I guess goes back to what I was trying to
say about the agents and the environment.
GO is a closed environment it's very simple you can write a program and the rules are the
rules, there is no entropy there is no stochasticity
there is no randomness.
Where as any real world application is quite much
more challenging.
There are other players you don't know what
they are doing, there are news outlets you
might not have considered, there is quite
a bit of sentiment and so and so, I think
those environments that are vastly more complex,
it will take quite a few of new breakthroughs
to be able to attack them in a similar way
that we did with Alpha Go.
I mean, something not really like Alpha Go,
full Alpha Go, but obviously
any sort of
thing related to a time series and so on you can train
a model to try to be predictive.
However, the more noisier and messy the data
is, the less the algorithm works.
Speech is a single ... generate it and predict
the future quite well but other signals I
mean there quite many problems of course.
