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Comment by teabee89 | Hacker News Reader

I'm very pleased to see Numenta on HN front page, as they're doing incredibly difficult and ambitious work without deep learning's spotlight. They take a philosophically very different approach: instead of warming up biologically implausible neural models from the 60s and hope that with enough data we'll reach artificial general intelligence (AGI), Numenta founder Jeff Hawkins (way before Hinton's or Hassabis's recent declarations of DL reaching a deadend) thinks we shall understand our biological neocortex better and reverse engineer it because it's the only piece of hardware most scientists agree is at the source of intelligence. Although planes don't have wings, we had to understand wing-flapping first to find better ways to fly. If you're interested, I highly recommend you follow https://discourse.numenta.org/

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> Although planes don't have wings

I take your point that planes don't fly by flapping like birds, but obviously they do actually have wings.

Depends on what you mean by wings. The word wings here has multiple meanings, with commonality that they both are involved in flying. However, they differ in their operation, i.e. one thing flaps the other doesn't.

A more concise way of putting it would be to say that airplanes are not ornithopters.

You'll be claiming that tables don't have legs next.

>Depends on what you mean by wings.

No it doesn't. I have arms. Certain machinery has arms. They may mean different things but they both have arms, just as both birds and planes have wings

Furthermore, the mechanics of flapping flight is complex, of little relevance to airplane design, and not well understood until well after airplanes were invented. What aviation owes to ornithology is mostly from the observation of gliding birds.

If anyone is interested in some foundational reading Jeff Hawkins and Sandra Blakeslee published a fantastic book in 2004 called "On Intelligence: How a New Understanding of the Brain will Lead to the Creation of Truly Intelligent Machines".

There is also an audiobook version if that's your thing. I enjoyed it very much. Happy to see more progress from this group.

I’m very curious where you found Hassabis saying DL is at a dead end. I would be really interested to watch or read if you have a link.

"Deep learning is an amazing technology and hugely useful in itself, but in my opinion it's definitely not enough to solve AI, [not] by a long shot," [Hassabis] said

"I would regard it as one component, maybe with another dozen or half-a-dozen breakthroughs we're going to need like that.

"There's a lot more innovation that's required." https://www.techrepublic.com/article/google-deepmind-founder...

I presume this is the thing - I don't think he actually said 'dead end'.

To me these quotes don’t support the idea that deep learning is at a dead end. We are only just beginning to get it to really work for real world problems and I think that will take off a lot in the coming years.

Even if all you care about is general AI, there is still a lot of progress that needs to be made within DL.

I think the point is just that we should be open to other approaches because they will be needed as well

Correct, that's what I was referring to. Apologies if I mischaracterized his stance.

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