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Why businesses shouldn't chase AGI
By Rich Heimann
All Roads Lead to Rome: The Machine Learning Job Market in 2022 is a self-congratulatory article by the new VP of AI at Halodi Robotics, Eric Jang. The article boastfully discusses Jang’s lucrative job search, which he presents as market research. However, what caught my attention was not the dubious antidotal market analysis (which includes many unverified claims and suppositions) but Jang’s assertion that every successful technology company will be an AGI company and require an “AGI strategy.”
AGI was only recently popularized by Shane Legg and fellow researchers Ben Goertzel and Cassio Pennachin. In 2007, Goertzel and Pennachin edited a book titled Artificial General Intelligence, which called for stronger adherence to the original vision of AI, which is not (as Jang suggests) merely the “means to make… software more adaptive and generally useful.” According to Goertzel and Pennachin, AGI possesses “self-understanding and autonomous self-control,” with the “ability to solve a variety of complex problems in a variety of contexts and to learn to solve new problems that they didn’t know about at the time of their creation.” In other words, AGI is a blank slate problem solver where knowledge of a problem is independent of any strategy to solve that problem and where any goal is understood and shared by the solution. This is a tall order for applied problem-solving since your solution does not need to know that it is solving a problem, but you do.
It would be revisionist to suggest that Legg, Goertzel, and Pannachin promoted the name to deal with the vacuous nature of contemporary “AI,” meaning almost anything to anyone. However, today “AGI” is used more and more by originalists to distinguish their work from the noisy contemporary “AI” label. Over the same period, “AGI” has gone from a fringe idea promoted by unknown researchers to something that people surprisingly use to make career decisions and as corporate mission statements.
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