In the next nine years, we expect to develop AI models capable of discovering concepts akin to general relativity, marking a significant leap in AI's reasoning abilities.

Current AI models feel limited and are not making groundbreaking discoveries like general relativity, possibly due to the way we frame our research questions.

The biggest obstacles to reaching AGI are new research challenges, as AI research does not follow the same timeline as engineering, often taking much longer to yield results. This non-linear progress of technology can be seen in historical examples like the rapid development of the atomic bomb from the theoretical concept of the neutron in the early 1900s to its realization in the 1940s.

The timeline for achieving artificial general intelligence (AGI) is uncertain, with predictions varying widely, but many believe it could happen sooner than previously thought, possibly by 2040.

The ability to allow AI models to reason for extended periods, rather than just providing quick answers, can lead to significantly better outcomes for complex questions.

The timeline for achieving AGI has shifted; I initially thought it would take about 15 years, but now I estimate we might reach significant milestones by 2030 or 2031. We had extensive discussions about the safety and alignment of artificial general intelligence (AGI), recognizing the potential risks if something goes horribly wrong.

People are surprisingly willing to wait for a great answer, even if it takes time for the model to think.

I believe AI could potentially solve one of the seven Millennium Prize Problems, but we're still a long way from that capability.

Current AI models are approaching a level of intelligence that rivals human capabilities, suggesting that artificial general intelligence (AGI) may already be here.