4 ms·

Numenta Platform for Intelligent Computing

82 points by martinlaz 6y ago

polotics 6y ago
Python 2 only, project in maintenance mode? Why post this what's the hacker news?
- rsiqueira 6y ago
  This is interesting because it's an implementation of Hierarchical Temporal Memory (HTM), that is a theory about how a biological brain works in terms of memory processing, why we learn in sequences, how a single memory is distributed in many areas. See also: https://en.wikipedia.org/wiki/Hierarchical_temporal_memory https://en.wikipedia.org/wiki/Hierarchical_temporal_memory
- lux 6y ago
  It looks like this may be the new implementation: https://github.com/htm-community/htm.core https://github.com/htm-community/htm.core
orbifold 6y ago
Not to be too mean about it, but I feel like this is an instance of brilliant marketing more than anything. The founder of Numenta knows how to communicate to Engineers in a convincing way. Neuroscientists (and Science in general) has a way of politely ignoring outsiders and in any case Computational neuroscience doesn’t have terribly high standards of rigor and quality anyways.
- greyface- 6y ago
  For context: the founder of Numenta is Jeff Hawkins https://en.wikipedia.org/wiki/Jeff_Hawkins https://en.wikipedia.org/wiki/Jeff_Hawkins
- zcw100 6y ago
  How is this brilliant marketing? Most people have never heard of Nummenta and they’ve managed to do that during a massive hype cycle in AI.
- samuell 6y ago
  IBM has been doing some research on Hierarchical Temporal Memory (the concept behind Numenta's stuff), via "IBM Cortial Learning Center" [1]. At least some people have seen something of more value than just marketing there, and worth exploring. [1] https://nice.sandia.gov/documents/2015/NICE3talkwwwFinal-NO%20VIDEOS.pdf https://nice.sandia.gov/documents/2015/NICE3talkwwwFinal-NO%...
  - ansible 6y ago
    Though there doesn't seem to be much activity there since 2015.
    - samuell 6y ago
      True.
- p1esk 6y ago
  It's the opposite, they are so bad at marketing that they are completely ignored by both neuroscience and machine learning communities. Even though they are exactly in between these two fields, and their ideas are good. The company is still alive only because the founder funds it himself.
- cblconfederate 6y ago
  > and in any case Computational neuroscience doesn’t have terribly high standards of rigor I beg your pardon sir! The standards are relatively OK
samuell 6y ago
For people wanting to look into HTM (Hierarchical Temporal Memory), do check out Numenta's main website [1], in particular the papers [2] and videos [3] sections. Otherwise, HTM inventor Jeff Hawkins' book "On Intelligence" is one of the top 3 or so most fascinating books I've ever read. It doesn't cover HTM though, just how the brain works at a conceptual level, but in a way I haven't seen anyone else explain. Jeff clearly has an ability to see the forest through the trees in a way that is not too commonly found. This is one of the reasons I think HTM might be on to something, although it of course has to prove itself in real life too. But we should remember for how long classic Neural Networks was NOT overly successful, and almost dismissed by a lot of people (including my university teacher who was rather skeptical about them, when I took an ML course on like 12 years ago and personally believed a lot in them). We had to "wait" for years and years until enough people were eventually throwing enough work on finding out how to make them really shine. [1] https://numenta.org/ https://numenta.org/ [2] https://numenta.com/neuroscience-research/research-publications/papers/ https://numenta.com/neuroscience-research/research-publicati... [3] https://www.youtube.com/user/OfficialNumenta https://www.youtube.com/user/OfficialNumenta [4] https://www.amazon.com/Intelligence-Understanding-Creation-Intelligent-Machines/dp/0805078533 https://www.amazon.com/Intelligence-Understanding-Creation-I... Edit: Fixed book link.
- querez 6y ago
  > we should remember for how long classic Neural Networks was NOT overly successful We already knew in the late80s/early 90s that neural networks were universal function approximators, and there was an era in the late 80s/early 90s where neural nets were VERY successful (or at least: very influential among the ML circles of their day). Sure, they were dismissed once kernel machines came about, simply because those had more to offer at the time. But it would be a mistake to compare HTM with classical neural networks: neural nets were always known to do something sensible and to "work", even if they might not be the state-of-the-art method. In stark contrast, HTM has been "out there" for over long a decade by now, with (as far as I know) not a single tangible result, neither theoretical nor practical. They never managed to hobble together even a single paper with credible results, even though they came out with it right at the time where connectionist approaches became popular again (yes, there were papers, but there's a reason they only got published in 2nd or 3rd tier venues). From where I stand, it's a "hot air" technology that somehow seems to stay afloat because the person behind it know how to write popular science books. Everyone researcher I know who tried to make HTM work came away with the same conclusion: it just doesn't.
mark_l_watson 6y ago
As part of this older project, there is a nice benchmarking/comparison example for several types of anomaly detection for sequence data. If you need to do that, looking at this example is worthwhile.
zubiaur 6y ago
Lex Fridman has a fantastic interview with the Numenta's (and Palm's) founder, Jeff. https://lexfridman.com/jeff-hawkins/ https://lexfridman.com/jeff-hawkins/
Upvoter33 6y ago
Hawkins also has a new book coming. His first book (as said in other comments) is a fantastic read. https://www.amazon.com/Thousand-Brains-New-Theory-Intelligence/dp/1541675819 https://www.amazon.com/Thousand-Brains-New-Theory-Intelligen...
- y-c-o-m-b 6y ago
  Thanks for posting this, I've just pre-ordered it. I didn't know he was coming out with a new one until I saw your post. I really liked reading On Intelligence.
- ssivark 6y ago
  For those interested, the book probably expands on the following paper from a few months ago: https://numenta.com/blog/2019/01/16/the-thousand-brains-theory-of-intelligence/ https://numenta.com/blog/2019/01/16/the-thousand-brains-theo... (paper linked to from blog post) There's also a recent Lex Fridman podcast episode where he interviews Jeff Hawkins on this theme: https://lexfridman.com/jeff-hawkins/ https://lexfridman.com/jeff-hawkins/
deleted 6y ago
[deleted]
axegon_ 6y ago
I fiddled around with it before Google open sourced tensorflow. Seems like the project is almost entirely abandoned-no commits for a year now. I suppose this may have something to do with the death of the lead developer Matt Taylor several months ago(R.I.P.) but I could be wrong. It would be interesting to see if someone could get it up to speed.
- kroggen 6y ago
  It is community maintained here: https://github.com/htm-community https://github.com/htm-community But I guess that the focus on Numenta now is on new deeper ideas, mainly related to grid cells and processing of spatial data on mini-columns
LargoLasskhyfv 6y ago
Why would I want to mess with that now when it depends on Python 2.7? Wouldn't that be like basing something on the LuaJIT-based Torch7?

