[TriEmbed] ARM computer quantity discount

John Vaughters jvaughters04 at yahoo.com
Tue Nov 13 10:04:43 CST 2018


 No doubt that quantum computers are interesting, but the TRUE problem with AI is we do not really understand how the brain works yet. So far history has provided us with nothing but failure of big claims. I believe that trend will continue. Biology is extremely complex. Scientists over simplify mainly because we lack necessary knowledge of how things work. The good news is in each epic failure of HUGE claims, we get more knowledge and very useful tools. For instance, they now have visual processing that can identify skin cancer. This is touted as AI. I disagree. It's advanced visual processing that can compare it's learning and make a decision. While impressive as a learned response decision, it is not abstract thought. It is however what we expect from computers. The ability to enhance our lives through tasks more suited to computers.
I'm not against the idea we will one day conquer true AI, but I do believe it will be long after anyone reading this email is alive. Why? The history is long on this goal and the progress is extremely slow.
So rest easy the Terminators are not coming just yet `,~)
John Vaughters
    On Tuesday, November 13, 2018, 10:24:33 AM EST, Gregg Tracton via TriEmbed <triembed at triembed.org> wrote:  
 
 
That is why quantum computers are so exciting: the structure of "holographic" computing is far superior to neurons, much faster than even a neutron net (like by billions), and the interconnects can be controlled by software (rather than neurons that are mostly hard-coded).  Plus, it's hard to get multiple brains to work together, but easy for computers, even at the board level.
And if we were to compare apples to apples, then the basic computing element in brains would be the molecule (like dopamine), not the neurons that accumulate them and trigger switches.  Neurons are more at the level of ALUs or even DSPs, not transistors.
--gregg
On Tue, Nov 13, 2018 at 8:17 AM John Vaughters via TriEmbed <triembed at triembed.org> wrote:



Interesting article. 

Regarding this quote from the article:

"One of the first fundamental differences between the brain and computers is how their “smallest units” function. Brain neurons can have multiple connections and react to impulses in a range of different ways. Computer transistors, by comparison, are switches that, while can be connected to other transistors, can only have one of two states."


This is the problem. Trying to simulate biologic structure with silicon. Highly inefficient and structurally different. Biology is just better than what we can create at this time. I'm not convinced electronics will ever be able to simulate a brain, but it is a very interesting approach and we can certainly learn from it. Not a new idea, but very cool to see this scale.

John Vaughters



On Friday, November 9, 2018, 6:25:36 PM EST, Pete Soper via TriEmbed <triembed at triembed.org> wrote: 







U of Manchester probably got a price break for this new machine they've made:

    SpiNNaker Million-Core Supercomputer

-Pete



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