Well, most unsupervised deep learning algorithms these days involve some
unsupervised pre-training of the network...

But the crux of Deep Mind's video-game demonstration was RL where the game
score was the "supervision" providing the utility function, yeah...

I should add that Deep Mind is doing a huge amount of other stuff besides
this game-focused stuff -- that just happens to be the aspect of their work
that yields the funkiest demos...

ben

On Wed, Oct 21, 2015 at 5:15 PM, Steve Richfield <[email protected]>
wrote:

> Ben,
>
> Am I reading this right - that this is "just" a VERY good demo of
> SUPERVISED learning - with no unsupervised components?
>
> Steve
> =========
>
> On Tue, Oct 20, 2015 at 11:19 PM, Ben Goertzel <[email protected]> wrote:
>
>>
>> On Wed, Oct 21, 2015 at 1:54 PM, Benjamin Kapp <[email protected]> wrote:
>>
>>> They are using reinforcement learning to train their system.  But one of
>>> the problems with this is that it is dependent on a reward/punishment
>>> system which for them is determined by game scores.  But in the real world
>>> there is no game score.  Also in the game world game score is temporally
>>> closely related to the actions the agent performs.  However in the real
>>> world rewards and punishments may be delayed by a great deal of time (if
>>> they are ever given).
>>>
>>
>>
>> Demis, Shane and the other Deep Mind folks are well aware of these
>> issues, of course...
>>
>> A fallacy I commonly see is that people like to compare their own ideas,
>> with other peoples' practical demonstrations...   Of course Deep Mind's
>> practical demos, so far, embody only a small fraction of their ideas and
>> understanding...
>>
>>
>>>
>>> Further, Demis says in his talk they assume humans gain knowledge from
>>> experience, however the poverty of the stimulus argument proposed by
>>> Chomsky demonstrates clearly that humans acquire language faster than is
>>> possible given the limited stimuli they are exposed to.  As such (for some
>>> kinds of knowledge of the world at least) it seems that human knowledge
>>> acquisition is due in no small part to a priori instinctual knowledge,
>>> something they do not seem to be representing in their system.
>>>
>>
>>
>> While I agree that humans have some inborn "inductive bias" as well as
>> some specific hard-wired skills, the extent and nature of this bias and
>> hard-wiring in the context of language is certainly not well-understood
>> currently.   Derek Bickerton's writing on this topic has often been
>> interesting....  I note that using a deep network with a specific
>> architecture for language understanding is also a way of coding "inductive
>> bias" into one's architecture....   It is not clear how specific are the
>> inductive biases for language encoded into the human brain...  Old-style
>> Chomskian "principles and parameters" ideas are clearly not correct in
>> detail...
>>
>>
>>>
>>> Also even if Demis is up to speed on all the latest knowledge from the
>>> domains of the mind sciences (which he likely is not), it wouldn't be the
>>> case that he would know how the brain functions deterministically since
>>> this is still outside the scope of human knowledge.  As such he and his
>>> team can only guess at how the brain does intelligence.
>>>
>>
>>
>> Demis is a top-grade neuroscientist as well as an AGI guy, and many of
>> the Deep Mind folks are deeply into cognitive neuroscience.  They know the
>> latest research....   Which means they also know how incomplete that
>> research is, yeah...
>>
>> -- Ben
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>
>
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-- 
Ben Goertzel, PhD
http://goertzel.org

"The reasonable man adapts himself to the world: the unreasonable one
persists in trying to adapt the world to himself. Therefore all progress
depends on the unreasonable man." -- George Bernard Shaw



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