Google AI CEO on why Sam Altman's 'ultimate goal' for OpenAI cannot be realised

Google DeepMind CEO Demis Hassabis believes true Artificial General Intelligence (AGI) is still distant, citing limitations in continual learning, long-term reasoning, and consistency. He stated current systems don't adapt in real-time, struggle with planning over years, and exhibit uneven performance, unlike human experts. Hassabis's comments contrast with OpenAI's ambitious AGI goals.

By TOI TECH DESK

DeepMind's CEO said there are still 3 areas where AGI systems can't match real intelligence

DeepMind's CEO said AGI still lags behind real intelligence in three areas. LUDOVIC MARIN/POOL/AFP via Getty Images DeepMind's Demis Hassabis said artificial general intelligence efforts still leave a lot to be desired. Current systems cannot learn continuously, cannot plan long-term, and lack consistency, he said. He said last year that it would take five to 10 years for the world to see real AGI in play. True artificial general intelligence is on the way, but it still has some ways to go, said Google DeepMind's CEO. Speaking at an AI summit in New Delhi, Demis Hassabis was asked whether current AGI systems can match human intelligence. AGI is a hypothetical form of machine intelligence that can reason like people and solve problems using methods it was not trained in. Hassabis' short answer: "I don't think we are there yet." He listed three areas where current AGI systems are falling short. The first was what he called "continual learning," saying that the systems are frozen based on the training they received before implementation. "What you'd like is for those systems to continually learn online from experience, to learn from the context they're in, maybe personalize to the situation and the tasks that you have for them," he said during the discussion. Secondly, Hassabis said current systems struggle with long-term thinking. "They can plan over the short term, but over the longer term, the way that we can plan over years, they don't really have that capability at the moment," he said. And lastly, he said that the systems lack consistency. They're adept in some areas and unskilled in others. "So, for example, today's systems can get gold medals in the international Math Olympiad, really hard problems, but sometimes can still make mistakes on elementary maths if you pose the question in a certain way," he said. "A true general intelligence system shouldn't have that kind of jaggedness." Humans, in comparison, would not make mistakes on an easy math problem if they were math experts, he added. Hassabis said in a "60 Minutes" interview last year that true AGI would arrive in five to 10 years. The executive cofounded DeepMind, an AI research lab, in 2010. The lab was acquired by Google in 2014 and is the brains behind Google's Gemini. In 2024, Hassabis won a joint Nobel Prize in chemistry for his work on protein structure prediction. AGI is a disputed topic in Silicon Valley. Databricks CEO Ali Ghodsi said at a September conference that current AI chatbots already meet the definition of AGI, but Silicon Valley leaders keep "moving the goalposts" and pushing toward superintelligence, or AI that can outthink humans. The AI Summit in India, from Monday to Friday this week, has attracted big names from the tech and AI spheres. Notable speakers on the summit's agenda include OpenAI CEO Sam Altman, Anthropic CEO Dario Amodei, Google CEO Sundar Pichai, and Meta's chief AI officer, Alexandr Wang. Read the original article on Business Insider