Feynman is not as expert on the topic as he is on his core research, but his gift for great explanation carries over and makes the material more accessible. The lectures are ground in thermodynamics and the related information theories, and there's a very accessible lecture in there too about Maxwell's Daemon. Most of the material is very foundational and still correct, so it's a good read for anyone who is interested in the area. I'm glad I read it before I had to deal with more complicated and statistical approaches to computation and entropy.
Fenyman worked with Thinking Machines on their first supercomputer, The Connection Machine in the 80s. Here's some great background and anecdotes from the founder, Danny Hillis:
Adjacent work from Fields & Levin 2021 on the thermodynamics of cellular process, arguing that due to the information processing demands and classical thermo minimal power requirements per operation for loose estimates of protein control, aggregate cellular metabolism power requirements are off by 10-15 orders of magnitude of available. They then conclude that cellular processes are using quantum coherent processes for major work internally and externally (p17).
If you like physics and you haven't watched Sabine, you're missing out. She discusses recently published research in an entertaining and accessible manner while also doing a good job of touching on more advanced aspects pertinent to the topic at hand. She's great at covering the skeptic's perspective (she usually takes that perspective herself) and playing Devil's advocate, especially when it comes to anything adjacent to her life's work in particle physics.
Ironically, the video is a skeptic's attempt at a balanced review of a published paper, and the paper, which makes its argument in text, is way more bullshit than the video's verbal discussion of it.
If Levin wouldn't produce so much fluff on pseudoscientific concepts like "selves" and "computational psychiatry", he would have had the mice regenerate better and already proceed to humans, like Sinclair.
How would quantum theory explain the thermodynamics of increased mental clarity reported by humans on 3-5 day of fasting induced ketosis? Or multiple biocomputational benefits of mTOR inhibition (by e.g. rapamycin for longevity purposes), reduced rate of metabolism?
Extrapolating to modern mechanotech, this would be similar to an airplane flying faster and better upon regular reduction of fuel to it. Imagine a computer running more loads and faster upon regular reduction of AC power to it. Thus linear application of thermodynamics seems rather ridiculous and quantum theory may not save, because it disintegrates beyond the Plank's scale.
Biology is not a simple linear physical equation. We have buffers. There's a lot of balancing mechanisms inside and altering your food supply can change the state your body operates in. Or if I may try this naive comparison, when I drive my car and use brakes, I slow down up until a point the engine starts to reaccelerate. The ECU adapts to reallocate more energy because going too slow would "kill" the engine. For a computer, fasting would be like reaching memory pressure so high, your OS garbage collects/flush caches and then programs suddenly runs better.
ps: not that I like all of Levin's work, I do admit that his tendency to abstract into grand ideas is not helping, but I think the morphogenesis/gap-junctions part of his work is still very interesting and straightforward.
Yes, biology is not as simple. With mTOR inhibition fasting is not a full story. mTOR is a sensor of food (amino acids) and a master regulator of growth signals. mTOR is inhibited naturally by fasting and artificially by drugs like rapamycin. And rapamycin is currently a winner in life/health extension across species (Matt Kaerbelin, Rich Miller from theDrive podcast). So with rapamycin inhibiting mTOR (or other fasting mimetic drugs) it's enough to only _send_a_signal_ of low energy/food to the biosystem to obtain gains in health and reverse biological time. So your analogy fits best here, as you are only using signals.
While with fasting it is a reduction of actual food/fuel. Garbage collection can be comparable to fasting-induced autophagy, but in fasting it is also an absence of growth signals like IGF-1 that provides gains in health function (though Greg Fahy research on thymus regeneration in humans with a mix including a growth hormone may contradict this).
The majority of Levin's work in developmental biology done in embryos, which are naturally a highly flexible tissue and naturally express high levels of Yamanaka genes, which are now used for epigenetic reprogramming (OSK). Growing eyes on the tadpole's tail is cool, but I want to grow a tooth for myself now.
