11–20 of 78 posts
Can someone ELI5 the general concept?
Just linked this on a similar information theory thread [1] (glad it's so popular on HN right now!)
Earlier quoted context omitted.
Thank you for this. I spend a non-trivial amount of time telling people working in AI and machine learning (which I also do) that the brain isn't some parameter optimization machine and that analogies from whatever technology or math people are excited about aren't very useful. I wish some neuroscience education and articles like these were some part of the ML canon.
I couldn't disagree with you more. The article referenced by GP mistakes the form for the function. Just because the computer uses different technology than human tissue, doesn't mean it isn't emulating the same ultimate processes that are happening in our bodies. And even if we don't have the correct algorithms in sight today, there is every reason to believe that whatever processes are occurring in our brains and b…
True, but there are some pretty interesting ideas out there. I'm going have to start putting together a list of articles. From the proof that if we have free will, so do particles to some extent. To the notion that quantum computation may happen in the brain. Not saying I believe these things, but the people behind them are pretty smart.
For anyone interested in this, the Landauer limit now has experimental evidence. Also, it is now believed that the Margolus-Levitin theorem puts a lower bound on energy even on reversible computations.
It's hard to imagine what it would even mean to get experimental evidence against the Landauer limit. You'd have to throw out basic thermodynamics. (It would about the same as getting experimental evidence for a perpetual motion machine; possible, but basically requiring a revolution in fundamental physics.) The disputes over the Landauer limit were conceptual and definitional disputes, not disagreements over well-fo…
https://advances.sciencemag.org/content/2/3/e1501492
Even in those experiments, there are scenarios where energy is recovered during the erasure of the bit. Although the number of experiments is large enough to recover the k_b T ln(2) expected value.
Can someone ELI5 the general concept?
Earlier quoted context omitted.
I couldn't disagree with you more. The article referenced by GP mistakes the form for the function. Just because the computer uses different technology than human tissue, doesn't mean it isn't emulating the same ultimate processes that are happening in our bodies. And even if we don't have the correct algorithms in sight today, there is every reason to believe that whatever processes are occurring in our brains and b…
>> which no article or neuroscience education has yet demonstrated. True, but there are some pretty interesting ideas out there. I'm going have to start putting together a list of articles. From the proof that if we have free will, so do particles to some extent. To the notion that quantum computation may happen in the brain. Not saying I believe these things, but the people behind them are pretty smart.
The question remains, what reason do we have to believe that only a living brain, and not a silicon analogue, can tap into those features of reality?
Theories are now emerging that Universe is running one large bayesian learning algorithm (bayesian inference itself is proven to be an optimal knowledge creation method) See e.g. Bayesian Brain and Universal Darwinism
See also: brain as hydraulics, brain as a system of cogs, brain as a computer.[1] [1] https://aeon.co/essays/your-brain-does-not-process-informati...
Earlier quoted context omitted.
See also: brain as hydraulics, brain as a system of cogs, brain as a computer.[1] [1] https://aeon.co/essays/your-brain-does-not-process-informati...
Thank you for this. I spend a non-trivial amount of time telling people working in AI and machine learning (which I also do) that the brain isn't some parameter optimization machine and that analogies from whatever technology or math people are excited about aren't very useful. I wish some neuroscience education and articles like these were some part of the ML canon.
The article, however, is rubbish. As psychologist, I cringed throughout. It is a blurr of half-baked ideas and ill-understood controversies from cognitive science. The author manages to write an entire article about information at its core without ever properly defining information, not to speak of representation. In the sense of Shannon, or course neurons are channels transmitting information. What else would they do?
And of course we can decode that information even from the outside, even down to discrete processing stages during the execution of mental tasks (https://onlinelibrary.wiley.com/doi/epdf/10.1111/ejn.13817). And if there are truely no representations in the brain, as the author states, how do we plan for future events that are far beyond the horizon? And even if you reject all that, there is DNA in the brain that is literally information and expressed (decoded and made into protein) ALL THE TIME.
Regarding cognition, the good Mr. Epstein has not grasped the difference between computers and computability. I don't think anybody is looking for silicon in the brain. The smart people are asking how it is possible for a complex system to operate in a complex world without an outside unit directing their behavior. They ask "How how can the human mind occur in the physical universe" (http://act-r.psy.cmu.edu/?post_type=publications&p=14305)? How is it that we can do the things we do? How do we set goals, plan steps to achieve them, and choose the right actions for implementation?
I get where you are coming from and I agree with you regarding a dangerous misunderstanding of AI, especially ML. But this article is not helping putting things in perspective. I am willing, however, to concede one point to Mr. Epstein: His brain is dearly lacking information, representation, algorithms, or any such marker usually signifying intelligent life.
Earlier quoted context omitted.
Thank you for this. I spend a non-trivial amount of time telling people working in AI and machine learning (which I also do) that the brain isn't some parameter optimization machine and that analogies from whatever technology or math people are excited about aren't very useful. I wish some neuroscience education and articles like these were some part of the ML canon.
I couldn't disagree with you more. The article referenced by GP mistakes the form for the function. Just because the computer uses different technology than human tissue, doesn't mean it isn't emulating the same ultimate processes that are happening in our bodies. And even if we don't have the correct algorithms in sight today, there is every reason to believe that whatever processes are occurring in our brains and b…
The trap is to think about the brain in terms of things we find impressive, and about things we find impressive as being like brains somehow. Therefore analogies to steam engines, computers and deep learning. And these analogies have always turned out to be silly.