Meta set to release ChatGPT competitor

Facebook parent company Meta is set to release a commercial version of its artificial intelligence model which startups and businesses can tap to build custom software on the technology.

Customised software is software that is specially developed for some specific organisation or other user. It can be contrasted with the use of software packages developed for the mass market.

According to Meta, the software can create text, images and code, which is powered by large language models (LLMs) that are trained on huge amounts of data, requiring vast computing power.

This move will put Meta in competition with Microsoft-backed OpenAI and Google, which are currently leading the race in the generative AI market.

The Facebook parent company, according to Financial Times released its own language model, known as LLaMA, to researchers and academics earlier this year. The new version will be more widely available and customisable by companies.

Yann LeCun, vice president and chief AI scientist at Meta during a recent conference in Aix-en-Province, said the new innovation will change the phase of AI completely.

“The competitive landscape of AI is going to completely change in the coming months, in the coming weeks maybe, when there will be open source platforms that are actually as good as the ones that are not,” he said.

According to sources, Meta has been working on AI research and development for more than a decade but has appeared to be on the back foot after OpenAI’s ChatGPT, a conversational chatbot, was released in November, spurring other Big Tech groups to launch similar products.

Meanwhile, the Financial Times quoting a source close to Mets said, “The goal is to diminish the current dominance of OpenAI.”

Meta set up a generative AI unit earlier this year led by Chris Cox. Joelle Pineau, Meta’s vice president said that Cox’s team straddled the research side of AI but also product development, as it was “creating totally new businesses.”

The benefit of open-source models includes a higher take-up by users who input more data for the AI to process. The more data an LLM has, the more powerful its capabilities become.