Sinclair is now using epigenetic regprogramming with OSK (developmental) genes to effectively regrow the severed optic nerve in primates and proceeding to humans. Levin has mouse paws cut off in a similar way and regrows them in a wearable bioreactor with a mix of drugs, which include not only "electroceuticals" (ion channel modulators), but probably also some (growth) hormones or hormone precursors (as he mentioned in a podcast they may use some estrogen precursor).
Yea, they regenerate ~70% of the whole paw with multiple tissues, but the end result seems the same if it would be obtained by OSK reprogramming.
In a recent podcast #300 Attia was again mentioning the rather reliable benefits of caloric restriction. So thermodynamically it still seems ridiculous that by reducing the inflow of energy (at least the one of the most well-known type) the biological (and presumable computational) efficiency is increased at literally no cost.
if you find this interesting you'll also find the publications of J.P Cruthfield interesting, he seem to have worked in this same institute up to 2004 before moving to UC Davis. he has 20+ years worth of papers on the topic, I keep procrastinating reading them esp the ones about what he calls epsilon machines.
I don't really understand this topic, but find the premise interesting enough.
From a boolean logic point of view - AND is irreversible, since (1 .AND. 0) is 0, as is (0 .AND. 0.) Going from the result (0), you can't reverse and get the starting inputs.
NOT however is reversible, since 1 .NOT. -> 0, and you can get back to 1 with another .NOT.
In a certain way you could say you can integrate AND
For example 1 AND 0 = 0
Now if I only have 0 as a result, it means one of the arguments was 0, and the other is either 0 or 1
So the “integral” of AND(0,x) = 0, is (0, (either 0 or 1)) or just x = (either 0 or 1)
[0 or 1 meaning one means either. It doesn’t mean 0 OR 1, which would be 1]
This is analog to the result of an integral being expressed as a function + C (constant). The C part is the uncertainty of the result, just like having (0 or 1) for AND
The (0 or 1) part can also be expressed as a probability distribution, for example p(0)=0.5,p(1)=0.5 which then you can use to “sample” the integral of AND by randomly taking a (0 or 1) and using it as argument to AND(0, x)
Is SFI alive after all his founders are long gone? I think so, but really it is increasingly difficult to discern its current unique contribution to the global scientific landscape.
From the headline, I thought this was yet another attempt by some silicon valley bro to handwave furiously about everything being thermodynamics. Thankfully, this was not the case.
I'm kinda surprised nobody's done this before, given how important estimating wastage is.
The thermodynamic "limit" is pretty small compared to any other waste in a system (from Wikipedia):
> At room temperature, the Landauer limit represents an energy of approximately 0.018 eV (2.9×10^−21 J). Modern computers use about a billion times as much energy per operation.
The Landauer principle gives a lower bound for the energy needed for computation (specifically, irreversible information erasure). Is it possible that there is a heretofore undiscovered lower bound that is higher?
As an aside, modern computers perform computation like a car with square wheels --- in discrete steps, where all your energy is irreversibly discarded in each step. Theoretically, reversible computing [1] can do useful work with less energy without needing to erase information.
Every computing system, biological or synthetic, from cells to brains to laptops, has a cost. This isn’t the price, which is easy to discern, but an energy cost connected to the work required to run a program and the heat dissipated in the process.
Researchers at SFI and elsewhere have spent decades developing a thermodynamic theory of computation, but previous work on the energy cost has focused on basic symbolic computations — like the erasure of a single bit — that aren’t readily transferable to less predictable, real-world computing scenarios.
If you're going to directly quote the first two paragraphs of the article, it's generally considered good form to indicate you're quoting from the article (for example by starting your text with ">")
https://www.amazon.com/Feynman-Lectures-Computation-Frontier...
Feynman is not as expert on the topic as he is on his core research, but his gift for great explanation carries over and makes the material more accessible. The lectures are ground in thermodynamics and the related information theories, and there's a very accessible lecture in there too about Maxwell's Daemon. Most of the material is very foundational and still correct, so it's a good read for anyone who is interested in the area. I'm glad I read it before I had to deal with more complicated and statistical approaches to computation and entropy.