AGI? “Not in 100 years!” Well, maybe check the scoreboard…
Reevaluating the Timeline of Artificial General Intelligence (AGI): Has It Arrived Sooner Than Expected?
In 2018, philosopher and AI researcher Nick Bostrom articulated a significant milestone in artificial intelligence: passing a hard Turing Test—conducted by expert interrogators—was considered an “AI-complete” problem. This term implied that achieving Artificial General Intelligence (AGI), capable of any intellectual task a human can perform, was still a distant goal, likely requiring a major breakthrough.
Fast forward to 2025, and the AI landscape has dramatically shifted in ways previously thought to be decades away. Recent developments suggest that artificial intelligence systems have made substantial progress—a reality that warrants reconsideration of our timeline estimates. Here are some of the most compelling indicators:
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LLMs Passing Expert-Level Turing Tests: Large Language Models (LLMs) now routinely pass tests administered by human experts, demonstrating capabilities once thought exclusive to human cognition.
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Outperforming Humans in Imitating Human Behavior: These models are not just passing tests—they are outperforming human participants in convincingly mimicking human language and behavioral patterns.
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Peer-Reviewed Evidence of Behavioral Indistinguishability: Multiple academic studies have independently confirmed that current AI systems can produce outputs indistinguishable from those of humans in controlled experiments.
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Consistent Fooling of Real People at Scale: Beyond laboratory settings, LLMs are now reliably deceiving large audiences of everyday users in real-world interactions.
For reference, be sure to review the following key publications:
So, what does this mean for AGI? It suggests that AGI might not be the distant, far-off goal we once believed it to be. We may have already crossed the threshold without fully recognizing it—simply because the noise of rapid technological advancement has overshadowed this milestone.
As we move forward, it is important for researchers, policymakers, and the broader public to reevaluate the assumptions about the timeline and implications of artificial intelligence development. The era of AGI could be closer than anticipated, compelling us to
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