Why Meta’s latest large language model only survived three days online

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The Meta team behind Galactica argues that language models are better than search engines. “We believe this will be the next interface for how humans access scientific knowledge,” the researchers write.

This is because language models can “potentially store, combine, and reason about” information. But that “potentially” is crucial. It’s a coded admission that language models cannot yet do all these things. And they may never be able to.

“Language models are not really knowledgeable beyond their ability to capture patterns of strings of words and spit them out in a probabilistic manner,” says Shah. “It gives a false sense of intelligence.”

Gary Marcus, a cognitive scientist at New York University and a vocal critic of deep learning, gave his view in a Substack post titled “A Few Words About Bullshit,” saying that the ability of large language models to mimic human-written text is nothing more than “a superlative feat of statistics.”

And yet Meta is not the only company championing the idea that language models could replace search engines. For the last couple of years, Google has been promoting its language model PaLM as a way to look up information.

It’s a tantalizing idea. But suggesting that the human-like text such models generate will always contain trustworthy information, as Meta appeared to do in its promotion of Galactica, is reckless and irresponsible. It was an unforced error.

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