, like a 2020 study about the harms of large language models, co-authored by the leads of Google’s Ethical AI team, Timnit Gebru and Margaret Mitchell.
For some researchers, Dean’s announcement at the quarterly meeting was the first they were hearing about the restrictions on publishing research. But for those working on large language models, a technology core to chatbots, things had gotten stricter since Google executives first issued a “Code Red” to focus on AI in December, after ChatGPT became an instant phenomenon.could require repeated intense reviews with senior staffers, according to one former researcher.
When he uses Google Translate and YouTube, “I already see the volatility and instability that could only be explained by the use of,” these models and data sets, El Mhamdi said. It’s important to rigorously evaluate the technology’s capabilities, he added. Liang recently co-authored a paper examining AI search tools like the new Bing. It found that only about 70 percent of its citations were correct.began buying AI start-ups
Despite these steady advancements, it was ChatGPT — built by the smaller upstart OpenAI — that triggered a wave of broader fascination and excitement in AI. Founded to provide a counterweight to Big Tech companies’ takeover of the field, OpenAI faced less scrutiny than its bigger rivals and was more willing to put its most powerful AI models into the hands of regular people.
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