This AI Prediction was made by Ray J. Solomonoff in 1985.
Predicted time for AGI / HLMI / transformative AI:
Opinion about the Intelligence Explosion from Ray J. Solomonoff:
After we have reached Milestone E, it shouldn’t take much more than ten years to construct ten thousand duplicates of our original “Milestone E” machine, and have a total computing capability close to that of the computer science community. The ten year figure seems reasonable when one notes that the cost of these machines will keep halving every four years or so, and also that the new “artificial” computer scientists will help speed the construction of the new machines.
Flycer’s explanation for better understanding:
Milestone E has been reached, and it is estimated that it will take around ten years to construct ten thousand duplicates of the original machine. The cost of these machines will halve every four years, and the help of artificial computer scientists will speed up the process. This ten year figure is considered reasonable.
The future of humanity with AGI / HLMI / transformative AI:
What seems most certain is that the future of man— both scientific and social— will be far more exciting than the wildest eras of the past.
Flycer’s Secondary Explanation:
The future of humanity is sure to be more exciting than any period of the past. Science and society are both set to experience dramatic changes in the coming years. It is certain that the future of mankind will be full of surprises.
Ray J. Solomonoff was an American computer scientist and one of the founders of the field of algorithmic information theory. He is best known for his work on the theory of universal induction, which is a method for making predictions based on past observations. He also developed the universal prior, which is a probability distribution used to represent prior knowledge in Bayesian inference. He was a professor at the University of Illinois at Urbana-Champaign and a Fellow of the Association for Computing Machinery.
Keywords: Milestone E, ten thousand, computer science