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Sources say Meta disbanded the protein folding team and switched to business artificial intelligence.

2025-01-22 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > IT Information >

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Shulou(Shulou.com)11/24 Report--

CTOnews.com, August 8 (Xinhua)-- Social media giant Meta, formerly known as Facebook, has disbanded a team of scientists who have created more than 600 million protein structure databases using artificial intelligence, the Financial Times reported. The move shows that Meta is moving from purely scientific projects to developing revenue-generating artificial intelligence products.

The team, called ESMFold, previously developed a large language model that can process vast amounts of biological data to predict the structure of proteins, a project that has been praised by experts in the field of drug development and new therapies. However, ESMFold was disbanded this spring as part of company-wide layoffs, according to three people familiar with the matter.

CTOnews.com has previously reported that Mark Zuckerberg, Meta's chief executive, has stressed that this year is the company's "year of efficiency" and has restructured and laid off staff to improve profitability and growth. Meta was an early investor in artificial intelligence, setting up its basic artificial intelligence research (Fair) laboratory in 2013 and hiring top scholars in the field. However, Meta lags behind competitors such as OpenAI, Microsoft and Google in the development of generative artificial intelligence.

As part of its new direction, Meta has set up a generative artificial intelligence team led by Chris Cox, its product director, which includes former members of Fair, and Meta plans to launch a series of similar chatbots in September. Meta is still committed to exploratory research through Fair, but is now focused on integrating its research into the product.

The ESMFold project has previously created an open source database to help scientists easily access specific protein structures relevant to their work. However, there are concerns about whether Meta will continue to bear the cost of maintaining the database and another service that runs the ESM algorithm on new protein sequences, an uncertainty that raises questions about the long-term availability of these resources in the research community.

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