
AI development is going to get even faster - jonbaer
https://jack-clark.net/2016/04/03/why-ai-development-is-going-to-get-even-faster-yes-really/
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rmelly
_(One challenge: though neural networks generalize very well, we still lack a
decent theory to describe them, so much of the field proceeds by intuition.
This is both cool and extremely bad. “It’s amazing to me that these very
vague, intuitive arguments turned out to correspond to what is actually
happening,” says Ilya Sutskever, research director at OpenAI., of the move to
create ever-deeper neural network architectures. Work needs to be done here.
“Theory often follows experiment in machine learning,” says Yoshua Bengio, one
of the founders of the field. Modern AI researchers are like people trying to
invent flying machines without the formulas of aerodynamics, says Yann Lecun,
Facebook’s head of AI.)_

One of the most interesting aspects of the field - we don't have robust ways
of predicting what will work without trying it.

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arcanus
> Modern AI researchers are like people trying to invent flying machines
> without the formulas of aerodynamics

An apt analogy, given that flying machines were designed by individuals
without a robust understanding of fluid mechanics.

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AndrewKemendo
This doesn't really describe how development is going to get faster. It just
lumps the next big leap into unsupervised learning - which isn't really an
understood concept as the author describes.

The "unsupervised learning as black box" argument always bothers me. It looks
too much like the consciousness debate. The theory that UL is an emergent
property from massively scaled NAIs is at least plausible IMO, but that wasn't
really discussed.

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bbctol
There's no real guarantee that current success with neural networks will
continue to ramp up all the way to hard AI. They're impressive, and getting
more interesting all the time, but the downside of the whole "though neural
networks generalize very well, we still lack a decent theory to describe them,
so much of the field proceeds by intuition" is that we don't know when they'll
suddenly stop being useful for some problem.

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anabis
I agree that the road to hard AI is still foggy, but the applications of the
current technology by itself has only scratched the surface.

For example, since Deep Learning has already shown great advance in the audio-
visual tasks, the entertainment business which heavily utilize those senses
will get a boost all around.

