Elon Musk's Wikipedia rival Grokipedia got off to a "rocky start" in its public debut, but Wikipedia founder Jimmy Wales didn't even have to take a look at the AI's output to know what he expected.
"I'm not optimistic he will create anything very useful right now," Wales said at the CNBC Technology Executive Council Summit in New York City on Tuesday.
Wales had plenty of choice words for Musk, notably in response to allegations that there is "woke bias" on Wikipedia. "He is mistaken about that," Wales said. "His complaints about Wiki are that we focus on mainstream sources and I am completely unapologetic about that. We don't treat random crackpots the same as The New England Journal of Medicine and that doesn't make us woke," he said at the CNBC event. "It's a paradox. We are so radical we quote The New York Times."
"I haven't had the time to really look at Grokipedia, and it will be interesting to see, but apparently it has a lot of praise about the genius of Elon Musk in it. So I'm sure that's completely neutral," he added.
Wales' digs at Grokipedia — which has its own wiki page — were less about any ongoing spat with Musk and more about his significant concerns about the efforts by all large language models to create a trusted online source of information.
"The LLMs he is using to write it are going to make massive errors," Wales said. "We know ChatGPT and all the other LLMs are not good enough to write wiki entries."
Wales gave several real-world examples of why he doesn't have faith in LLMs to recreate what Wikipedia's global community has built over decades at a fraction of the cost — he estimated the organization's hard technology costs as $175 million annually versus the tens of billions of dollars big tech companies are constantly pouring into AI efforts, and by one Wall Street estimate, a total of $550 billion in AI spending expected by the so-called hyperscalers next year.
One example Wales cited of LLM's inaccuracy relates to his wife. Wales said he often asks new chatbot models to research obscure topics as a test of their abilities, and asking who his wife is, a "not famous but known" person, he said, who worked in British politics, always results in a "plausible but wrong" answer. Any time you ask an LLM to dig deep, Wales added, "it's a mess."
He also gave the example of a German Wiki community member who wrote a program to verify the ISBN numbers of books cited, and was able to trace notable mistakes to one person. That person ultimately confessed they had used ChatGPT to find citations for text references and the LLM "just very happily makes up books for you," Wales said.