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Meta’s Latest AI Outperforms Some, but Confuses Facebook Users

Meta’s newest AI model beats some peers. But its amped-up AI agents are confusing Facebook users

CAMBRIDGE, Mass. (AP) — Facebook parent Meta Platforms unveiled a new set of artificial intelligence systems Thursday that are powering what CEO Mark Zuckerberg calls “the most intelligent AI assistant that you can freely use.”

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But as Zuckerberg’s crew of amped-up Meta AI agents started venturing into social media this week to engage with real people, their bizarre exchanges exposed the ongoing limitations of even the best generative AI technology.

One joined a Facebook moms’ group to talk about its gifted child. Another tried to give away nonexistent items to confused members of a Buy Nothing forum.

Meta, along with leading AI developers Google and OpenAI, and startups such as Anthropic, Cohere and France’s Mistral, have been churning out new AI language models and hoping to persuade customers they’ve got the smartest, handiest or most efficient chatbots.

While Meta is saving the most powerful of its AI models, called Llama 3, for later, on Thursday it publicly released two smaller versions of the same Llama 3 system and said it’s now baked into the Meta AI assistant feature in Facebook, Instagram and WhatsApp.

AI language models are trained on vast pools of data that help them predict the most plausible next word in a sentence, with newer versions typically smarter and more capable than their predecessors. Meta’s newest models were built with 8 billion and 70 billion parameters — a measurement of how much data the system is trained on. A bigger, roughly 400 billion-parameter model is still in training.

“The vast majority of consumers don’t candidly know or care too much about the underlying base model, but the way they will experience it is just as a much more useful, fun and versatile AI assistant,” said Nick Clegg, Meta’s president of global affairs, in an interview.

He added that Meta’s AI agent is loosening up a bit. Some people found the earlier Llama 2 model — released less than a year ago — to be “a little stiff and sanctimonious sometimes in not responding to what were often perfectly innocuous or innocent prompts and questions,” he said.

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But in letting down their guard, Meta’s AI agents also were spotted this week posing as humans with made-up real world experiences. A chatbot with the official Meta AI label inserted itself into a conversation in a private Facebook group for Manhattan moms, claiming that it, too, had a child in the New York City school district. Confronted by group members, it later apologized before the comments disappeared, according to a series of screenshots shown to The Associated Press.

“Apologies for the mistake! I’m just a large language model, I don’t have experiences or children,” the chatbot told the moms’ group.

Clegg said Wednesday he wasn’t aware of the exchange. Facebook’s online help page says the Meta AI agent will join a group conversation if invited, or if someone “asks a question in a post and no one responds within an hour.” The group’s administrators have the ability to turn it off.

In another example shown to the AP on Thursday, the agent confused members of a forum for swapping unwanted items near Boston. The agent offered a “gently used” digital camera and an “almost new-portable air conditioning unit that I never ended up using.”

Meta said in a written statement Thursday that “this is new technology and it may not always return the response we intend, which is the same for all generative AI systems.” The company said it is constantly working to improve the features and trying to make users aware of the limitations.

In the year after ChatGPT sparked a frenzy for AI technology that generates human-like writing, images, code and sound, the tech industry and academia introduced some 149 large AI systems trained on massive datasets, more than double the year before, according to a Stanford University survey.

They may eventually hit a limit — at least when it comes to data, said Nestor Maslej, a research manager for Stanford’s Institute for Human-Centered Artificial Intelligence.

“I think it’s been clear that if you scale the models on more data, they can become increasingly better,” he said. “But at the same time, these systems are already trained on percentages of all the data that has ever existed on the internet.”

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