82 points by martinlaz 6y ago

polotics 6y ago

Python 2 only, project in maintenance mode? Why post this what's the hacker news?

rsiqueira 6y ago
This is interesting because it's an implementation of Hierarchical Temporal Memory (HTM), that is a theory about how a biological brain works in terms of memory processing, why we learn in sequences, how a single memory is distributed in many areas. See also: https://en.wikipedia.org/wiki/Hierarchical_temporal_memory https://en.wikipedia.org/wiki/Hierarchical_temporal_memory
lux 6y ago
It looks like this may be the new implementation: https://github.com/htm-community/htm.core https://github.com/htm-community/htm.core

orbifold 6y ago

Not to be too mean about it, but I feel like this is an instance of brilliant marketing more than anything. The founder of Numenta knows how to communicate to Engineers in a convincing way. Neuroscientists (and Science in general) has a way of politely ignoring outsiders and in any case Computational neuroscience doesn’t have terribly high standards of rigor and quality anyways.

greyface- 6y ago
For context: the founder of Numenta is Jeff Hawkins https://en.wikipedia.org/wiki/Jeff_Hawkins https://en.wikipedia.org/wiki/Jeff_Hawkins
zcw100 6y ago
How is this brilliant marketing? Most people have never heard of Nummenta and they’ve managed to do that during a massive hype cycle in AI.
samuell 6y ago
IBM has been doing some research on Hierarchical Temporal Memory (the concept behind Numenta's stuff), via "IBM Cortial Learning Center" [1]. At least some people have seen something of more value than just marketing there, and worth exploring. [1] https://nice.sandia.gov/documents/2015/NICE3talkwwwFinal-NO%20VIDEOS.pdf https://nice.sandia.gov/documents/2015/NICE3talkwwwFinal-NO%...
- ansible 6y ago
  Though there doesn't seem to be much activity there since 2015.
  - samuell 6y ago
    True.
p1esk 6y ago
It's the opposite, they are so bad at marketing that they are completely ignored by both neuroscience and machine learning communities. Even though they are exactly in between these two fields, and their ideas are good. The company is still alive only because the founder funds it himself.
cblconfederate 6y ago
> and in any case Computational neuroscience doesn’t have terribly high standards of rigor I beg your pardon sir! The standards are relatively OK

