GPT4All: Limitations and References

Table of Links

Abstract and 1. Introduction

2 The Original GPT4All Model

2.1 Data Collection and Curation

2.2 Model Training, 2.3 Model Access and 2.4 Model Evaluation

3 From a Model to an Ecosystem

3.1 GPT4All-J: Repository Growth and the implications of the LLaMA License

3.2 GPT4All-Snoozy: the Emergence of the GPT4All Ecosystem

3.3 The Current State of GPT4All

4 The Future of GPT4All

Limitations and References

Limitations

By enabling access to large language models, the GPT4All project also inherits many of the ethical concerns associated with generative models. Principal among these is the concern that unfiltered language models like GPT4All enable malicious users to generate content that could be harmful and dangerous (e.g., instructions on building bioweapons). While we recognize this risk, we also acknowledge the risk of concentrating this technology in the hands of a limited number of increasingly secretive research groups. We believe that the risk of focusing on the benefits of language model technology significantly outweighs the risk of misuse, and hence we prefer to make the technology as widely available as possible.

Finally, we realize the challenge in assigning credit for large-scale open source initiatives. We make a first attempt at fair credit assignment by explicitly including the GPT4All open source developers as authors on this work, but recognize that this is insufficient fully characterize everyone involved in the GPT4All effort. Furthermore, we acknowledge the difficulty in citing open source works that do not necessarily have standardized citations, and do our best in this paper to provide URLs to projects whenever possible. We encourage further research in the area of open source credit assignment, and hope to be able to support some of this research ourselves in the future.

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