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Two papers in Nature show major advancements in the effort to translate brain activity into speech. Our reporter Zeyi Yang looks at what this means for Chinese internet users. ( MIT Technology Review)īrain implants helped create a digital avatar of a stroke survivor’s face Nobody knows how language models work: “I think that the fundamental problem is that we keep focusing on test results rather than how you pass the tests,” says Tomer Ullman, a cognitive scientist at Harvard University.Ĭhinese ChatGPT alternatives just got approved for the general publicīaidu, one of China’s leading artificial-intelligence companies, has announced it will open up access to its ChatGPT-like large language model, Ernie Bot, to the general public. Lessons from the animal kingdom: Lucy Cheke, a psychologist at the University of Cambridge, UK, suggests AI researchers could adapt techniques used to study animals, which have been developed to avoid jumping to conclusions based on human bias. But that’s not true: human psychology tests rely on many assumptions that may not hold for large language models,” says Laura Weidinger, a senior research scientist at Google DeepMind. “This is the sort of thing that children can easily solve,” says Taylor Webb, one of the researchers.ĪI language models are not humans: “With large language models producing text that seems so human-like, it is tempting to assume that human psychology tests will be useful for evaluating them. GPT-3 proposed elaborate but mechanically nonsensical solutions. The idea is that the story hints at ways to solve the problem.
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GPT-3: Researchers at the University of California, Los Angeles, gave GPT-3 a story about a magical genie transferring jewels between two bottles and then asked it how to transfer gumballs from one bowl to another, using objects such as a posterboard and a cardboard tube.
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