I remembered that Hinton is enthusiastic about what he is doing. The last
line of the paper read:

"Ultimately, major progress in artificial intelligence will come about
through systems that combine representation learning with complex
reasoning. Although deep learning and simple reasoning have been used for
speech and handwriting recognition for a long time, new paradigms are
needed to replace rule-based manipulation of symbolic expressions by
operations on large vectors."

I disagree with the sense of this statement although I realize that he is
referring to old rule-based paradigms where the rules are written
individually and never learned by the program though 'experience'.

So maybe one of the other writers is or will be a great teacher who
realizes that some intuitive explanations, using pictures and text, will
help the student to get it.
Jim Bromer


On Wed, Nov 11, 2015 at 8:06 PM, Jim Bromer <[email protected]> wrote:

> What a great article. Hinton must be a great teacher.
>
> Jim Bromer
>
> On Wed, Nov 11, 2015 at 8:04 PM, Jim Bromer <[email protected]> wrote:
>
>> On Mon, Nov 9, 2015 at 3:34 PM, Robert Mash <[email protected]>
>> wrote:
>>
>>> I found this linked review of the state of the art in deep learning by
>>> Hinton/LeCun/Bengio in the Tensor Flow announcement.
>>> http://www.cs.toronto.edu/~hinton/absps/NatureDeepReview.pdf
>>>
>>
>> Thanks for that link. I wish I could build a simple deep learning network
>> just to see how it works even though I am not super impressed by them.
>>
>> Jim Bromer
>>
>>
>> On Mon, Nov 9, 2015 at 3:34 PM, Robert Mash <[email protected]>
>> wrote:
>>
>>> I found this linked review of the state of the art in deep learning by
>>> Hinton/LeCun/Bengio in the Tensor Flow announcement.
>>> http://www.cs.toronto.edu/~hinton/absps/NatureDeepReview.pdf
>>>
>>>
>>>
>>> On Nov 9, 2015, at 12:10 PM, Peter Christiansen <[email protected]>
>>> wrote:
>>>
>>>
>>> http://www.popsci.com/google-ai?src=SOC&dom=fb
>>>
>>>
>>> Sent from my iPad
>>>
>>>
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