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See Drexler's mechanical nanotechnology from 1989.[1]

There's a minimum size at which such mechanisms will work, and it's bigger than transistors. This won't scale down to single atoms, according to chemists.

[1] http://www.nanoindustries.com/nanojbl/NanoConProc/nanocon2.h...

For things like machine learning I wonder how much extra performance could be squeezed out by simply working with continuous floating values on the analog level instead of encoding them as bits through a big indirect network of nands.

This is very interesting because according to one of the authors of the mechanical computing paper(personal communication) they never dynamically simulated the mechanisms. It was purely kinematic. So this web browser simulation is new work. Reversibility might disappear once dynamics are modelled.

Actually kinda impressive that a current CPU is "only" 9 orders of magnitude from the ridiculously low theoretical minimum energy needed per "floating point operation" (kinda fuzzy, but who's counting at 9 orders of magnitude?). The efficiency difference between the first computers and SOTA CPUs is probably more than 9 orders of magnitude - actually, it seems to me that it's in the ballpark of 9 orders of magnitude.

This is the concept behind the computers in The Diamond Age right ? Or am I mistaken ?

These simulations are great. With the balance example if you move the clock back and forth at resonance frequency, you can get it really twisted up so it doesn't work: https://postimg.cc/xXFgbxtn

A great pedagogical article on thermodynamic vs logical reversibility, for those interested: https://arxiv.org/abs/1311.1886 (Sagawa 2014).

I love this, I have a friend who has a 3d printer and we started looking at the repo for this project to print the mechanical shift register and play with a physical toy representation of storing a bit of data: https://github.com/mattmoses/MechanicalComputingSystems

Edit: I love that other people are thinking about this around now

Now that I think of it, if using damped springs, the system would not be reversible. Energy is dissipated through the damping, and the system will increase in entropy and converge on a local energy minimum point.

Another way of looking at it: there are 4 states going in (0 or 1 on 2 pushers) but there are only 2 states of the 'memory' contraption, so you lose a bit on every iteration (like classical Boolean circuits)

Classical reversible computing feels like it would be a good way to interface with a quantum computer (since it's also reversible in theory).

for the silicon kind of reversible computing, see vaire.co. they're in tapeout.

My most exciting prediction is that we'll be able to some day have Optical Computing LLMs, where we grow crystals (instead of silicon wafers) such that they contain wave-guides in which a single ray of light is what makes up each "input" into a Neural Net, and as it shines thru, it does the "logic" of a MLP. The summation part is not hard because light naturally superposes to "add", but the multiplications and activation functions will be the hardest part.

But ideally once manufactured, a given LLM "model" will be a single solid crystal, such that shining an array of beams into it, will come out the other end of this complex crystal as an "inference" result. This will mean an LLM that consumes ZERO ENERGY, and made of glass will also basically last forever too.

We already have Optical Chips but they don't quite do what I'm saying. What I'm saying is essentially an "Analog LLM" where all the vector adds, mults, and tanh functions are done by the light interactions. It seems possible, but I think it's doable.I think there should theoretically be a "lens shape" that does an activation function, for example. Even if we have to do the multiplications by conventional chips, in a hybrid "silicon-wave system" such an "Analog Optical LLM" would still have huge performance and energy savings, and millions of times faster than today's tech.

And being based on light, could utilize quantum effects so that the whole thing can become a Quantum Computer as well. We could use effects like polarization and photon spin perhaps to even have 100s of inferences happening simultaneously thru a given apparatus, as long as wavelengths are different enough to not interact.

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> Specifically, the Landauer’s principle states that all non-physically-reversible computation operations consume at least 10^21 J of energy at room temperature (and less as the temperature drops).

Wow! What an absurd claim!

I checked the Wikipedia page and I think you actually meant 10^-21 J :)

A big problem with the idea of physical reversible computing is the assumption that you get to start with a blank tape. Blank tapes are trivial to acquire if I can erase bits, but if I start with a tape in some state, creating working space in memory reverisbly is equivalent (identical) to lossless compression, which is not generally achievable.

If you start with blank tape then it isn't really reversible computing, you're just doing erasure up front.