Meta plans to release a commercial version of its artificial intelligence (AI) model aiming to reach wider usage, according to a Financial Times report.
The report contained details from sources close to Meta, who said that although the company released its own large language mode (LLM) for researchers and academics called LLaMa earlier this year, the new version will be more widely available and can be customized by companies.
This comes as Meta tries to position itself to be competitive with Microsoft-backed ChatGPT creator OpenAI and Google, the current market leaders.
FT’s source, reported to have knowledge of high-level strategy at Meta, said:
“The goal is to diminish the current dominance of OpenAI.”
With the commercial version of LLaMa, startups and businesses will be able to build custom software and applications on top of Meta’s underlying AI technology.
At the moment, all of Meta’s models are free and open-source though two of FT’s sources said the company has been exploring a paid version for enterprise customers. However, it would not be a part of the upcoming release.
The release of the commercial version is expected “imminently,” says the FT source.
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Moreover, Meta has made its LLM models open-source, which means the details of the system’s operations are publicly available. This is not the case with its competition like OpenAI, which keeps its code private to third parties.
FT’s source said:
“Meta realized they were behind on the current AI hype cycle, and this gives them a way to open up the ecosystem and seem like they are doing the right thing, being charitable and giving back to the community.”
Cointelegraph reached out to Meta for additional comments.
These developments come as Meta faces a lawsuit from author Sarah Silverman and two other authors on behalf of a class of copyright owners across the United States, which alleges Meta has committed copyright infringement while training its AI systems.
OpenAI has been hit with a similar class-action lawsuit that alleges the company has committed data theft in the training of its models.
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