5 ms·

Good article. This is a great example of "AI"'s inability to extrapolate. Yes, it's able to find amazing shortcuts that no human could working in-distribution,

Good article. This is a great example of "AI"'s inability to extrapolate. Yes, it's able to find amazing shortcuts that no human could working in-distribution, but it has no understanding beyond that, and so can fail as outlined. I wish people would bear this in mind more as they pontificate about how we're near AGI and all that implies. It's all Eliza with just a really big set of phrases it can respond to. Doesn't mean it isn't useful but it's so much different than all the silly musings about sentience and whatnot.

pipo234 3y ago
+1 Arguably "AI" is already plenty general enough, it's just not very intelligent.
worrycue 3y ago
Guess this is similar to ChatGPT and “ davidjl” - https://news.ycombinator.com/item?id=36242914 https://news.ycombinator.com/item?id=36242914 - and tricking image categorisers with specially designed noise. Today’s AI seem to have all sort of unexpected failure modes which can be exploited by adversarial attacks.
- DemeterFarm 3y ago
  [dead]
- Zetobal 3y ago
  Like humans?
  - worrycue 3y ago
    The good thing is we have a lot of knowledge on human failure modes though and have planned around most of them. AIs are currently an unknown quality when it comes to their failure modes* and we are often caught by surprise when they fail at something that we expect they should be able to do because we don't fail at it. * Given how little we understand about how it all actually works in practice, I have a feeling we will never be able to fully grasp their failure modes unlike traditional computing.
rcme 3y ago
I think it depends on what you mean by understanding. KataGo taught itself to play go by explicitly deprioritizing “losing” strategies. This means it didn’t play many amateur strategies because they were lost early in the training. This is hard for a human to understand because humans all generally share a learning curve going from beginning to amateur to expert. So all humans have more experience with “losing” techniques. Basically what I’m saying is, it might be that the training scheme of this AI explicitly prioritized having little understanding of these specific tactics, which is different than not having any understanding.

pipo234 3y ago

+1 Arguably "AI" is already plenty general enough, it's just not very intelligent.

worrycue 3y ago

Guess this is similar to ChatGPT and “ davidjl” - https://news.ycombinator.com/item?id=36242914 https://news.ycombinator.com/item?id=36242914 - and tricking image categorisers with specially designed noise. Today’s AI seem to have all sort of unexpected failure modes which can be exploited by adversarial attacks.

DemeterFarm 3y ago
[dead]
Zetobal 3y ago
Like humans?
- worrycue 3y ago
  The good thing is we have a lot of knowledge on human failure modes though and have planned around most of them. AIs are currently an unknown quality when it comes to their failure modes* and we are often caught by surprise when they fail at something that we expect they should be able to do because we don't fail at it. * Given how little we understand about how it all actually works in practice, I have a feeling we will never be able to fully grasp their failure modes unlike traditional computing.

rcme 3y ago

I think it depends on what you mean by understanding. KataGo taught itself to play go by explicitly deprioritizing “losing” strategies. This means it didn’t play many amateur strategies because they were lost early in the training. This is hard for a human to understand because humans all generally share a learning curve going from beginning to amateur to expert. So all humans have more experience with “losing” techniques. Basically what I’m saying is, it might be that the training scheme of this AI explicitly prioritized having little understanding of these specific tactics, which is different than not having any understanding.