basic units of the digital world, where all forms of information and operations are encoded and manipulated in binary format. Inspired by the success of next token prediction in natural language processing, we introduce bGPT, a model with next byte prediction to simulate the digital world. bGPT matches specialized models in performance across various modalities, including text, audio, and images, and offers new possibilities for predicting, simulating, and diagnosing algorithm or hardware behaviour. It has almost flawlessly replicated the process of converting symbolic music data, achieving a low error rate of 0.0011 bits per byte in converting ABC notation to MIDI format. In addition, bGPT demonstrates exceptional capabilities in simulating CPU behaviour, with an accuracy exceeding 99.99% in executing various operations. Leveraging next byte prediction, models like bGPT can directly learn from vast binary data, effectively simulating the intricate patterns of the digital world.

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