Meta’s AI research head wants open source licensing to change

In July, Meta’s Fundamental AI Research (FAIR) center released its large language model Llama 2 relatively openly and for free, a stark contrast to its biggest competitors. But in the world of open-source software, some still see the company’s openness with an asterisk.

While Meta’s license makes Llama 2 free for many, it’s still a limited license that doesn’t meet all the requirements of the Open Source Initiative (OSI). As outlined in the OSI’s Open Source Definition, open source is more than just sharing some code or research. To be truly open source is to offer free redistribution, access to the source code, allow modifications, and must not be tied to a specific product. Meta’s limits include requiring a license fee for any developers with more than 700 million daily users and disallowing other models from training on Llama. IEEE Spectrum wrote researchers from Radboud University in the Netherlands claimed Meta saying Llama 2 is open-source “is misleading,” and social media posts questioned how Meta could claim it as open-source. 

FAIR lead and Meta vice president for AI research Joelle Pineau is aware of the limits of Meta’s openness. But, she argues that it’s a necessary balance between the benefits of information-sharing and the potential costs to Meta’s business. In an interview with The Verge, Pineau says that even Meta’s limited approach to openness has helped its researchers take a more focused approach to its AI projects. 

“Being open has internally changed how we approach research, and it drives us not to release anything that isn’t very safe and be responsible at the onset,” Pineau says. 

Meta’s AI division has worked on more open projects before

One of Meta’s biggest open-source initiatives is PyTorch, a machine learning coding language used to develop generative AI models. The company released PyTorch to the open source community in 2016, and outside developers have been iterating on it ever since. Pineau hopes to foster the same excitement around its generative AI models, particularly since PyTorch “has improved so much” since being open-sourced. 

She says that choosing how much to release depends on a few factors, including how safe the code will be in the hands of outside developers. 

“How we choose to release our research or the code depends on the maturity of the work,” Pineau says. “When we don’t know what the harm could be or what the safety of it is, we’re careful about releasing the research to a smaller group.” 

It is important to FAIR that “a diverse set of researchers” gets to see their research for better feedback. It’s this same ethos that Meta used when it announced Llama 2’s release, creating the narrative that the company believes innovation in generative…