Open-source artificial intelligence

Concept of open applied to AI

Open-source artificial intelligence is the application of open-source practices to the development of artificial intelligence resources.

Many open-source artificial intelligence products are variations of other existing tools and technologies which have been shared as open-source software by large companies.[1]

Companies often develop closed products in an attempt to keep a competitive advantage in the marketplace.[2] A journalist for Wired explored the idea that open-source AI tools have a development advantage over closed products, and could overtake them in the marketplace.[2]

Popular open-source artificial intelligence project categories include large language models, machine translation tools, and chatbots.[3]

For software developers to produce open-source artificial intelligence resources, they must trust the various other open-source software components they use in its development.[4][5]

## Large language models

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### LLaMA

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Main article: LLaMA

LLaMA is a family of large language models released by Meta AI starting in February 2023.[6] Meta claims these models are open-source software, but the Open Source Initiative disputes this claim, arguing that "Meta's license for the LLaMa models and code does not meet this standard; specifically, it puts restrictions on commercial use for some users (paragraph 2) and also restricts the use of the model and software for certain purposes (the Acceptable Use Policy)."[7]

Comparison of open-source large language foundation models  Model  | Developer  | Parameter count  | Context window  | Licensing

|
|
|
|

LLaMA[6] | Meta AI | 7B, 13B, 33B, 65B  | 2048  | ——
LLaMA 2[8][9] | Meta AI  | 7B, 13B, 70B  | 4k  | Custom Meta license
Mistral 7B[10] | Mistral AI | 7 billion  | 8k[11] | Apache 2.0
GPT-J[12] | EleutherAI | 6 billion  | 2048  | Apache 2.0
Pythia[13] | EluetherAI  | 70 million - 12 billion  | ——  | Apache 2.0 (Pythia-6.9B only)[14]

## References

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1. ^ Heaven, Will Douglas (May 12, 2023). "The open-source AI boom is built on Big Tech's handouts. How long will it last?". MIT Technology Review.
2. ^ a b Solaiman, Irene (May 24, 2023). "Generative AI Systems Aren't Just Open or Closed Source". Wired.
3. ^ Castelvecchi, Davide (29 June 2023). "Open-source AI chatbots are booming — what does this mean for researchers?". Nature. 618 (7967): 891–892. doi:10.1038/d41586-023-01970-6.
4. ^ Thummadi, Babu Veeresh (2021). "Artificial Intelligence (AI) Capabilities, Trust and Open Source Software Team Performance". Lecture Notes in Computer Science. Vol. 12896\. pp. 629–640. doi:10.1007/978-3-030-85447-8_52. ISBN 978-3-030-85446-1. `{{cite book}}`: `|journal=` ignored (help); Missing or empty `|title=` (help)
5. ^ Mitchell, James (2023-10-22). "How to Create Artificial intelligence Software". AI Software Developers. Retrieved 2024-03-31.
6. ^ a b "Introducing LLaMA: A foundational, 65-billion-parameter language model". 2023-09-11. Archived from the original on 2023-09-11. Retrieved 2023-10-03.
7. ^ "Meta's LLaMa 2 license is not Open Source".
8. ^ "meta-llama/Llama-2-70b-chat-hf · Hugging Face". huggingface.co. Retrieved 2023-10-03.
9. ^ "Llama 2 - Meta AI". ai.meta.com. Retrieved 2023-10-03.
10. ^ "mistralai/Mistral-7B-v0.1 · Hugging Face". huggingface.co. Retrieved 2023-10-03.
11. ^ AI, Mistral (2023-09-27). "Mistral 7B". mistral.ai. Retrieved 2023-10-03.
12. ^ "EleutherAI/gpt-j-6b · Hugging Face". huggingface.co. 2023-05-03. Retrieved 2023-10-03.
13. ^ Biderman, Stella; Schoelkopf, Hailey; Anthony, Quentin; Bradley, Herbie; O'Brien, Kyle; Hallahan, Eric; Mohammad Aflah Khan; Purohit, Shivanshu; USVSN Sai Prashanth; Raff, Edward; Skowron, Aviya; Sutawika, Lintang; Oskar van der Wal (2023-10-03). "[2304.01373] Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling". arXiv:2304.01373 [cs.CL].
14. ^ "EleutherAI/pythia-6.9b · Hugging Face". huggingface.co. 2023-05-03. Retrieved 2023-10-03.