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Jakub Pachocki on AGI timeline

From Sam, Jakub, and Wojciech on the future of OpenAI with audience Q&A · · OpenAI

“We believe that it is possible that deep learning systems are less than a decade away from superintelligence — systems that are smarter than all of us on a large number of critical axes.”

Jakub Pachocki
Chief Scientist, OpenAI
Controversial Policy Impact AGI timelinesuperintelligenceAI safety

On , Jakub Pachocki, Chief Scientist at OpenAI, spoke about AGI timeline during Sam, Jakub, and Wojciech on the future of OpenAI with audience Q&A on OpenAI.

Sam, Jakub, and Wojciech on the future of OpenAI with audience Q&A
Watch on YouTube at 4:26
Sam, Jakub, and Wojciech on the future of OpenAI with audience Q&A
OpenAI
Watch on YouTube at 4:26
OpenAI leaders discuss their ambitious plans for artificial general intelligence (AGI), detailing research, product development, and massive infrastructure needs. They also address audience questions about AGI timelines, safety concerns, and future product developments, offering unprecedented transparency.
Jakub Pachocki

About Jakub Pachocki

Chief Scientist · OpenAI

In a March 2026 podcast appearance, OpenAI Chief Scientist Jakub Pachocki discussed the company’s focus on continual learning, describing it as "the thing that we're building" and "what we're working toward." He addressed the use of math and physics benchmarks as proxies for general intelligence and noted that reinforcement learning is being extended beyond easily-verified domains toward longer-horizon tasks. Pachocki also expressed excitement about the "first proof challenge," a benchmark of unpublished problems from mathematicians and theoretical computer scientists, and recounted how an OpenAI model was prompted to solve those problems during a training run. Pachocki stated that OpenAI believes its models are "capable enough to actually materially change the economy, change how things are done," and said the company feels "a lot of urgency about that." He also acknowledged challenges associated with automating intellectual work, including questions about jobs and wealth concentration, and said that "this requires real policy maker involvement."

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