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I think the term ai has been completely abused. In fact I try to avoid using the word ai if I can help it and use deep learning instead because that's really th

I think the term ai has been completely abused. In fact I try to avoid using the word ai if I can help it and use deep learning instead because that's really the whole crux of this new tech. I think most people, definitely author of the piece, miss the whole core impact of ai. Ai is basically a new way to process and calculate data, a new type of algorithm. We can now identify objects in pictures using computer vision with deep learning. This was NOT POSSIBLE with the tech before. A computer can now beat a team of human ai players in dota. This was definitely NOT POSSIBLE before. At the end of the day this is the impact and its not a small impact. It opens a lot of possibilities to what can now be done. To me it's far more impactful blockchain will ever be. To some degree I'm actually quite happy with all the misleading hype because the people who understand and are capable of using the technology are quietly making real differences behind all the smoke and cloud

ska 8y ago
While there have been some good incremental improvements, I think you are overstating the place of deep learning vis a vis everything in machine learning that came before it. The same thing happened to SVMs in the early 2000s, but with much less industry noise. NB I’m not trying to compare the impact of the two, just noting it was also over stated. After all, deep learning is fundamentally a continuation of much older techniques. And we absolutely could identify objects in pictures, we’ve been doing that for 40 years now - deep learning techniques have given a very nice jump in accuracy for some tasks but they didn’t come out of nowhere. I agree the whole labelling “AI” is problematic. That is also a many decades old problem though...
- kthejoker2 8y ago
  AI developments are more like battery storage improvements. Just 10% improvements year over year, in hardware, in architecture, in algorithms, in data capturing and labeling ... they've just really started to add up. But 10% growth YOY compounds very quickly.
  - ska 8y ago
    10 percent would compound quickly if we were seeing that - I suspect most of the recent acceleration has far more to do with data availability than any technical improvements though.
jammygit 8y ago
I'm fond of the term 'data modelling' for most 'machine learning' tasks. Except for the systems that play DOTA, Go, and Starcraft - those are something else.
- kthejoker2 8y ago
  Those are just reinforcement learning. Again, standard systems, been around for ages, the whole movie WarGames (36 years old) hinges on an RL-based supercomputer gone wild. They're not something else, they're still just really, really impressive lookup tables.

ska 8y ago

While there have been some good incremental improvements, I think you are overstating the place of deep learning vis a vis everything in machine learning that came before it. The same thing happened to SVMs in the early 2000s, but with much less industry noise. NB I’m not trying to compare the impact of the two, just noting it was also over stated. After all, deep learning is fundamentally a continuation of much older techniques. And we absolutely could identify objects in pictures, we’ve been doing that for 40 years now - deep learning techniques have given a very nice jump in accuracy for some tasks but they didn’t come out of nowhere. I agree the whole labelling “AI” is problematic. That is also a many decades old problem though...

kthejoker2 8y ago
AI developments are more like battery storage improvements. Just 10% improvements year over year, in hardware, in architecture, in algorithms, in data capturing and labeling ... they've just really started to add up. But 10% growth YOY compounds very quickly.
- ska 8y ago
  10 percent would compound quickly if we were seeing that - I suspect most of the recent acceleration has far more to do with data availability than any technical improvements though.

jammygit 8y ago

I'm fond of the term 'data modelling' for most 'machine learning' tasks. Except for the systems that play DOTA, Go, and Starcraft - those are something else.

kthejoker2 8y ago
Those are just reinforcement learning. Again, standard systems, been around for ages, the whole movie WarGames (36 years old) hinges on an RL-based supercomputer gone wild. They're not something else, they're still just really, really impressive lookup tables.