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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Further information: Large language model

This section needs to be updated. Please help update this article to reflect recent events or newly available information. (November 2024)

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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  | Ref.

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LLaMA | Meta AI | 7B, 13B, 33B, 65B  | 2048  |  | [6]
Llama 2 | Meta AI | 7B, 13B, 70B  | 4k  | Custom Meta license  | [8][9]
Llama 3.1 | Meta AI | 8B, 70B, 405B  | 128K  | Meta Llama 3 Community License  | [10][11][12]
Llama 3.2 | Meta AI | 1B to 405B  |  | Research-only  | [13]
Mistral 7B | Mistral AI | 7 billion  | 8k  | Apache 2.0 | [14][15]
Mixtral 8x22B | Mistral AI | 8×22B  |  | Apache 2.0 | [13]
GPT-J | EleutherAI | 6 billion  | 2048  | Apache 2.0 | [16]
GPT-NeoX | EleutherAI | 20B  |  | MIT License | [13]
Pythia | EleutherAI | 70 million - 12 billion  |  | Apache 2.0 (Pythia-6.9B only)  | [17][18]
T5 | Google AI | 60 million to 11 billion  |  | Apache 2.0 | [13]
Gemma 2 | Google DeepMind | 2B, 9B, 27B  |  | Apache 2.0 | [13]
OLMo  | Allen Institute for AI | Various  |  | Apache 2.0 | [13]
BLOOM | BigScience | 176 billion  |  | OpenRAIL-M  | [13]
StarCoder2 | BigCode | Various  |  | Apache 2.0 | [13]
Falcon | Technology Innovation Institute | 7B, 40B  |  | Apache 2.0 | [13]
Jamba Series  | AI21 Labs | Mini to Large  |  | Custom  | [13]
Sea-Lion  | AI Singapore | 7B  |  | Custom  | [13]
Qwen Series  | Alibaba Group | 7B  |  | Custom  | [13]
Dolly 2.0 | Databricks | 12B  |  | CC BY-SA 3.0 | [13]
Granite Series  | IBM | 3B, 8B  |  | Apache 2.0 | [13]
Phi-3 Series  | Microsoft | Mini to Medium  |  | MIT License | [13]
NVLM 1.0 Family  | Nvidia | 72B  |  | CC BY-SA 3.0 | [13]
RakutenAI Series  | Rakuten | 7B  |  | Custom  | [13]
Grok-1 | xAI | 314B  |  | Apache 2.0 | [13]

## Text-to-image models

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Further information: Text-to-image model

Comparison of text-to-image models  Model  | Developer  | Parameter count  | Licensing  | Ref.

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Stable Diffusion 3.5 | Stability AI | 2.5B to 8B  | OpenRAIL-M  | [13]
IF  | DeepFloyd | 400M to 4.3B  | Custom  | [13]

## Computer vision models

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Further information: Computer vision

Comparison of computer vision models  Model  | Developer  | Parameter count  | Licensing  | Ref.

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SAM 2.1  | Meta | 38.9M to 224.4M  | Apache 2.0 | [13]
DeepLab  | Google | Not disclosed  | Apache 2.0 | [13]
Florence  | Microsoft | 0.23B, 0.77B  | MIT License | [13]
CLIP  | OpenAI | 400M  | MIT License | [13]

## 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". In Denis Dennehy; Anastasia Griva; Nancy Pouloudi; Yogesh K. Dwivedi; Ilias Pappas; Matti Mäntymäki (eds.). Responsible AI and Analytics for an Ethical and Inclusive Digitized Society. 20th International Federation of Information Processing WG 6.11 Conference on e-Business, e-Services and e-Society, Galway, Ireland, September 1–3, 2021. Lecture Notes in Computer Science. Vol. 12896\. Springer. pp. 629–640. doi:10.1007/978-3-030-85447-8_52. ISBN 978-3-030-85446-1.
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. ^ "Meet Llama 3.1". Llama Meta. 2024-09-09. Retrieved 2024-09-09.
11. ^ "llama 3.1 context window - Google Search". www.google.com. Retrieved 2024-09-09.
12. ^ "llama3/LICENSE at main · meta-llama/llama3". GitHub. Retrieved 2024-09-09.
13. ^ a b c d e f g h i j k l m n o p q r s t u v w x Jason, Perlow (2024-11-06). "The best open-source AI models: All your free-to-use options explained". ZDNET. Archived from the original on 13 November 2024. Retrieved 2024-11-13.
14. ^ "mistralai/Mistral-7B-v0.1 · Hugging Face". huggingface.co. Retrieved 2023-10-03.
15. ^ AI, Mistral (2023-09-27). "Mistral 7B". mistral.ai. Retrieved 2023-10-03.
16. ^ "EleutherAI/gpt-j-6b · Hugging Face". huggingface.co. 2023-05-03. Retrieved 2023-10-03.
17. ^ 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].
18. ^ "EleutherAI/pythia-6.9b · Hugging Face". huggingface.co. 2023-05-03. Retrieved 2023-10-03.

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