Jeff Hawkins gets shit on a lot in ML because his theories haven’t produced models with results as good as the mainstream approach, but I’m glad they keep working at it and keep coming up with interesting ideas.<p>Too much of ML these days is about some NN model that does 0.n% better than SOTA on some specific task. Then you change one tiny parameter and he entire thing breaks, and it turns out we didn’t understand why it was working at all.
Full paper here: <a href="https://www.biorxiv.org/content/biorxiv/early/2017/09/28/162263.full.pdf" rel="nofollow">https://www.biorxiv.org/content/biorxiv/early/2017/09/28/162...</a><p>I always enjoy reading analysis/ideas/intuitions about how the brain works, because it provides inspiration for machine learning improvements that can be applied in the real world.<p>That said, I’m still optimistically waiting for Numenta (and Geoff Hinton’s capsule theory) to set the new bar at one of the many difficult image/speech/language/etc recognition challenges.<p>Ideas are great, but at the end of the day science moves forward when we measure our ideas against reality. (To the credit of this paper, it does make a series of predictions, though those seem extremely difficult to measure in biological systems for the time being.)
Skeptical. Previously the brain was a machine consisting of drives and pulleys, just like the state of technology of the day. Now the brain is a computer that runs deep learning models. It would be one thing to just say the cortex has columns. It's another to go on and model what those columns are doing with linear algebra. The coincidence that this picture emerges at the same time as current fads in tech is too great to ignore<p>I am more interested in the work that is identifying different kinds of cells e.g place cells
Great to see numenta in the news again. On Intelligence was the book that got me excited about biologically based machine learning. The methods that in that book is very different to anything else I’ve seen in current “trendy” ML.
Here are some video resources to help explain this theory:<p>- <a href="https://www.youtube.com/watch?v=BvJJn9VS4rk" rel="nofollow">https://www.youtube.com/watch?v=BvJJn9VS4rk</a>
- <a href="https://www.youtube.com/watch?v=-h-cz7yY-G8" rel="nofollow">https://www.youtube.com/watch?v=-h-cz7yY-G8</a>
The world needs more work being done in the way Hawkins and co. are doing it, and less in the mold of most deep learning/ML work. Why? He's actually trying to connect building intelligent machines with biology. This is a huge problem, but so few are working on it. Rather, we are all distracted by deep learning because of its recent successes in very specific problem areas. In a few years, when we run into its limits, Hawkins and people doing work like this will have a chance to shine (if they produce something that works, of course).
> Error! Problem, or Page Not Found<p>> Sorry, the page you were looking for does not exist.<p>Link is broken. From browsing, I believe the correct link is<p><a href="https://numenta.com/papers-videos-and-more/resources/layers-and-columns/" rel="nofollow">https://numenta.com/papers-videos-and-more/resources/layers-...</a>
Understand how the brain works means understand how we the humans see and understand the world and ourselfs within it. The brain organically and selectivelly selects what to learn and which information shou
ld be retained. Our brain receives training since birthdays. Then the family implements some of their own training then school and world. The brain never stops.<p>Great job Numenta !!
I'm getting "Error! Problem, or Page Not Found
Sorry, the page you were looking for does not exist."<p>Edit: Weird, I just closed my browser and tried again, and the article looks like it flashed into the screen then was replaced by the error message. Happens repeatedly on Chrome on Android...
I'm probably talking out of my ass but I'm somewhat suspect of a cortex having straight up columns. I'm curious whether these are artifacts of the fact that linear algebra seems to be the dominant algebra in ML/modeling of human perception. Recently I've been dipping my feet into geometric algebra which seems to be the superior algebra for just about anything you can think of (human perception but also like all of physics, Maxwell's 4 equations are reduced to a single equation in GA) and it's particularly better for reasoning about spaces which this seems to be all about.<p>And unlike linear algebra it actually makes sense (e.g. why is cross product only in three dimensions?, wtf are determinants esp. in the context of matrix division all about?).<p>This blog post introduces GA and talks about it's relationship to human perception.<p><a href="https://slehar.wordpress.com/2014/03/18/clifford-algebra-a-visual-introduction/" rel="nofollow">https://slehar.wordpress.com/2014/03/18/clifford-algebra-a-v...</a>