[FRIAM] A pretty cellular automata video

[Marcus Daniels]

Companies like Mythic and IBM have developed analog devices for energy- efficient deep learning.   Noise and low precision are often used as part of ML training protocols anyway.    Here they did careful side-by-side testing to quantify the impact of going analog.

https://www.frontiersin.org/articles/10.3389/fncom.2021.675741/full

Or perhaps the proposition is that CS people (for example) can’t appreciate complexity that where the generative rules are unknown or obscure?   Sure that horse is fast, but how can I put a new engine in it?

On Oct 1, 2021, at 12:58 AM, David Eric Smith <desmith at santafe.edu> wrote:

 Doh!

I’m such a dolt, watching the pretty pictures.

They’re both Turing complete, correct?  Is there a natural sense of writing a program that, in that algorithmic representation, you know is somehow algorithmically deep in 110, which then becomes something algorithmically interesting under the corresponding representation in Life?  If one did that, would all the constructions be so forced that it was tedious and not elucidating of anything?  One is better to run “analog” and just relish the evident generative complexity?

Eric



On Sep 30, 2021, at 5:33 AM, Steve Smith <sasmyth at swcp.com<mailto:sasmyth at swcp.com>> wrote:

Jon -
https://www.youtube.com/watch?v=P2uhhAXd7PI&ab_channel=ElliotWaite


I never cease to be surprised and fascinated watching simple rules generate complex structure and dynamics.

I had a lot of complex reactions to this but I won't waste anyone's bandwidth with my reflective rambling...

Thanks for sharing...

- Steve


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