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> Therefore these viruses can facilely jump over hills in the gradient descent of optimization It warms to see that the similarities of some aspects of biologi

> Therefore these viruses can facilely jump over hills in the gradient descent of optimization It warms to see that the similarities of some aspects of biological life to the current AI/ML terms has entered the lexicon, well at least on HN crowd. The fact that it makes a lot of sense to use those terms hints that we might indeed be on the right track to building AGI and understnding the life itself in general.

quonn 6y ago
How is there gradient descent or even a gradient in biological mutations? If anything there could be an analogy to undirected trial & error as in genetic algorithms.
- RobertoG 6y ago
  I think that they are using "gradient descend" when they should be using "space of the problem". Otherwise is a good comment.
- Erlich_Bachman 6y ago
  It's directed by the survival and spreading of the virus.
jsinai 6y ago
meta, what if it was just GPT-3 commenting and there was just leakage from the ML community
mvanaltvorst 6y ago
Gradient descent is a subset of survival of the fittest, described by Darwin in 1800-1900, and has been in applied in computer science since the 70's. An AGI will probably use some form of gradient descent during its training, yes, but I wouldn't argue that this has brought us even close to an AGI.
- dnautics 6y ago
  This is wrong. Gradient descent derives from multivariate calculus, not evolution.
hutzlibu 6y ago
"The fact that it makes a lot of sense to use those terms hints that we might indeed be on the right track to building AGI " But there is also the danger of false analogies doing damage, by creating the illusion of understanding something because the wording feels familiar. There are no doubts similarities, but that does not mean, it is the same. That happened a couple of times already with progess in technology and then simplified applied technical models to biological life. So sure, I think so too, that we are on the right track, I am just a bit more hesistant.
dnautics 6y ago
Objective cost surfaces have been around way longer than ml. It's been in the genetic algorithm lexicon for a long time, and more true to form, in stuff like actual potential energy diagrams of high dimensional degrees of freedom spaces in enzymology. Also having been a professional biochemist and worked in AI infrastructure, I know the commonalities well and know how to avoid faux-amis. Note that this process is NOT backpropagation. "The fact that it makes a lot of sense to use those terms hints that we might indeed be on the right track to building AGI and understnding the life itself in general" Nope, it's a residual of the fact that AI stole ideas from other fields, and ran with the terminology as marketing. Sometimes even to the point of extreme divergence from the original ("neural" nets).

quonn 6y ago

How is there gradient descent or even a gradient in biological mutations? If anything there could be an analogy to undirected trial & error as in genetic algorithms.

RobertoG 6y ago
I think that they are using "gradient descend" when they should be using "space of the problem". Otherwise is a good comment.
Erlich_Bachman 6y ago
It's directed by the survival and spreading of the virus.

jsinai 6y ago

meta, what if it was just GPT-3 commenting and there was just leakage from the ML community

mvanaltvorst 6y ago

Gradient descent is a subset of survival of the fittest, described by Darwin in 1800-1900, and has been in applied in computer science since the 70's. An AGI will probably use some form of gradient descent during its training, yes, but I wouldn't argue that this has brought us even close to an AGI.

dnautics 6y ago
This is wrong. Gradient descent derives from multivariate calculus, not evolution.

hutzlibu 6y ago

"The fact that it makes a lot of sense to use those terms hints that we might indeed be on the right track to building AGI " But there is also the danger of false analogies doing damage, by creating the illusion of understanding something because the wording feels familiar. There are no doubts similarities, but that does not mean, it is the same. That happened a couple of times already with progess in technology and then simplified applied technical models to biological life. So sure, I think so too, that we are on the right track, I am just a bit more hesistant.

dnautics 6y ago

Objective cost surfaces have been around way longer than ml. It's been in the genetic algorithm lexicon for a long time, and more true to form, in stuff like actual potential energy diagrams of high dimensional degrees of freedom spaces in enzymology. Also having been a professional biochemist and worked in AI infrastructure, I know the commonalities well and know how to avoid faux-amis. Note that this process is NOT backpropagation. "The fact that it makes a lot of sense to use those terms hints that we might indeed be on the right track to building AGI and understnding the life itself in general" Nope, it's a residual of the fact that AI stole ideas from other fields, and ran with the terminology as marketing. Sometimes even to the point of extreme divergence from the original ("neural" nets).