Gary Marcus Challenges Elon Musk’s Predictions on AGI Development
Gary Marcus has publicly challenged Elon Musk’s assertion that Artificial General Intelligence (AGI) will be achieved by 2029, prompting a wager of $100,000. Marcus, who established RobustAI and Geometric Intelligence (later acquired by Uber), is also the Professor Emeritus of Psychology and Neural Science at NYU and the author of Rebooting.AI. His insights into AGI deserve attention.
AGI, often portrayed in films like 2001: A Space Odyssey‘s ‘HAL’ or Iron Man’s ‘J.A.R.V.I.S’, represents a form of artificial intelligence that resembles human cognitive capabilities. Unlike current AIs that are designed for specific tasks, AGIs possess the ability to learn and adapt to a wide variety of activities. Many experts predict that achieving AGI will take decades, with some expressing doubts about its eventual feasibility. Surveys among industry experts suggest an average estimate for the development of AGI by 2099 lays the probability at 50%.
In contrast, Musk remains optimistic, suggesting that 2029 is a transformative year when he expects AGI to emerge. His May 30, 2022 tweet reflected this belief: “2029 feels like a pivotal year. I’d be surprised if we don’t have AGI by then. Hopefully, people on Mars too.” Following this claim, Marcus responded by challenging Musk to a wager regarding the timeline of AGI’s emergence.
AI specialist Melanie Mitchell from the Santa Fe Institute has suggested that such bets could be facilitated through longbets.org. Marcus is keen on the idea, proposing that the stakes be directed towards charity, but he has yet to receive a response from Musk.
In a recent post on his Substack, Marcus elaborated on his reservations regarding Musk’s predictions. He stated, “Your track record on betting on precise timelines for things is, well, spotty,” referencing Musk’s previous forecasting of self-driving cars, which has not materialized as expected. Marcus argues that such grand statements can mislead and detract from addressing fundamental questions in artificial intelligence, such as the complexities of language comprehension and reasoning.
Reflecting on a recent incident where a Tesla in Autopilot mode collided with a private jet, Marcus emphasized the necessity of resolving significant AI challenges before pursuing AGI. “It’s easy to convince yourself that AI problems are much simpler than they actually are, because of the long tail problem,” he argued. “While we gather extensive data for everyday situations, rare events present substantial challenges that existing methodologies struggle to tackle.”
Marcus is confident that Musk will not achieve fully-autonomous ‘Level 5’ vehicles in the near future, despite Musk’s assurances at TED2022. He cautions that unexpected scenarios, such as the intrusion of a private jet, will continue to complicate AI development.
He believes that while seven years may seem ample time, the field must diversify its strategies to realize AGI by the decade’s end. Without this, dealing with rare outliers may hinder progress towards this ambitious goal. Marcus argues that although these outlier issues don’t represent an insurmountable challenge, they currently lack effective solutions. Thus, predicting AGI’s achievement within this timeframe can be viewed as overly optimistic.
Moreover, Marcus highlights that while deep learning excels at object recognition, it falls short in replicating advanced human abilities like planning, reading, or language comprehension. He provided a pie chart illustrating the multifaceted capabilities an AGI must develop. He noted that his insights remain largely unchanged over the past five years, reiterating that we still lack stable and reliable solutions for fundamental cognitive tasks such as common sense reasoning and analogy. Meanwhile, Tesla is working on a robot designed to perform everyday tasks.
Marcus expresses skepticism about the development of general-purpose domestic robots, particularly in light of Tesla’s ongoing issues with their vehicles. He argues, “The AGI required for a versatile home robot, where each household poses unique safety challenges, vastly surpasses what is necessary for cars navigating roads that are largely standardized from one town to another.” This commentary stems from the current ambiguity surrounding the term AGI, prompting Marcus to outline five predictions regarding capabilities that he believes AI will not achieve by Elon Musk’s target of 2029 for AGI development.
So, Musk—are you willing to take on Marcus’ challenge? Personally, I wouldn’t even consider it, even if I shared Musk’s financial liberty.
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