5 ms·

Time for an AI winter I guess.

Logon90 5y ago
Just from the headline you can see the irrelevance of this chip. Who talks about transistor count as a proxy of performance?
streetcat1 5y ago
You do realize that AI crossed human expert performance in NLP / Vision tasks ?
- semi-extrinsic 5y ago
  Exactly how does one outperform a human expert in natural language processing?
  - pulse7 5y ago
    Parent probably meant that it outperformed a human expert in some specific task in the area of natural language processing - for example the task of converting a spoken language into a written language...
  - zetazzed 5y ago
    See, if you were an AI, you would understand EXACTLY what the poster means by this.
  - twic 5y ago
    Maybe the gibberish GPT-3 spits out is actually true, and our puny monke brains are just too weak to understand it.
  - PeterisP 5y ago
    They don't really outperform human experts on real tasks yet (no matter what some superGLUE or other benchmark shows); but in general, once a system can solve a particualr task well, it would be plausible to outperform human experts simply by not making random errors. If we have multiple human experts annotate a NLP task and measure inter-annotator agreement, it will be far from 100%; part of that will be genuine disagreements or fuzzy gray area, but part of the identified differences will be simply obviously wrong answers given by the experts - everyone makes mistakes. The same applies for many other domains - business process automation, data entry, etc; no employee will produce error-free output in a manual process, no matter how simple and unambiguous the task is. And for simpler tasks the computer can easily make less mistakes than a human - especially if you measure the human reliability not for a few minutes of focus, but for a whole tedious working day.
- firebaze 5y ago
  I'm not sure if you're assuming best intentions. If you do, it'd be nice to provide sources - to my knowledge, vision under non-optimal conditions (rain, snow, sunlight ahead) is only partially solved by resorting to sensors resistant to the disturbance. I'd be glad to learn I'm wrong.
  - fredfoobar 5y ago
    TBH, I believe we need another AI winter to come up with something better than the AI "black boxes" we have right now.
- king_magic 5y ago
  No, it hasn't. Not even close. AI has "crossed human expert performance" on extremely narrow NLP/CV tasks. AI is still light years away from human-level performance.
- anthk 5y ago
  GPT-3 is not even close to a minimal and coherent text adventure made with Inform6 from a novice, even if it's written by a non-native English speaker. Those networks didn't match "Detective", a crappy story written by a 12yo.
trhway 5y ago
>Time for an AI winter with AI chips burning 15KW? No chance for the winter in sight. Some chances for AI hell though.
fredfoobar 5y ago
This statement was made for experimental purposes, to understand HN biases.

Just from the headline you can see the irrelevance of this chip. Who talks about transistor count as a proxy of performance?

streetcat1 5y ago

You do realize that AI crossed human expert performance in NLP / Vision tasks ?

semi-extrinsic 5y ago
Exactly how does one outperform a human expert in natural language processing?
- pulse7 5y ago
  Parent probably meant that it outperformed a human expert in some specific task in the area of natural language processing - for example the task of converting a spoken language into a written language...
- zetazzed 5y ago
  See, if you were an AI, you would understand EXACTLY what the poster means by this.
- twic 5y ago
  Maybe the gibberish GPT-3 spits out is actually true, and our puny monke brains are just too weak to understand it.
- PeterisP 5y ago
  They don't really outperform human experts on real tasks yet (no matter what some superGLUE or other benchmark shows); but in general, once a system can solve a particualr task well, it would be plausible to outperform human experts simply by not making random errors. If we have multiple human experts annotate a NLP task and measure inter-annotator agreement, it will be far from 100%; part of that will be genuine disagreements or fuzzy gray area, but part of the identified differences will be simply obviously wrong answers given by the experts - everyone makes mistakes. The same applies for many other domains - business process automation, data entry, etc; no employee will produce error-free output in a manual process, no matter how simple and unambiguous the task is. And for simpler tasks the computer can easily make less mistakes than a human - especially if you measure the human reliability not for a few minutes of focus, but for a whole tedious working day.
firebaze 5y ago
I'm not sure if you're assuming best intentions. If you do, it'd be nice to provide sources - to my knowledge, vision under non-optimal conditions (rain, snow, sunlight ahead) is only partially solved by resorting to sensors resistant to the disturbance. I'd be glad to learn I'm wrong.
- fredfoobar 5y ago
  TBH, I believe we need another AI winter to come up with something better than the AI "black boxes" we have right now.
king_magic 5y ago
No, it hasn't. Not even close. AI has "crossed human expert performance" on extremely narrow NLP/CV tasks. AI is still light years away from human-level performance.
anthk 5y ago
GPT-3 is not even close to a minimal and coherent text adventure made with Inform6 from a novice, even if it's written by a non-native English speaker. Those networks didn't match "Detective", a crappy story written by a 12yo.

trhway 5y ago

>Time for an AI winter with AI chips burning 15KW? No chance for the winter in sight. Some chances for AI hell though.

fredfoobar 5y ago

This statement was made for experimental purposes, to understand HN biases.