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Out of curiousity given your seemingly strong sentiments, what is your background and what authors/researchers would you say have influenced your thinking the m

Out of curiousity given your seemingly strong sentiments, what is your background and what authors/researchers would you say have influenced your thinking the most?

aalleavitch 9y ago
I'm just a frontend engineer who dabbles in ML and cognitive science; my neuroscience experience is limited to a bachelor's degree and a couple years of lab work so I'm admittedly a lot more passionate than I am personally authoritative on the subject. The biggest influence on my thinking regarding intelligent systems generally is Douglas Hofstadter, but the notions of brain function I alluded to above are prevalent throughout a lot of computational neuroscience.
- arketyp 9y ago
  I sympathize with this being in a similar professional situation and having once been introduced to this field via Hofstadter. His musings are usually on a distinctly symbolic level however, and though it is not my intention to defend a kind of results-only pragmatic approach, I do concern myself with strategies for progressively reaching better models of intelligence and their realization in contemporary hardware in particular. What, for instance, is your opinion about Hinton's recently published capsules idea? https://arxiv.org/abs/1710.09829 https://arxiv.org/abs/1710.09829 https://openreview.net/forum?id=HJWLfGWRb https://openreview.net/forum?id=HJWLfGWRb
  - aalleavitch 9y ago
    I haven't had the opportunity to dive deeply into capsule networks yet, but I have been fairly excited by what little I've read so far. I think that Hinton et al are brilliant and definitely taking neural nets in the right direction by trying to approximate more of the mid-level organization of the brain, but I feel like recent attempts to integrate things like attention and memory into nns are still at a very elementary level. This isn't to denigrate recent work at all: this is a stage we have to cross on our way to more powerful intelligent systems, and you're right that pragmatically one of the best ways to further the field is to focus on making models that are useful in their current state even if they poorly approximate more complex systems. On the whole, I'd wager the state of the field is still at the Bohr model level, but progressing rapidly.

Out of curiousity given your seemingly strong sentiments, what is your background and what authors/researchers would you say have influenced your thinking the most?

aalleavitch 9y ago

I'm just a frontend engineer who dabbles in ML and cognitive science; my neuroscience experience is limited to a bachelor's degree and a couple years of lab work so I'm admittedly a lot more passionate than I am personally authoritative on the subject. The biggest influence on my thinking regarding intelligent systems generally is Douglas Hofstadter, but the notions of brain function I alluded to above are prevalent throughout a lot of computational neuroscience.

arketyp 9y ago
I sympathize with this being in a similar professional situation and having once been introduced to this field via Hofstadter. His musings are usually on a distinctly symbolic level however, and though it is not my intention to defend a kind of results-only pragmatic approach, I do concern myself with strategies for progressively reaching better models of intelligence and their realization in contemporary hardware in particular. What, for instance, is your opinion about Hinton's recently published capsules idea? https://arxiv.org/abs/1710.09829 https://arxiv.org/abs/1710.09829 https://openreview.net/forum?id=HJWLfGWRb https://openreview.net/forum?id=HJWLfGWRb
- aalleavitch 9y ago
  I haven't had the opportunity to dive deeply into capsule networks yet, but I have been fairly excited by what little I've read so far. I think that Hinton et al are brilliant and definitely taking neural nets in the right direction by trying to approximate more of the mid-level organization of the brain, but I feel like recent attempts to integrate things like attention and memory into nns are still at a very elementary level. This isn't to denigrate recent work at all: this is a stage we have to cross on our way to more powerful intelligent systems, and you're right that pragmatically one of the best ways to further the field is to focus on making models that are useful in their current state even if they poorly approximate more complex systems. On the whole, I'd wager the state of the field is still at the Bohr model level, but progressing rapidly.