Do We Have an Evolutionary End Point?
“If I were really prescient, I would have told people in 1990 that new jobs would soon become available to create and operate websites and mobile applications, doing data analytics and online merchandising. But they wouldn’t have had any idea what I was talking about.” — Ray Kurzweil, The Singularity Is Nearer: When We Merge with AI, p. 200, Kindle Edition
Artificial General Intelligence (AGI) promises many things. In articles and books AGI is described as a state of machine intelligence in which the machine equals or exceeds human cognitive competence in a wide range of fields, as opposed to only one or two. Notwithstanding government apocalyptic efforts to nuke mankind out of existence, true AGI could arrive by the time you’re reading this. According to tech journalist Julian Horsey,
Dr. Alan D. Thompson, a prominent AI specialist, has proposed a conservative countdown suggesting that AGI could be achieved by November 2024. This prediction is based on a percentage scale that tracks progress towards key milestones in AI development. These milestones include eliminating hallucinations in language models, achieving physical embodiment in robots, and passing advanced tests such as making a cup of coffee in an unfamiliar environment.
The drawback to current narrow intelligent systems, it is claimed, is their inability “to adapt to new goals or circumstances, and generalize knowledge from one context to another, which humans do through transfer learning.” While this may be true in many cases, it is emphatically not true with regard to some of DeepMind’s AI products. In March 2016, AlphaGo defeated world Go champion Lee Sedol, which some claimed was the Holy Grail of AI because the game of Go is “a googol times more complex than chess — with an astonishing 10 to the power of 170 possible board configurations. . . . more than the number of atoms in the known universe.”
Its victory was “conclusive proof that the underlying neural networks could be applied to complex domains, while the use of reinforcement learning showed how machines can learn to solve incredibly hard problems for themselves, simply through trial-and-error.” [Emphasis added]
Artificial intelligence can be viewed as a tool to help people work better, faster and with increased precision and reliability. Capitalism has thrived on the backs of such tools since the dawn of the industrial revolution. Once AGI is reached the pace of almost everything will increase sharply, then unbelievably, as more processes become information technologies and therefore exponentially increasing in price-performance. Unless it is disconnected from its energy source, AGI will never stop learning, nor will it forget anything it has learned, and will handle intellectual tasks millions of times faster than the best human minds. Since civilization is heavily dependent on affordable energy, AGI will at least accelerate improvements in energy production and conservation, and will likely discover new and economical methods of extracting
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