Yann LeCun, chief AI scientist at Meta and a leading figure in deep learning, has cautioned that the fast growing humanoid robot market is showing signs of a bubble. He said many companies are rushing to build robots without knowing how to make them intelligent enough to be genuinely useful.
He shared his views while speaking at the first MIT Generative AI Impact Symposium at the Massachusetts Institute of Technology in the United States. The event focuses on advancing generative AI research and industry collaboration.
LeCun said, “There is a large number of robotics companies that have been created over the last few years building humanoid robots. The big secret of the industry is that none of those companies has any idea how to make those robots smart enough to be generally useful.” He explained that current technology can train robots to perform specific tasks in manufacturing but not in everyday home environments. He added that major advances in artificial intelligence are still needed before domestic robots become possible.
He also pointed out that many of these startups have raised billions of dollars. Their success will depend on “whether we are going to make progress, significant progress, towards those kinds of world model planning type architectures.”
This warning reflects wider concerns in the industry. Experts believe that challenges like continual learning must be solved before artificial general intelligence can be achieved. Andrej Karpathy, an OpenAI co founder and AI researcher, recently said on a popular podcast, “They do not have continual learning. You cannot just tell them something and they will remember it. They are cognitively lacking and it is just not working. It will take about a decade to work through all of those issues.”
LeCun said current large language models are not ready to power humanoid robots. He stated that AI must learn from high bandwidth sensory data such as video. “We are never going to get to human level intelligence by just training on text,” he said. He explained that a four year old child has seen as much visual data as the largest models trained on all publicly available text.
He believes the answer lies in something called a world model. This is an AI system that can understand the physical world by learning from real world sensory information. LeCun is researching non generative self supervised systems like V JEPA that predict what happens next in a video. He said these models show early signs of common sense and could help robots complete tasks without any extra training.
Yann LeCun is one of the three godfathers of AI. He is a professor at New York University and a Turing Award winner for his breakthroughs in deep learning.
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