samuell 6y ago

For people wanting to look into HTM (Hierarchical Temporal Memory), do check out Numenta's main website [1], in particular the papers [2] and videos [3] sections. Otherwise, HTM inventor Jeff Hawkins' book "On Intelligence" is one of the top 3 or so most fascinating books I've ever read. It doesn't cover HTM though, just how the brain works at a conceptual level, but in a way I haven't seen anyone else explain. Jeff clearly has an ability to see the forest through the trees in a way that is not too commonly found. This is one of the reasons I think HTM might be on to something, although it of course has to prove itself in real life too. But we should remember for how long classic Neural Networks was NOT overly successful, and almost dismissed by a lot of people (including my university teacher who was rather skeptical about them, when I took an ML course on like 12 years ago and personally believed a lot in them). We had to "wait" for years and years until enough people were eventually throwing enough work on finding out how to make them really shine. [1] https://numenta.org/ https://numenta.org/ [2] https://numenta.com/neuroscience-research/research-publications/papers/ https://numenta.com/neuroscience-research/research-publicati... [3] https://www.youtube.com/user/OfficialNumenta https://www.youtube.com/user/OfficialNumenta [4] https://www.amazon.com/Intelligence-Understanding-Creation-Intelligent-Machines/dp/0805078533 https://www.amazon.com/Intelligence-Understanding-Creation-I... Edit: Fixed book link.

querez 6y ago
> we should remember for how long classic Neural Networks was NOT overly successful We already knew in the late80s/early 90s that neural networks were universal function approximators, and there was an era in the late 80s/early 90s where neural nets were VERY successful (or at least: very influential among the ML circles of their day). Sure, they were dismissed once kernel machines came about, simply because those had more to offer at the time. But it would be a mistake to compare HTM with classical neural networks: neural nets were always known to do something sensible and to "work", even if they might not be the state-of-the-art method. In stark contrast, HTM has been "out there" for over long a decade by now, with (as far as I know) not a single tangible result, neither theoretical nor practical. They never managed to hobble together even a single paper with credible results, even though they came out with it right at the time where connectionist approaches became popular again (yes, there were papers, but there's a reason they only got published in 2nd or 3rd tier venues). From where I stand, it's a "hot air" technology that somehow seems to stay afloat because the person behind it know how to write popular science books. Everyone researcher I know who tried to make HTM work came away with the same conclusion: it just doesn't.

mark_l_watson 6y ago

As part of this older project, there is a nice benchmarking/comparison example for several types of anomaly detection for sequence data. If you need to do that, looking at this example is worthwhile.

zubiaur 6y ago

Lex Fridman has a fantastic interview with the Numenta's (and Palm's) founder, Jeff. https://lexfridman.com/jeff-hawkins/ https://lexfridman.com/jeff-hawkins/

Upvoter33 6y ago

Hawkins also has a new book coming. His first book (as said in other comments) is a fantastic read. https://www.amazon.com/Thousand-Brains-New-Theory-Intelligence/dp/1541675819 https://www.amazon.com/Thousand-Brains-New-Theory-Intelligen...

y-c-o-m-b 6y ago
Thanks for posting this, I've just pre-ordered it. I didn't know he was coming out with a new one until I saw your post. I really liked reading On Intelligence.
ssivark 6y ago
For those interested, the book probably expands on the following paper from a few months ago: https://numenta.com/blog/2019/01/16/the-thousand-brains-theory-of-intelligence/ https://numenta.com/blog/2019/01/16/the-thousand-brains-theo... (paper linked to from blog post) There's also a recent Lex Fridman podcast episode where he interviews Jeff Hawkins on this theme: https://lexfridman.com/jeff-hawkins/ https://lexfridman.com/jeff-hawkins/

deleted 6y ago

[deleted]

axegon_ 6y ago

I fiddled around with it before Google open sourced tensorflow. Seems like the project is almost entirely abandoned-no commits for a year now. I suppose this may have something to do with the death of the lead developer Matt Taylor several months ago(R.I.P.) but I could be wrong. It would be interesting to see if someone could get it up to speed.

kroggen 6y ago
It is community maintained here: https://github.com/htm-community https://github.com/htm-community But I guess that the focus on Numenta now is on new deeper ideas, mainly related to grid cells and processing of spatial data on mini-columns

LargoLasskhyfv 6y ago

Why would I want to mess with that now when it depends on Python 2.7? Wouldn't that be like basing something on the LuaJIT-based Torch7?