Reverse Engineering a Neural Network's Clever Solution to Binary Addition

Re:Reverse Engineering a Neural Network's Clever Solution to... by kens on Monday January 16, 2023 @01:41PM (#34403991)

The trick of performing binary addition by using analog voltages was used in the IAS family of computers (1952), designed by John von Neumann. It implemented a full adder by converting two input bits and a carry in bit into voltages that were summed. Vacuum tubes converted the analog voltage back into bits by using a threshold to generate the carry-out and more complex thresholds to generate the sum-out bit.

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Re:Reverse Engineering a Neural Network's Clever Solution to... by elcritch on Monday January 16, 2023 @03:59PM (#34405396)

Nifty, makes one wonder if logarithmic or sigmoid functions for ML could be done using this method. Especially as we approach the node size limit, perhaps dealing with fuzzy analog will become more valuable.

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Re:Reverse Engineering a Neural Network's Clever Solution to... by djmips on Monday January 16, 2023 @04:08PM (#34405492)

There are a few startups making analog ML compute. Mythic & Aspinity for example

https://www.eetimes.com/aspinity-puts-neural-networks-back-t...

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Re:Reverse Engineering a Neural Network's Clever Solution to... by shagie on Monday January 16, 2023 @04:30PM (#34405744)

Veritasium has a bit of an video on Mythic - Future Computers Will Be Radically Different (Analog Computing) - https://youtu.be/GVsUOuSjvcg

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Re:Reverse Engineering a Neural Network's Clever Solution to... by westurner on Monday January 16, 2023 @11:52PM (#34409283)

From "Faraday and Babbage: Semiconductors and Computing in 1833" https://news.ycombinator.com/item?id=32888210 and then "Qubit: Quantum register: Qudits and qutrits" https://news.ycombinator.com/item?id=31983110:

>>> The following is an incomplete list of physical implementations of qubits, and the choices of basis are by convention only: [...] Qubit#Physical_implementations: https://en.wikipedia.org/wiki/Qubit#Physical_implementations

> - note the "electrons" row of the table

According to this Table on wikipedia, it's possible to use electron charge (instead of 'spin') to do Quantum Logic with Qubits.

How is that doing quantum logical computations with electron charge different from from what e.g. Cirq or Tequila do (optionally with simulated noise to simulate the Quantum Computer Engineering hardware)?

FWIU, analog and digital component qualities are not within sufficient tolerance to do precise analog computation? (Though that's probably debatable for certain applications at least, but not for general purpose computing architectures?) That is, while you can build adders out of voltage potentials quantified more specifically than 0 or 1, you might shouldn't without sufficient component spec tolerances because noise and thus error.

IMHO, Turing Tumble and Spintronics are neat analog computer games.

(Are Qubits, by Church-Turing-Deutsch, sufficient to; 1) simuluate arbitrary quantum physical systems; or 2) run quantum logical simulations as circuits with low error due to high coherence? https://en.wikipedia.org/wiki/Church%E2%80%93Turing%E2%80%93... )

>> See also: "Quantum logic gate" https://en.wikipedia.org/wiki/Quantum_logic_gate

Analog computers > Electronic analog computers aren't Electronic digital computers: https://en.wikipedia.org/wiki/Analog_computer#Electronic_ana...

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Re:Reverse Engineering a Neural Network's Clever Solution to... by crapaud23 on Tuesday January 17, 2023 @08:19AM (#34412035)

Analog pid controllers: https://www.youtube.com/watch?v=Ps9iD738rUg Soviet IR tracking missile heads too. Stumbled upon one on ebay once, was surprised the control system was analog. Not sure which one it was and I'm very surprised to find a Raytheon AIM 9 Sidewinder missile kit there: https://www.ebay.com/itm/273992271867

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Re:Reverse Engineering a Neural Network's Clever Solution to... by dilippkumar on Monday January 16, 2023 @11:58PM (#34409314)

> designed by John von Neumann.

I can strongly recommend an excellent biography:

The Man from the Future: The Visionary Life of John von Neumann by Ananyo Bhattacharya

I knew of von Neumann because his name shows up many many times when studying computers. But I had no idea he had several equally monumental bodies of work in such a wide range of subjects.

It’s that rare biography that helps understand the history of multiple different disciplines: quantum mechanics, game theory, computer science and more.

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Re:Reverse Engineering a Neural Network's Clever Solution to... by glitchc on Tuesday January 17, 2023 @10:35PM (#34423150)

There's a limit to this process. At a certain number of bits, the sum of voltages will be too high to represent safely. Yet adding more bits on a digital computer is trivial.

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