Pamela,

I expect that they have! And I certainly hope so. I simply have not found them yet after some earnest looking. Can you please send me some references?? Right now I suspect that the heart of machine learning has the pearl, and I'm just now turning there.


And I'm optimistically suspicious that those entropic functionals that you find in information theory and that are built on top of conditional probability (relative entropy, mutual information, conditional entropy, entropy rate, etc.) hold promise...and that at the heart of machine learning they lay lurking - or could.

Anyway, thx for the note; and /please/ send me any related referernces!

Grant


On 8/8/17 11:20 AM, Pamela McCorduck wrote:
Grant, does it really seem plausible to you that the thousands of crack researchers at Stanford, Carnegie Mellon, Google, MIT, Cal Berkeley, and other places have not seen this? And found remedies?

Just for FRIAM’s information, John McCarthy used to call Asimov’s Three Laws Talmudic. Sorry I don’t know enough about the Talmud to agree or disagree.




On Aug 8, 2017, at 1:42 AM, Marcus Daniels <mar...@snoutfarm.com <mailto:mar...@snoutfarm.com>> wrote:

Grant writes:

"Fortunately, the AI folks don't seem to see - yet - that they are stumbling all over the missing piece: stochastic adaptation. You know, like in evolution: chance mutations. AI is still down with a bad case of causal determinism. But I expect they will fairly shortly get over that. Watch out."

What is probability, physically? It could be an illusion and that there is no such thing as an independent observer. Even if that is true, sampling techniques are used in many machine learning algorithms -- it is not a question of if they work, it is an academic question of why they work.

Marcus
------------------------------------------------------------------------
*From:*Friam <friam-boun...@redfish.com <mailto:friam-boun...@redfish.com>> on behalf of Grant Holland <grant.holland...@gmail.com <mailto:grant.holland...@gmail.com>>
*Sent:*Monday, August 7, 2017 11:38:03 PM
*To:*The Friday Morning Applied Complexity Coffee Group; Carl Tollander
*Subject:*Re: [FRIAM] Future of humans and artificial intelligence
That sounds right, Carl. Asimov's three "laws" of robotics are more like Asimov's three "wishes" for robotics. AI entities are already no longer servants. They have become machine learners. They have actually learned to project conditional probability. The cat is out of the barn. Or is it that the horse is out of the bag? Whatever. Fortunately, the AI folks don't seem to see - yet - that they are stumbling all over the missing piece: stochastic adaptation. You know, like in evolution: chance mutations. AI is still down with a bad case of causal determinism. But I expect they will fairly shortly get over that. Watch out. And we still must answer Stephen Hawking's burning question: Is intelligence a survivable trait?

On 8/7/17 9:54 PM, Carl Tollander wrote:
It seems to me that there are many here in the US who are not entirely on board with Asimov's First Law of Robotics, at least insofar as it may apply to themselves, so I suspect notions of "reining it in" are probably not going to fly.




On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez<alfr...@covaleda.co <mailto:alfr...@covaleda.co>>wrote:

    Future will be quite interesting. How will be the human being of
    the future? For sure not a human being in the way we know.

    
http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158
    
<http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158>

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