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Madison Mills (AXIOS): AI godfather Yann LeCun's advice on college, work and breaking through AI hype

AXIOS (Madison Mills) - AI godfather Yann LeCun's advice on college, work and breaking through AI hype

If AI doomerism is freaking you out, consider the advice of Yann LeCun, former Meta AI chief and a scientist with over 40 years of experience in the field. Why it matters: As CEOs warn of job loss and existential risk, Turing award-winning LeCun argues the real danger is making life-altering decisions based on exaggerated claims about the future of the technology. The big picture: The leading AI scientist warns that doom narratives are already harming teens' mental health, calling extinction fears "extremely destructive" — and wrong. - "A small proportion of high school students are actually kind of depressed because they've read that AI is not only going to take a job, but basically cause human extinction," he said. "They take that seriously and it has a profound effect on their psychology." No, AI won't deplete 20% of jobs, and yes, you still need to go to college, LeCun argues. Here's more advice from LeCun, executive chairman of AMI Labs: 1. Don't listen to CEOs - It can be hard to keep up with the AI race when CEOs of the frontier labs keep saying each model is more powerful and potentially world-ending than the last. LeCun tells Axios: ignore them. - "Don't listen to CEOs… they have a vested interest in propping up the power of the products they sell," he says, adding that AI CEOs are also not the ones to listen to about the impact of AI on labor. That's a job for economists. - AI tools are powerful, but "still not very good at reasoning," and "there is a long history... of researchers in AI having a widely optimistic view of when machines will become more intelligent than humans...this is not going to take us to human level AI for quite a while." - LeCun's view is reflected in work as executive chairman of AMI Labs, where he's building AI systems aimed at overcoming the reasoning limits he sees in today's models. 2.

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