Epstein Secrets

From: Joscha Bach To: Jeffrey Epstein <[email protected]> Subject: Re: Date: Fri, 09 Mar 2018 16:33:27 +0000 What do you think of as space/field effects? The universe or learning?

s space/field effects? The universe or learning? Btw., did you ever come across Schmidhuber's idea of a Goedel lachine? > On Mar 9, 2018, at 05:39, jeffrey E. <[email protected]> wrote: > I would think of it more of a space / field effects , Not recursive algorithm s > On Fri, Mar 9, 2018 at 6:06 AM Jos

From: Joscha Bach To: Jeffrey Epstein <[email protected]> Subject: Re: Date: Fri,

From: Joscha Bach To: Jeffrey Epstein <[email protected]> Subject: Re: Da

out the functionality by themselves. Second order AI is automated function approximation. Learning has existed for a long time in AI of course, but Deep Learning means compositional function approximation. > Our current approximator paradigm is mostly the neural network, i.e. chained normalized weighted sums

From: Joscha Bach < Sent: Saturday, March 10, 2018 1:52 AM To: Jeffrey Epstein Subject: Re: Attachments: signature.asc Hmm. I'd say that there is a multidimensional space in which =nderstanding is projected. Understanding i

s a theory about models =uilt on constructionist formal languages, and I might get converted to =cott Aaronson's views. > On Mar 9, 2018, at 12:08, jeffrey E. <[email protected]> wrote: > understanding is a multi dimensional space the language is a =rojection in that space. or an arrow in category theor

: Saturday, March 10, 2018 1:52 AM To: Jeffrey Epstein Subject: Re: Attachments: signature.asc Hmm.

< Sent: Saturday, March 10, 2018 1:52 AM To: Jeffrey Epstein Subject: Re: Attachments: signature.a

out the functionality by themselves. =econd order Al is automated function approximation. Learning has =xisted for a long time in Al of course, but Deep Learning means =ompositional function approximation. > Our current approximator paradigm is mostly the neural network, i.e. =hained normalized weighted sums

From: Joscha Bach c:e. To: Jeffrey Epstein <[email protected]> Subject: Re: Date: Fri, 09 Mar 2018 05:05:59 +0000 Last week I got to know Steve Hyman, Daniel Kahneman and Bob Horvitz. T

From: Joscha Bach c:e. To: Jeffrey Epstein <[email protected]> Subject: Re: Date: Fri,

From: Joscha Bach c:e. To: Jeffrey Epstein <[email protected]> Subject: Re: Da

out the functionality by themselves. Second order Al is automated function approximation. Learning has existed for a long time in AI of course, but Deep Learning means compositional function approximation. Our current approximator paradigm is mostly the neural network, i.e. chained normalized weighted sums of

as lucky with the new landlords as with the previous ones. Bests, and thank you for everything! Joscha EFTA00863127 > On Mar 8, 2018, at 16:37, jeffrey E. <[email protected]> wrote: > progress? > -- > please note > The information contained in this communication is > confidential, may be attorney

From: "Jeffrey E." <[email protected]> To: Joscha Bach <,

out the functionality by themselves. Second order AI is automated function approximation. Learning has existed for a long time in AI of course, but Deep Learning means compositional function approximation. Our current approximator paradigm is mostly the neural network, i.e. chained normalized weighted sums of

s space/field effects? The universe or learning? Btw., did you ever come across Schmidhuber's idea of a Goedel Machine? > On Mar 9, 2018, at 05:39, jeffrey E. <[email protected]> wrote: > I would think of it more of a space / field effects , Not recursive algorithm s > On Fri, Mar 9, 2018 at 6:06 AM Jos

out the functionality by themselves. Second order Al is automated function approximation. Learning has existed for a long time in AI of course, but Deep Learning means compositional function approximation. > Our current approximator paradigm is mostly the neural network, i.e. chained normalized weighted sums

From: jeffrey E. <[email protected]> Sent: Friday, March 9, 2018 10:40 AM To: Joscha Bach Subject: Re: I would think of it more of a space / field effects =

out the functionality by themselves. Second ord=r Al is automated function approximation. Learning has existed for a long =ime in Al of course, but Deep Learning means compositional function approx=mation. Our current approximator paradigm is mostly the neural network, i.e. chaine= normalized weighted sums of

From: jeffrey E. <[email protected]> Sent: Friday, March 9, 2018 5:09 PM To: Joscha Bach Subject: Re: understanding is a multi dimensional space the langua

out the functionality by themselves. Secon= order Al is automated function approximation. Learning has existed for a =ong time in Al of course, but Deep Learning means compositional function a=proximation. > Our current approximator paradigm is mostly the neural network, i.e. c=ained normalized weighted sums