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May well turn out later on that AI is best modeled for speed and detail at 11 bit resolution - after all - evolution has done a lot of work that we equate as ma

by Zenst 7y ago

May well turn out later on that AI is best modeled for speed and detail at 11 bit resolution - after all - evolution has done a lot of work that we equate as machine learning. Also interesting that 11 is also a prime number. But equally, may just be one of life's coincidences and the human drive to see patterns and understand exactly what is going on - a trait that still advances humanity today.

jayd16 7y ago
Evolution also determined a giraffe's lyrngeal nerve should detour down the neck and back.
- jacquesm 7y ago
  Apparently the signal arrived too early so a delay loop was spliced in. Score one for ID.
  - therein 7y ago
    When the giraffe class was first released it was too OP with its tall neck, allowing it to access food previously unreachable to many other classes while also being able to keep an eye on predators lurking at distance. Upon next evolutionary tick, it had to be nerfed.
    - mockingbirdy 7y ago
      For anyone who doesn't get the reference: Watch TierZoo [1]. Hilarious and informative, especially for gamers. [1]: https://www.youtube.com/watch?v=6xbQ2WbTp0E https://www.youtube.com/watch?v=6xbQ2WbTp0E
fucking_tragedy 7y ago
> May well turn out later on that AI is best modeled for speed and detail at 11 bit resolution - after all - evolution has done a lot of work that we equate as machine learning. I don't see gradient descent or back propagation in biology.
- Zenst 7y ago
  Maybe not yet, but for example gradient descent - https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0219004 https://journals.plos.org/plosone/article?id=10.1371/journal... As for back propagation, I'm sure there are aspects in nature in which translate - maybe the nerves system of some species. Way to see it is that evolutionary change of any form could in theory be modeled in machine learning. There may be aspects of evolution and how it operates that help refine how we do machine learning.
- salty_biscuits 7y ago
  Well for gradient ascent you have this. https://en.wikipedia.org/wiki/Chemotaxis https://en.wikipedia.org/wiki/Chemotaxis
- ianai 7y ago
  iirc, back propagation sounds similar in inspection to some of the processes seen in sleeping brains. Ie what they see in MRIs looks like what back propagation might look like from outside. But I’m really not comfortable enough with these terms to speak about them.
- DoctorOetker 7y ago
  The jury is still out on back-propagation (i.e. reverse accumulation automatic differentiation) within the brain (retrograde signalling from the post-synaptic neuron to the pre-synaptic neuron may still be discovered and turn out to approximate RM AD) But regarding evolution implementing back-propagation, I agree that is just bonkers, as it would require cells to back-propagate in time information about death or procreation! If our biology implements information time machines, biology would be a lot weirder than it is (and it would imply that we could use that by sequencing an organisms genome (or ensemble of them) to read from the future, and keeping it fed without allowing reproduction, and later when we want to write information back either kill or let it reproduce). That's just plain nonsense. There can't be back-propagation in evolution without biological time-travel of information. And machine learning without back-propagation is basically a genetic algorithm, so the claim that "evolution has done a lot of work that we equate as machine learning" would then reduce to a widely accepted fact that nobody disputes and is thus uninformative: "evolution has done a lot of work that we equate as genetic algorithms"

by Zenst 7y ago

jayd16 7y ago

Evolution also determined a giraffe's lyrngeal nerve should detour down the neck and back.

jacquesm 7y ago
Apparently the signal arrived too early so a delay loop was spliced in. Score one for ID.
- therein 7y ago
  When the giraffe class was first released it was too OP with its tall neck, allowing it to access food previously unreachable to many other classes while also being able to keep an eye on predators lurking at distance. Upon next evolutionary tick, it had to be nerfed.
  - mockingbirdy 7y ago
    For anyone who doesn't get the reference: Watch TierZoo [1]. Hilarious and informative, especially for gamers. [1]: https://www.youtube.com/watch?v=6xbQ2WbTp0E https://www.youtube.com/watch?v=6xbQ2WbTp0E

fucking_tragedy 7y ago

> May well turn out later on that AI is best modeled for speed and detail at 11 bit resolution - after all - evolution has done a lot of work that we equate as machine learning. I don't see gradient descent or back propagation in biology.

Zenst 7y ago
Maybe not yet, but for example gradient descent - https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0219004 https://journals.plos.org/plosone/article?id=10.1371/journal... As for back propagation, I'm sure there are aspects in nature in which translate - maybe the nerves system of some species. Way to see it is that evolutionary change of any form could in theory be modeled in machine learning. There may be aspects of evolution and how it operates that help refine how we do machine learning.
salty_biscuits 7y ago
Well for gradient ascent you have this. https://en.wikipedia.org/wiki/Chemotaxis https://en.wikipedia.org/wiki/Chemotaxis
ianai 7y ago
iirc, back propagation sounds similar in inspection to some of the processes seen in sleeping brains. Ie what they see in MRIs looks like what back propagation might look like from outside. But I’m really not comfortable enough with these terms to speak about them.
DoctorOetker 7y ago
The jury is still out on back-propagation (i.e. reverse accumulation automatic differentiation) within the brain (retrograde signalling from the post-synaptic neuron to the pre-synaptic neuron may still be discovered and turn out to approximate RM AD) But regarding evolution implementing back-propagation, I agree that is just bonkers, as it would require cells to back-propagate in time information about death or procreation! If our biology implements information time machines, biology would be a lot weirder than it is (and it would imply that we could use that by sequencing an organisms genome (or ensemble of them) to read from the future, and keeping it fed without allowing reproduction, and later when we want to write information back either kill or let it reproduce). That's just plain nonsense. There can't be back-propagation in evolution without biological time-travel of information. And machine learning without back-propagation is basically a genetic algorithm, so the claim that "evolution has done a lot of work that we equate as machine learning" would then reduce to a widely accepted fact that nobody disputes and is thus uninformative: "evolution has done a lot of work that we equate as genetic algorithms"