[FRIAM] New ways of understanding the world

Mon Nov 30 17:26:14 EST 2020

Let’s say I provide you with a string of random numbers copied from the best random number table you care to offer.  No, we go to Jon, and holding the table in our laps, we correctly guess every number in the sequence.  Were those numbers random?  Or to make it  even easier, let Jon make a judgement of the randomness of the sequence and then let the sequence recycle and repeat it self exactly.  

I know that these are “citizen” questions.  I have never quite grasped the concept of randomness (as you see). 

Nick 

Nicholas Thompson

Emeritus Professor of Ethology and Psychology

Clark University

 <mailto:ThompNickSon2 at gmail.com> ThompNickSon2 at gmail.com

 <https://wordpress.clarku.edu/nthompson/> https://wordpress.clarku.edu/nthompson/

From: Friam <friam-bounces at redfish.com> On Behalf Of Frank Wimberly
Sent: Monday, November 30, 2020 4:12 PM
To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com>
Subject: Re: [FRIAM] New ways of understanding the world

Hmm.  Every third number in this apparently random sequence is even.  Order?  What's order? Nonrandomness?

On Mon, Nov 30, 2020 at 2:25 PM <thompnickson2 at gmail.com <mailto:thompnickson2 at gmail.com> > wrote:

All, 

I feel like this relates to a discussion held during Nerd Hour at the end of last Friday’s vfriam.  I was arguing  that given, say, a string of numbers, and no information external to that string, that no AI could detect “order” unless it already possessed a theory of what order is.  I found the discussion distressing because I thought the point was trivial but all the smart people in the conversation were arguing against me. 

n 

Nicholas Thompson

Emeritus Professor of Ethology and Psychology

Clark University

 <mailto:ThompNickSon2 at gmail.com> ThompNickSon2 at gmail.com

 <https://wordpress.clarku.edu/nthompson/> https://wordpress.clarku.edu/nthompson/

From: Friam <friam-bounces at redfish.com <mailto:friam-bounces at redfish.com> > On Behalf Of Jochen Fromm
Sent: Monday, November 30, 2020 3:15 PM
To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com <mailto:friam at redfish.com> >
Subject: Re: [FRIAM] New ways of understanding the world

The success of Google's deep learning program in predicting protein folding is impressive. Maybe that is what he meant.

https://www.nature.com/articles/d41586-020-03348-4

-J.

-------- Original message --------

From: Steve Smith <sasmyth at swcp.com <mailto:sasmyth at swcp.com> > 

Date: 11/30/20 21:55 (GMT+01:00) 

To: friam at redfish.com <mailto:friam at redfish.com>  

Subject: Re: [FRIAM] New ways of understanding the world 

Or a "model of nothing fit to everything we know: useful or merely wrong?"

On 11/30/20 1:41 PM, Jochen Fromm wrote:

Chris Anderson, the editor in chief of Wired, asks if a computer can find a theory of everything merely by learning from data. Unfortunately most deep learning models are like a black box which delivers good results but is hard to understand. Would a theory of everything be a theory of nothing? It reminds me of Russell Standish's book "theory of nothing".

https://www.wired.com/2008/06/pb-theory/ 

-J.

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Frank Wimberly
140 Calle Ojo Feliz
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505 670-9918

Research:  https://www.researchgate.net/profile/Frank_Wimberly2

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