About the above linked Hassabis paper, Ben said, "It's sort of a high level
inspirational paper... it does lay down pretty clearly what sort of
thinking and approach Deep Mind is likely to be taking in the next years
... there are no big surprises here though as this has been Demis's
approach, bias and interest all along, right?"

>From my knowledge of several articles and videos by, or about, Hassabis --
 I totally agree.  But I am a little less ho-hum than Ben, perhaps because
I'm not as up on the current state of AGI as Ben.

Reading Hassabis's paper makes me bullish about how close we are to
powerful, if not fully human-level AGI, within 5 years.

Why?  Because all of the unsolved challenges Hassabis discusses seem like
they could be easily solved if enough engineering and programming talent
was thrown at them.  I feel like I could relatively easily -- within a few
months -- weave plausible high level architectural descriptions for solving
all of these problems, as, presumably, people like Demis and Ben could do
even better. (Perhaps that is why Ben is so ho-hum about the paper.)  With
the money that's being thrown into AGI, and the much greater ease of doing
cognitive architectural experiments made possible with Neural Turing
Machines -- which allow programmable, modular plug-and-play with
pre-designed and pre-trained neural net modules -- the world is going to
get weird fast.

Tell me why I am wrong.

On Sun, Jul 23, 2017 at 8:29 PM, Ed Pell <[email protected]> wrote:

> https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5467749/
>
>
> On 7/23/2017 4:18 PM, Giacomo Spigler wrote:
>
>>
>> An Approximation of the Error Backpropagation
>> Algorithm in a Predictive Coding Network
>> with Local Hebbian Synaptic Plasticity
>>
>
>
>
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