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Scientist Says AI With Reasoning Power Will Be Less Predictable

Ilya Sutskever suggests advancing AI by having technology generate new data or models evaluate multiple answers for accuracy, while other scientists focus on using real-world data to enhance AI’s effectiveness.
Ilya Sutskever, co-Founder and Chief Scientist of OpenAI speaks during a talk at Tel Aviv University in Tel Aviv, Israel June 5, 2023. REUTERS/Amir Cohen/File Photo

Ilya Sutskever, former Chief Scientist at OpenAI and a leading figure in artificial intelligence, predicted on Friday that reasoning capabilities will make AI technology significantly less predictable.

Accepting a “Test Of Time” award for his 2014 paper with Google’s Oriol Vinyals and Quoc Le, Sutskever said a major change was on AI’s horizon.

An idea that his team had explored a decade ago, that scaling up data to “pre-train” AI systems would send them to new heights, was starting to reach its limits, he said.

More data and computing power had resulted in ChatGPT that OpenAI launched in 2022, to the world’s acclaim.

“But pre-training as we know it will unquestionably end,” Sutskever declared before thousands of attendees at the NeurIPS conference in Vancouver.

“While compute is growing, “the data is not growing, because we have but one internet,” he said.

Sutskever offered some ways to push the frontier despite this conundrum.

He said that technology itself could generate new data, or AI models could evaluate multiple answers before settling on the best response for a user, to improve accuracy.

Other scientists have set sights on real-world data.

But his talk culminated in a prediction for a future of super intelligent machines that he said “obviously” await, a point with which some disagree.

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This year, Sutskever co-founded Safe Super intelligence Inc in the aftermath of his role in Sam Altman’s short-lived ouster from OpenAI.

Long-in-the-works AI agents, he said, will come to fruition in that future age, have deeper understanding and be self-aware.

He said that AI will reason through problems like humans can.

There is a catch.

“The more it reasons, the more unpredictable it becomes,” he said.

Reasoning through millions of options could make any outcome non-obvious.

By way of example, AlphaGo, a system built by Alphabet’s DeepMind, surprised experts of the highly complex board game with its inscrutable 37th move, on a path to defeating Lee Sedol in a match in 2016.

Sutskever said, “The chess AIs, the really good ones, are unpredictable to the best human chess players.”

AI as we know it, he said, will be “radically different.”

(With inputs from Reuters)