AI Luminaries Clash At Davos Over How Close Human-Level Intelligence Really Is

An anonymous reader shared this report from FortuneThe large language models (LLMs) that have captivated the world are not a path to human-level intelligence, two AI experts asserted in separate remarks at Davos. Demis Hassabis, the Nobel Prize-winning CEO of Google DeepMind, and the executive who leads the development of Google's Gemini models, said today's AI systems, as impressive as they are, are "nowhere near" human-level artificial general intelligence, or AGI. [Though the artilcle notes that later Hassabis predicted there was a 50% chance AGI might be achieved within the decade.] Yann LeCun - an AI pioneer who won a Turing Award, computer science's most prestigious prize, for his work on neural networks - went further, saying that the LLMs that underpin all of the leading AI models will never be able to achieve humanlike intelligence and that a completely different approach is needed... ["The reason ... LLMs have been so successful is because language is easy," LeCun said later.] Their views differ starkly from the position asserted by top executives of Google's leading AI rivals, OpenAI and Anthropic, who assert that their AI models are about to rival human intelligence. Dario Amodei, the CEO of Anthropic, told an audience at Davos that AI models would replace the work of all software developers within a year and would reach "Nobel-level" scientific research in multiple fields within two years. He said 50% of white-collar jobs would disappear within five years. OpenAI CEO Sam Altman (who was not at Davos this year) has said we are already beginning to slip past human-level AGI toward "superintelligence," or AI that would be smarter than all humans combined... The debate over AGI may be somewhat academic for many business leaders. The more pressing question, says Cognizant CEO Ravi Kumar, is whether companies can capture the enormous value that AI already offers. According to Cognizant research released ahead of Davos, current AI technology could unlock approximately $4.5 trillion in U.S. labor productivity - if businesses can implement it effectively.

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