In a recent analysis, Forbes examines Sam Altman's latest blog post about artificial general intelligence (AGI) and its implications for AI development benchmarks.
The article compares three different AGI definitions:
1. Altman's new definition: "A system that can tackle increasingly complex problems, at human level, in many fields"
2. OpenAI's charter definition: "Highly autonomous systems that outperform humans at most economically valuable work"
3. Eliot's definition: "An AI system that exhibits intelligent behavior of both a narrow and general manner on par with that of humans, in all respects"
The article argues that Altman's new definition represents a looser, more achievable standard compared to more rigorous definitions of AGI.
This "moving of the goalposts" could make AGI appear more attainable in the near term, but potentially at the cost of compromising the original, more ambitious vision of artificial general intelligence.
The author suggests that maintaining higher standards for AGI might be more beneficial for long-term AI development, comparing it to the difference between landing on the moon versus establishing permanent lunar habitation.
The piece raises important questions about how defining AGI impacts development priorities and public expectations in the AI industry, with significant implications for AI makers, researchers, and society at large.