Why an AI 'godfather' is quitting Meta after 12 years
2 hours ago Share Save Liv McMahon Technology reporter Share Save
Getty Images Prof LeCun is known for advancing the deep learning field of AI, and for his jazzy bowties
Just a couple of weeks ago, one of the "godfathers" of artificial intelligence was in St James's Palace being handed an award from King Charles for his work in artificial intelligence (AI). Professor Yann LeCun was being honoured along with six other recipients for his contributions to the field, which have been credited as advancing deep learning. But Mr LeCun is at odds with some of the AI world over the future of the generation-defining technology. And now he is going all-in on his idea of "advanced machine intelligence" after announcing he is leaving his role as Meta's chief AI scientist to start a new firm. During his 12 years at the company, Prof LeCun won the prestigious Turing Award and witnessed several flurries of excitement around AI - not least the most recent boom in generative AI accelerated by rival OpenAI's launch of ChatGPT in late 2022. But his departure comes amid speculation the AI boom could meet an abrupt end should the so-called "AI bubble" of ballooning valuations and soaring spending burst. Investors, analysts and even big tech bosses like Google's chief executive Sundar Pichai have said a market correction to the AI sector would ripple across the wider economy.
What LeCun thinks the AI world gets wrong
Prof LeCun announced his planned departure from Meta on Wednesday after more than a week of rumours and reports of his exit. In a series of posts on Threads, he thanked the company's founder Mark Zuckerberg and highlighted its Fundamental AI Research (FAIR) lab as his "proudest non-technical accomplishment". "As many of you have heard through rumours or recent media articles, I am planning to leave Meta after 12 years: 5 years as founding director of FAIR and 7 years as Chief AI Scientist," he wrote. "The impact of FAIR on the company, on the field of AI, on the tech community, and on the wider world has been spectacular." The lab has over the years focused on developing systems and techniques to advance machine learning and translation. But, like large parts of the sector, Meta has looked to concentrate much of the company's research and spending on large language models (LLMs) - the systems at the heart of generative AI tools such as chatbots and image generators. Prof LeCun has suggested LLMs will be less useful in attempting to create AI systems that can match human intelligence. Instead, he wants to pursue what he called "advanced machine intelligence". It trains AI models primarily by using visual learning - trying to replicate how a child or a baby animal learns. That differs to LLMs, which are fed vast amounts of existing data, and then asked to generate a result based on the data and a prompt.