AI ‘godfather’ Yann LeCun says maths and physics matter more than coding | Technology News
2 min readNew DelhiUpdated: Dec 24, 2025 02:25 PM IST
Yann Lecun, the 65-year-old NYU professor who is regarded as one of the “godfathers” of AI, has some advice for students who are looking to get in the field of artificial intelligence.
“If you are a CS major and take the minimum required math courses for the typical CS curriculum, you might find yourself unable to adapt to major technological shifts,” Lecun told Business Insider. During an almost two-hour-long podcast called The Information Bottleneck on YouTube, Yann Lecun said students should focus on things with a “long shelf life” like mathematics, physics or engineering, signal processing, control theory, and optimisation.
“The disciplines with the longest shelf life are usually not computer science. Physics and engineering teach you how to model reality, and that’s what intelligence is really about,” says Lecun. While universities and computer science students are trying to grapple with and adapt to generative and agentic AI, students still seem to be having trouble finding a job.
The NYU professor said that he did not initially study computer science but was enrolled in electrical engineering at ESIEE in Paris, but he went on to get a Ph.D CS in 1987. Talking about large language models, Lecun said that “we are absolutely never ever going to get to human-level AI by just training on text. It’s just never going to happen.”
He reasoned that AI systems that rely on LLMs requirea ton of data to clone human behaviour and that scaling language models to get super intelligence (AGI) is never going to work. Talking about Artificial General Intelligence, the godfather of AI believes “what people call AGI is really just human-level intelligence.”
Yann Lecun’s advice for students is on the same lines as OpenAI’s Bret Taylor and Nobel Laureate Geoffrey Hinton, who have previously said that students should develop critical skills and coding isn’t everything in computer science.
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