The article has some interesting insights in latest deep learning successes. It is an example of hyper-optimistic thinking about AI timing (which is hyper-pessimistic, if we look on risks), as 2020-2030 for the authors seems like a plausible dates of AI arrival.
Some quotes:
“The difference between year 2011 and year 2016 is enormous. The difference between 2016 and 2021
would be even much more enormous because we have now 1-2 orders of magnitude more researchers
and companies deeply interested in DL. For example, when machines would start to translate almost
comparably to human professionals another billions of dollars would flow into deep learning based NLP.
The same holds true for most spheres, for example drug design [150]”
Review of state-of-the-arts in artificial intelligence. Present and future of AI.
Vladimir Shakirov
http://immortality-roadmap.com/review-of-state-of-the-arts.pdf
The article has some interesting insights in latest deep learning successes. It is an example of hyper-optimistic thinking about AI timing (which is hyper-pessimistic, if we look on risks), as 2020-2030 for the authors seems like a plausible dates of AI arrival.
Some quotes: “The difference between year 2011 and year 2016 is enormous. The difference between 2016 and 2021 would be even much more enormous because we have now 1-2 orders of magnitude more researchers and companies deeply interested in DL. For example, when machines would start to translate almost comparably to human professionals another billions of dollars would flow into deep learning based NLP. The same holds true for most spheres, for example drug design [150]”