Re: Memristor cross bar arrays for faster AI neural nets and math?

Jeroen Belleman wrote:

Don wrote:

Jan Panteltje wrote:

Jeroen Belleman wrote:

Jan Panteltje wrote:

Source:
University of Massachusetts Amherst
Summary:
A team of engineers has proven that their analog computing device, called a
memristor, can complete complex, scientific
computing tasks while bypassing the limitations of digital computing.
   https://www.sciencedaily.com/releases/2024/03/240314145325.htm
>
bit like our neural nets...

>
I have an issue with calling a memristor a 'computing device'. If

>
If you can do matrix computations with it why not?
quote from that llnk:
  "When organized into a crossbar array,
   such a memristive circuit does analog computing by using physical laws
   in a massively parallel fashion, substantially accelerating matrix operation,
   the most frequently used but very power-hungry computation in neural networks
   "
>

If you accept that, then so are capacitors and inductors!

>
Well you could store analog info in CMOS too, even in capacitors.
Inductors? not so sure, not so easy for a long time?

>
Does core memory qualify as inductors?

>
Memory cores have a very wide hysteresis. You need a fair bit of
current to magnetize them, and when they do, they go straight into
saturation and stay there when the current is removed. You have to
reverse the current to magnetize them the other way and again will
flip the whole way.
>
That's why they were useful as memory. As inductors, not so much.

Well said! This take on the Two-Capacitor Paradox ironically illustrates
intrisic inductance:

Learning from the Two-Capacitor Paradox: Do Capacitance and Inductance Exist?
<https://www.comsol.com/blogs/learning-from-the-two-capacitor-paradox-do-capacitance-and-inductance-exist>

Danke,

--
Don, KB7RPU, https://www.qsl.net/kb7rpu
There was a young lady named Bright Whose speed was far faster than light;
She set out one day In a relative way And returned on the previous night.