Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

An understanding of AI’s limitations is starting to sink in

economist.com

Post reply on HN
Print view View original

171–180 of 403 posts

Re: An understanding of AI’s limitations is starting to sink in

#171

Post by sdenton4 »

slykar wrote: post #113
tikititaki wrote: post #92

Earlier quoted context omitted.

While I can't speak for Siri, Google's voice recognition continues to surprise and even frighten me. And if you go online and look up deepfakes or AI generated voice of famous people, it also is freakishly accurate. Sure, there are some issues and most of them still fall somewhere in the uncanny valley.. but we are just starting to fully exploit this technology. AI that people don't tangibly see but make a giant impa…

I'm always disappointed with Google Asistant. When I say "navigate back home" it tries to route me to a company called "Home". Great job. I've included a hint "back". I've never been to a company called "Home". I'm after work. This is a fun example, but I never get good results. I say "weather" and it shows me the weather, just in a different city. FFS. Maybe in the next 5 years I'll be finally able to do something u…

That's the convolution of two problems:

a) Good general-purpose automatic speech recognition, which was an unattainable holy grail for DECADES. Previously, you would have to record a lot of your own voice to train the system for you in particular before it was at all reliable. Now it basically just works.

b) Making good use of the results of (a). Your examples are clearly in this category. This is ALSO a very hard problem; voice interfaces are basically brand new creatures, and I expect we'll be seeing 'best practices' form up for a while yet.

Re: An understanding of AI’s limitations is starting to sink in

#172

Post by MiroF »

rubber_duck wrote: post #76
MiroF wrote: post #16

Earlier quoted context omitted.

Absolutely. To be perfectly honest, it surprises me the extent to which ML naysaying seems to be popular on HN. The evidence of enormous progress seems pretty obvious to me.

I recently watched a podcast with Stephen Wolfram (few months old) where he runs a photo of himself through Wolfram Alpha "ImageIdentify" and it classifies him as a plunger with 50% probability and 8% probability it's a human [1]. He then goes on saying how he's working on systems that would allow a self driving system decide what to do based on if the collision detected is a human or inanimate object, etc. This was…

Classification accuracy is crazy good, I'm surprised that an obvious photo of him would be viewed as a plunger unless it's an adversarial example.

No offense to Wolfram, but they really are hardly at the cutting edge of ML research nonetheless.

Re: An understanding of AI’s limitations is starting to sink in

#173

Post by MiroF »

Judgmentality wrote: post #104
p1esk wrote: post #56

Earlier quoted context omitted.

Things may have changed over the past 5 years or so. Things may have changed over the past 5 weeks or so with GPT-3.

Until GPT-3 can write something meaningful, it's really just a showcase of the technology and a gimmick of a product. Sure it's cool, but what problem is it solving? As far as I can tell the only useful function it has is polluting the internet with pseudo-intellectual comments to promote some agenda (likely political). So now that I think about it, it actually would be incredibly valuable for things like subverting…

There's a ton of problems that a quality language model like GPT-3 can solve, beyond just spamming text generation - stuff like translation quality, automatic post-editing of text, classification, etc.

Re: An understanding of AI’s limitations is starting to sink in

#174

Post by MiroF »

criddell wrote: post #49
MiroF wrote: post #16

Earlier quoted context omitted.

Absolutely. To be perfectly honest, it surprises me the extent to which ML naysaying seems to be popular on HN. The evidence of enormous progress seems pretty obvious to me.

I wonder if it's because of the name machine learning ? It seems a lot of applications boil down to some type of discriminator or pattern matcher.

> It seems a lot of applications boil down to some type of discriminator or pattern matcher

This doesn't seem to imply that no learning is going on or that there is some sort of simple process. If I ask you to say whether something is a cat or a dog, you are essentially functioning as a discriminator there - but there is still a lot of process that goes on behind that.

Re: An understanding of AI’s limitations is starting to sink in

#175

Post by MiroF »

tr352 wrote: post #82
mtgp1000 wrote: post #11

I'm not sure how anyone who's watched the exponential growth of a brand new domain can pick a point today to and say that things aren't as good as we expected. What may have happened was that some eager CEOs have overpromised on timelines and resources. But the revolution is coming, ML is already starting to change society. We're building the tech. Right now. The author does not even realise the immeasurable potentia…

Perhaps basing our decisions on general purpose function approximators (whether forced or voluntarily) has not served us so well, ultimately. I think they play an important role in causing, or at least enabling, much of the trouble that we live in nowadays.

How?

Re: An understanding of AI’s limitations is starting to sink in

#176

Post by ppod »

tomp wrote: post #101
eanzenberg wrote: post #87

This is so strange. If you use facebook, google, netflix, apple, microsoft, amazon, tesla or a whole host of other products and services you are interfacing with AI all the time, sometimes as the core product of the service. To think there’s no value there is asinine. Comes up a lot on HN. Seems like people who get excited for these types of articles are set in their ways and don’t want to progress forward.

Aside from possibly Google, all of these products / services would have just as much, if not more, value without any AI beyond basic statistics.

That's an illusory distinction.

Re: An understanding of AI’s limitations is starting to sink in

#177

Post by bcrosby95 »

01100011 wrote: post #149
mattlondon wrote: post #53

The trouble is that people have been sold this idea that ML/AI can do amazing things, without properly being told that really the things it can do are quite narrowly-scoped. They've been sold the Star Trek computer idea. For example, years ago I was working on a prototype/proof-of-concept thing for instrumenting industrial machinery with stick-on small computers. Simple stuff - attach accelerators, temperature, humid…

> currently ML/AI requires us to know what the possible answers can be before we even begin training the network Isn't that what unsupervised learning is for?

I took it more to mean that, e.g., when solving for 1+1 it won't be allowed to answer "tomatoes".

Re: An understanding of AI’s limitations is starting to sink in

#179

Post by lopmotr »

joe_the_user wrote: post #169
Kaibeezy wrote: post #116

Earlier quoted context omitted.

Where are stop signs hexagons? Am I being a pedantic numpty or am I illustrating a point about the many ways errors creep in, regardless of the natural- or artificial-ness of the intelligence?

You're being a pedantic. Human beings are tremendously better at driving than machines despite sometimes saying hexagonal rather than octagonal. Humans and current AIs both make mistakes but humans manage a kind of robustness, ability to deal gracefully with unexpected situations, that current AIs don't seem to be progressing towards.

What happened to sensor fusion? There's no reason self-driving AI has to be as unreliable as toy or research AI. People made these same FUD arguments about computer in cars decades ago. Home computers were unreliable so cars will surely crash if their brakes or throttles are controlled by computers too.

Re: An understanding of AI’s limitations is starting to sink in

#180

Post by lokedhs »

kordlessagain wrote: post #145
Veedrac wrote: post #68

Earlier quoted context omitted.

https://youtu.be/hx7BXih7zx8?t=513

> complicated when you get to the long tail of it Well, there's the problem right there.

Watching this presentation did not make me any more confident about going in a self-driving car.

Based on the way it was presented, I got the feeling that they are just essentially manually identifying cases and addressing them as they see them. Is that solution really helping to make the system more robust when encountering an unexpected situation?

Post reply on HN