Meta's AI guru LeCun: Most of today's AI approaches will never lead to true intelligence

"I think AI systems need to be able to reason," says Yann LeCun, Meta's chief AI scientist. Today's popular AI approaches such as Transformers, many of which build upon his own pioneering work in the field, will not be sufficient. "You have to take a step back and say, Okay, we built this ladder, but we want to go to the moon, and there's no way this ladder is going to get us there," says LeCun. Yann LeCun, chief AI scientist of Meta Properties, owner of Facebook, Instagram, and WhatsApp, is likely to tick off a lot of people in his field. With the posting in June of a think piece on the Open Review server, LeCun offered a broad overview of an approach he thinks holds promise for achieving human-level intelligence in machines. Implied if not articulated in the paper is the contention that most of today's big projects in AI will never be able to reach that human-level goal. In a discussion this month with ZDNet via Zoom, LeCun made clear that he views with great skepticism many of the most successful avenues of research in deep learning at the moment. "I think they're necessary but not sufficient," the Turing Award winner told ZDNet of his peers' pursuits. Those include large language models such as the Transformer-based GPT-3 and their ilk. As LeCun characterizes it, the Transformer devotées believe, "We tokenize everything, and train giganticmodels to make discrete predictions, and somehow AI will emerge out of this." "They're not wrong," he says, "in the sense that that may be a component of a future intelligent system, but I think it's missing essential pieces." It's a startling critique of what appears to work coming from the scholar who perfected the use of convolutional neural networks, a practical technique that has been incredibly productive in deep learning programs. LeCun sees flaws and limitations in plenty of other highly successful areas of the discipline. Reinforcement learning will also never be enough, he maintains. Researchers such as David Silver of DeepMind, who developed the AlphaZero program that mastered Chess, Shogi and Go, are focusing on programs that are "very action-based," observes LeCun, but "most of the learning we do, we don't do it by actually taking actions, we do it by observing." Lecun, 62, from a perspective of decades of achievement, nevertheless expresses an urgency to confront what he thinks are the blind alleys toward which many may be rushing, and to try to coax his field in the direction he thinks things should go. "We see a lot of claims as to what should we do to push forward towards human-level AI," he says.