
Pathways to Cellular Supremacy in Biocomputing - hardmaru
https://www.nature.com/articles/s41467-019-13232-z
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dnautics
As someone who spent 10 years at the forefront of synthetic biology (and has
programmed for 30+ years) I always found the biocomputing baffling. I would be
willing to bet against Cellular Supremacy over any time frame, except
evolutionary or geologic timeframes.

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api
Your brain consumes about 40 watts and you wrote that sentence.

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dnautics
why do you assume that writing that sentence was computationally hard?

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ThisIBereave
the closest computational equivalent to writing that sentence we have today
involves executing a model with 1.5 billion parameters. (and I couldn't find
an estimate of the energy cost of that)

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api
It's many orders of magnitude larger than 40 watts * 5 seconds. :)

I have a running bet with some friends that one of the following is true:

(1) The brain is somehow leveraging quantum computing to achieve polynomial or
square root acceleration on combinatorial search and optimization problems.

(2) P=NP and there exist polynomial time classical algorithms for these
problems.

(3) The naturalistic hypothesis fails and intelligence is somehow
"supernatural" and does things that cannot be described or modeled within the
confines of physical space-time.

I cannot think of any alternative that can possibly explain how the brain can
do what it does on ~40 watts. Everything we have learned to date argues that
intelligence and cognition involves a whole lot of massive combinatorial
problems that can't possibly be performed classically on so little power.

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3455er
The brain is not a von-neumann architecture.

We have different architectures that can perform computation million times
more efficiently than general computers. Of course, they lose on other axes
(like precision).

Whats 54398456905 * 23423645745? Your 40 W brain can't compute that in a
minute, yet a 0.01 W calculator can in a millisecond.

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api
We can build less accurate computers and analog computers. Neither of these
even begin to approach what brains can do. A self-driving car's computer takes
hundreds of watts to run, uses reduced precision and custom silicon wherever
possible, and does not begin to approach the navigational ability of a mouse
or bird whose brain consumes less than one watt of power.

The human brain didn't evolve to perform consciously explicit and exact
calculations on huge numbers, but our navigational and positional awareness
abilities do far more impressive things with far more data much faster than
this. A monstrous amount of effective but subconscious number crunching is
involved in being aware of where your body is in space using nothing more than
vision and sensorimotor feedback, taking apart auditory input (including FFT-
like transforms), etc.

I really think CS people suffer from Dunning-Kreuger when they hand wave
around the impressiveness of biological systems. Study some actual biology and
neuroscience. What biological systems do as a normal part of metabolism and
cognition is as awesome and mind-blowing as the vast energies, times, and
distances found in astronomy. Computers are specialized devices that perform
impressive feats of specialized computation but they do not even approach what
biological systems do in terms of total data throughput per unit energy,
learning ability, or associative and versatile memory to name just a few.

Edit: computers seem so impressive to us because we built them specifically to
do the things we didn't evolve to do very well, but I have little doubt that
if there were some kind of evolutionary forcing function selecting us for
conscious explicit number crunching ability we would not need computers and
wouldn't have built them.

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tehsauce
> A self-driving car's computer takes hundreds of watts to run, uses reduced
> precision and custom silicon wherever possible, and does not begin to
> approach the navigational ability of a mouse or bird whose brain consumes
> less than one watt of power.

I would not trust the brain of a mouse or a bird to drive me in a car. Also
the self-driving car computers which take hundreds of watts to run do not take
advantage of custom silicon to the greatest possible extent, because the
relevant algorithms are evolving rapidly. There is probably at least an order
of magnitude or two of power efficiency that can be gained with current
systems if the algorithms were truly baked into the chips.

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api
I wasn't comparing performance at a specific task but performance at tasks of
equal or greater difficulty.

Mouse and bird brains have evolved to operate mouse and bird bodies, not cars,
and their learning ability isn't as powerful as a primate or a human so I
doubt they could learn to drive a car as well as us or our specialized self-
drive computers.

But... what they _do_ manage in terms of controlling mouse and bird bodies is
_vastly_ more sophisticated and impressive than driving a car. A mouse runs
around on four independently controlled legs and can tackle a vast array of
terrains while dodging or chasing moving objects. Birds can navigate in 3d
space while flying with articulated flapping wings with complex control
surfaces operated by dozens of muscles.

Driving a car is ridiculously easy compared to anything like that. If mouse
and bird brains had evolved to control cars I'd absolutely trust them to drive
me around at least as much if not more than I trust a Tesla's autopilot.
Driving is a simpler problem than operating a mouse body.

Don't get me wrong: our self-drive AIs are amazing engineering achievements.
I'm just pointing out the impressive performance of tiny brains using
fractions of a watt of power at much more difficult tasks.

The thing that blows my mind and makes me hypothesize quantum computing or
even P=NP is the power requirements of those brains. It's "impossible." I'm
not suggesting that we can't figure it out, just that we haven't yet and that
it's probably going to take more or different approaches than we think it will
take.

Immune systems were once considered so "impossible" that it led several
researchers to abandon science in frustration, but we eventually got a good
understanding of what was going on (and it's impressive!). Understanding
immune systems had to wait for molecular genetics and modern evolutionary
learning theory among other things. I suspect that really replicating brain-
like performance will have to wait for something as far beyond our current
state of the art as those were in the 1920s.

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ArtWomb
It appears that "Supremacy" isn't going away ;)

Overall, a very enjoyable read. As long as we are speculating on the limits of
bio-based computatbility, The same physical constraints governing inanimate
systems would of course apply to biochemical reactive systems.

What biologic does buy you is _reproduction_. An proclivity to seed machines
over a wide geographic or cosmic area that is self-propelling.

[https://en.wikipedia.org/wiki/Limits_of_computation](https://en.wikipedia.org/wiki/Limits_of_computation)

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Rexxar
This way to name things give me the impression that science is not any more
about advancing knowledge but about to find the most grandiloquent way to
speak about your work. All this "quantum supremacy" and now "cellular
supremacy" seems really disturbing.

As they propose the term in this article, I hope that someone will found a
better name. It's an interesting subject and it deserve a better name.

