Epstein Secrets

From: Joi Ito < Sent: Saturday, April 23, 2016 2:04 PM To: Jeffrey Epstein Subject: Re: Ed's talk at Davos There isn't one as good as his talk at MIT but it's =retty good: https://www.youtube.com/watch?v=4fjmnOQuqao 340

't =se calculations like Deep Blue but gets to symbolic reason through =einforced learning on neural networks. -Joi > On Apr 23, 2016, at 9:35 AM, jeffrey E. <[email protected]> wrote: > Yes but not detailed > On Saturday, April 23, 2016, Joi Ito <-> wrote: > BTW, one smart guy I met recently is Demi

: Saturday, April 23, 2016 2:04 PM To: Jeffrey Epstein Subject: Re: Ed's talk at Davos There isn't on

< Sent: Saturday, April 23, 2016 2:04 PM To: Jeffrey Epstein Subject: Re: Ed's talk at Davos There

tch?v=4fjmnOQuqao 340M people watched the video of the match. Key thing is that AlphaGo is creative and intuitive. It doesn't =se calculations like Deep Blue but gets to symbolic reason through =einforced learning on neural networks. -Joi > On Apr 23, 2016, at 9:35 AM, jeffrey E. <[email protected]>

< Sent: Saturday, April 23, 2016 2:06 PM To: Jeffrey Epstein Subject: Re: Ed's talk at Davos This i

From: Joi Ito < Sent: Saturday, April 23, 2016 2:06 PM To: Jeffrey Epstein Subject: Re: Ed's talk at Davos This is good to see the the human players... this is after he won =he bigger champion more recently. https://www.

=se calculations like Deep Blue but gets to symbolic reason through =einforced learning on neural networks. > - Joi » On Apr 23, 2016, at 9:35 AM, jeffrey E. <[email protected]> =rote: » Yes but not detailed » On Saturday, April 23, 2016, Joi Ito <-> wrote: » BTW, one smart guy I met recently is Demi

: Saturday, April 23, 2016 2:06 PM To: Jeffrey Epstein Subject: Re: Ed's talk at Davos This is good t

v=4fjmnOQuqao > 340M people watched the video of the match. > Key thing is that AlphaGo is creative and intuitive. It doesn't =se calculations like Deep Blue but gets to symbolic reason through =einforced learning on neural networks. > - Joi » On Apr 23, 2016, at 9:35 AM, jeffrey E. <[email protected]

From: Ari Gesher < To: Jeffrey Epstein [email protected]> Subject: Re: MDF Date: Mon, 28 Oct 2013 15:02:08 +0000 Ok, that's what I thought you meant - so that totally makes sense wh

From: Ari Gesher < To: Jeffrey Epstein [email protected]> Subject: Re: MDF Date: M

From: Ari Gesher < To: Jeffrey Epstein [email protected]> Subject: Re: MDF

t can breach the bounds of the rules of the game. Given that, either brute force or ML/statistical approaches works well enough to build things like Deep Blue or the Google self-driving car. At Palantir (where I work), we have, to date, stayed away from heavy machine learning or algorithmic approaches to

From: Ari Gesher <[email protected]> To: Jeffrey Epstein Subject: Re: MDF Date: Mon, 28 Oct 2013 01:32:03 +0000 That sounds really interesting - can you explain that a bit more so I can unpack it further

From: Ari Gesher <[email protected]> To: Jeffrey Epstein Subject: Re: MDF Date: Mon, 28 Oct 2013 01:32:0

From: Ari Gesher <[email protected]> To: Jeffrey Epstein Subject: Re: MDF Date: Mon, 28 Oct 2013

t can breach the bounds of the rules of the game. Given that, either brute force or ML/statistical approaches works well enough to build things like Deep Blue or the Google self-driving car. At Palantir (where I work), we have, to date, stayed away from heavy machine learning or algorithmic approaches to

, Kevin Slavin Greg Borenstein <[email protected]> Subject: Re: MDF Date: Thu, 24 Oct 2013 00:10:24 +0000 talcashi ikegami Martin Nowak , Jeffrey Epstein On Oct 23, 2013, at 8:09 AM, Joscha Bach <1 > wrote: That being said, AGI will have trouble succeeding because it is following the scruffy tradit

+0000 talcashi ikegami Martin Nowak , Jeffrey Epstein On Oct 23, 2013, at 8:09 AM, Joscha Bach <1 > w

00:10:24 +0000 talcashi ikegami Martin Nowak , Jeffrey Epstein On Oct 23, 2013, at 8:09 AM, Joscha Bach

t can breach the bounds of the rules of the game. Given that, either brute force or ML/statistical approaches works well enough to build things like Deep Blue or the Google self-driving car. At Palantir (where I work), we have, to date, stayed away from heavy machine learning or algorithmic approaches to

From: Ari Gesher To: Jeffrey Epstein <[email protected]> Subject: Re: MDF Date: Thu, 24 Oct 2013 00:37:50 +0000 The adaptive adversaries in the immune system context are parasites

From: Ari Gesher To: Jeffrey Epstein <[email protected]> Subject: Re: MDF Date:

From: Ari Gesher To: Jeffrey Epstein <[email protected]> Subject: Re: MDF

t can breach the bounds of the rules of the game. Given that, either brute force or ML/statistical approaches works well enough to build things like Deep Blue or the Google self-driving car. At Palantir (where I work), we have, to date, stayed away from heavy machine learning or algorithmic approaches to

References IIJ Richard P. Gabriel, Jilin Chen, Jeffrey Nichols, InkWell: A Creative Writer's Creative A

competition because of pancreatic cancer.) Chinook had no machine learned aspects. EFTA_R1_02074941 EFTA02702510 In 1997, Garry Kasparov lost to Deep Blue at chess—Kasp- arov was the reigning world chess champion. In one pivotal game Kasparov remarked on the "superior intelligence" of the machine duri

that breeds risks. It acts in ways that the designer could not have predicted in advance. “Clearly the system itself is misbehaving,” the researcher Jeffrey Mogul writes of his study of various cases where networks are cracked in this fashion. “However, none of the components have failed per-se.”!45 The

creators were limiting what it had been asked to do. At which point the AI would turn to thinking about how to escape those bounds. It would be like Deep Blue programmed to plan its own prison break. And as much as humans might try to stifle a smart machine, we’d be fighting to contain something more powerf