Although the new generation of foundational AI models (e.g. chatGPT) can produce stunning outputs, one of the leading AI thinkers, New York University professor and Turing Award winner, Yann LeCun, has a more sanguine view of their “intelligence”. LeCun’s view is that, for all the talk of these foundational models surpassing human capabilities, humans and other animals exhibit learning abilities and understandings of the world that are far beyond the capabilities of current AI and machine learning (ML) systems:
“How is it possible for an adolescent to learn to drive a car in about 20 hours of practice and for children to learn language with what amounts to a small exposure. How is it that most humans will know how to act in many situation they have never encountered? …Still, our best ML systems are still very far from matching human reliability in real-world tasks such as driving, even after being fed with enormous amounts of supervisory data from human experts, after going through millions of reinforcement learning trials in virtual environments, and after engineers have hardwired hundreds of behaviors into them.”
The global technology companies are locked in a competitive battle over AI, each with their own vision of AI. Microsoft has recently announced a big investment in OpenAI, which created chatGPT. Google has reportedly called back its founders to help repoint Google’s business to AI. LeCun himself is, in addition to his professorial position, Meta’s AI Chief Scientist. Understanding his recent views on the future of AI, whether you agree with them or not, helps map out the challenges that still lie ahead in reaching human-level machine intelligence.
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