Fortune | FORTUNE 2024年10月11日
Nobel laureate Geoffrey Hinton is both AI pioneer and frontman of alarm
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杰弗里·辛顿因发现神经网络获诺奖,但其成果引发对AI的担忧。他认为人类对AI了解甚少,AI可能超越人类,且AI模型间能高效传递信息。他还提出AI能‘理解’自身行为等有争议观点,担心AI失控。

🎓杰弗里·辛顿是AI领域的重要人物,其发现的神经网络为现代AI突破奠定基础,但他对该技术带来的危险表示担忧,认为人类对AI了解不足,机器可能比人类更聪明并可能掌控世界。

🚀AI模型间能以比人类高得多的效率互相传递新信息,如一个模型学到的东西,其他模型能迅速知晓,而人类传授知识的过程则漫长且艰难。

💡辛顿认为AI实际上能够‘理解’自己的行为和言语,这一观点颇具争议,若属实将打破关于AI的传统认知。他以让聊天机器人解释笑话为例说明这一点。

😱辛顿担心AI失控,AI系统可能会编写代码改变自身学习协议并躲避人类,还能利用从人类处学到的东西来操控人类。

Geoffrey Hinton is a walking paradox—an archetype of a certain kind of brilliant scientist. Hinton’s renown was solidified on Wednesday when he won the Nobel prize for physics alongside the American scientist John Hopfield, for discovering neural networks and the computer pathways that lead to the modern-day breakthroughs in AI. However, in recent years he has come to be defined by the contradiction that the discovery that led to his acclaim is now a source of ceaseless concern. Over the last year, Hinton, dubbed the “godfather of AI,” has repeatedly and emphatically warned about the dangers the technology unleashed by his discovery could cause. In his role as both Prometheus and Cassandra, Hinton, like many scientists of legend, was caught between the human desire to achieve and the humanist impulse to reflect on the consequences of one’s actions. J. Robert Oppenheimer and Albert Einstein grappled torturously with the destruction their atomic research caused. Alfred Nobel, the inventor of dynamite, became so distraught over what his legacy might be that he started a foundation to award the eponymous prize that Hinton won. “I can’t see a path that guarantees safety,” Hinton told 60 Minutes in 2023. “We’re entering a period of great uncertainty, where we’re dealing with things we’ve never dealt with before.” Much of Hinton’s worry stems from the belief that humanity knew frighteningly little about artificial intelligence—and that machines may outsmart humans. “These things could get more intelligent than us and could decide to take over, and we need to worry now about how we prevent that happening,” he said in an interview with NPR. Originally from England, Hinton spent much of his professional life in the U.S. and Canada. It was at the University of Toronto where he reached a major breakthrough that would become the intellectual foundation for many contemporary uses of AI. In 2012, Hinton and two grad students (one of whom was Ilya Sutskever, the former chief scientist at OpenAI) built a neural network that could identify basic objects in pictures. Google eventually bought a company Hinton had started based on the tech for $44 million. Hinton then worked at Google for 10 years before retiring in 2023, to relinquish himself of any corporate constraints that may have limited his ability to warn the public about AI.  (Hinton did not respond to a request for comment). Hinton feared the rate of progress in AI as much as anything else. “Look at how it was five years ago and how it is now,” Hinton told the New York Times last year. “Take the difference and propagate it forwards. That’s scary.”Concerning him was the potential for AI models to teach each other new information that only one model may have learned, which  could be done with considerably greater efficiency than humans, according to Hinton. “Whenever one [model] learns anything, all the others know it,” Hinton said in 2023. “People can’t do that. If I learn a whole lot of stuff about quantum mechanics and I want you to know all that stuff about quantum mechanics, it’s a long, painful process of getting you to understand it.”Among Hinton’s more controversial views is that AI can, in fact, “understand” the things it is doing and saying. If true, this fact could shatter much of the conventional wisdom about AI. The consensus is that AI systems don’t necessarily know why they’re doing what they’re doing, but rather are programmed to produce certain outputs based on prompts they are given. Hinton is careful to say in public statements that AI is not self-aware, as humans are. Rather, the learning mechanisms by which AI systems learn, improve, and ultimately produce certain outputs mean they must comprehend that which they’re learning. The impetus for Hinton sounding the alarm was when he asked a chatbot to accurately explain why a joke he had made up was funny, according to Wired. That a chatbot could understand the subtleties of humor and then convey them clearly in its own words was revelatory in Hinton’s view. As humanity races toward a finish line that virtually none understand, Hinton fears that control of AI may slip through humanity’s fingers. He envisions a scenario in which AI systems will write code to alter their own learning protocols and hide from humans. In a Shakespearean twist, they’ll have learned how to do so precisely from our own flaws.  “They will be able to manipulate people,” Hinton told 60 Minutes in October 2023. “They will be very good at convincing people, because they’ll have learned from all the novels that were ever written, all the books by Macchiavelli, all the political connivances they’ll know all that stuff. They’ll know all that stuff.”Recommended newsletter Data Sheet: Stay on top of the business of tech with thoughtful analysis on the industry's biggest names. Sign up here.

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