Yann LeCun, a former meta-AI scientist and one of the godfathers of modern artificial intelligence (AI), has identified another challenge where humans can outperform technology. Speaking at the India AI Impact Summit 2026, he said that large-scale language models “Incredibly convenient” It still falls short of tasks such as driving, which humans can handle relatively easily. LeCun acknowledged that AI systems can pass the bar exam and perform well in the Math Olympiad, but said a more fundamental gap remains, noting that the technology still lags behind real-world intelligence.“There certainly isn’t a self-driving car that you can teach yourself to drive like a 17-year-old with 20 hours of practice.” he said emphatically “We’re missing something big.”. LeCun explained that AI is good at information retrieval and symbolic reasoning, but lacks a true understanding of the physical world. He likened large-scale language models to the evolution of the printing press, libraries, and the Internet. “It’s a more efficient way to access information.”he added.
Yann LeCun said this about the gap between the two. AI and real-world intelligence
LeCun said that humans and animals learn and gradually form through observation and interaction. “Mental model” It helps you predict outcomes and adapt to new situations.He also said that unlike human learning, AI systems cannot yet function well in complex and unpredictable environments, which limits the potential for robots and self-driving cars compared to human learning.Regarding the use of AI in education and development, LeCun explained that AI is a technology that is meant to support human abilities, not replace them. He says AI has the potential to enhance human intelligence and expand access to knowledge, just as the printing press once did.He also pointed out that countries with large young and educated populations, such as India and some parts of Africa, could play a greater role in AI innovation if investments are made in skills development and infrastructure.Mr. LeCun is a professor at New York University, executive chair of AMI Labs, works in the fields of artificial intelligence, machine learning, and robotics, and is an ACM Turing Award recipient.He recently publicly questioned OpenAI’s claims about achieving artificial general intelligence (AGI) following a social media exchange with OpenAI Vice President Sebastian Bubeck. The discussion, which took place on X (formerly Twitter), reflected differing views on research transparency and whether a single company can develop AGI.LeCun criticized OpenAI’s research practices as largely conducted behind closed doors, rejected the idea that AGI will emerge from one organization or a single breakthrough, and said OpenAI does not have a monopoly on innovation.
