The road to artificial general intelligence

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Artificial intelligence models that may discover drugs and write code still fail at puzzles a lay person can master in minutes. This phenomenon sits at the center of the challenge of artificial general intelligence (AGI). Can today’s AI revolution produce models that rival or surpass human intelligence across all domains? In that case, what underlying enablers—whether hardware, software, or the orchestration of each—can be needed to power them?

Dario Amodei, co-founder of Anthropic, predicts some type of “powerful AI” could come as early as 2026, with properties that include Nobel Prize-level domain intelligence; the flexibility to modify between interfaces like text, audio, and the physical world; and the autonomy to reason toward goals, fairly than responding to questions and prompts as they do now. Sam Altman, chief executive of OpenAI, believes AGI-like properties are already “coming into view,” unlocking a societal transformation on par with electricity and the web. He credits progress to continuous gains in training, data, and compute, together with falling costs, and a socioeconomic value that’s
super-exponential.

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