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

How to recognize AI snake oil [pdf]

cs.princeton.edu

Post reply on HN
Print view View original

151–160 of 364 posts

Re: How to recognize AI snake oil [pdf]

#151

Post by cycrutchfield »

Fr0styMatt88 wrote: post #148
cycrutchfield wrote: post #103

Earlier quoted context omitted.

YouTube's "Up Next" recommendations do (significantly) better than random, therefore "Today ML can solve some problems".

I'm pretty sure it does better than 'next video = random(from all of YouTube)' would, but would it be much better than 'next video = random(videos with the same subject or tags as the one playing now)'?

Yes. They've published quite a number of papers on their recommendation algorithms. You can take a look and decide for yourself whether it's snake oil or not.

Re: How to recognize AI snake oil [pdf]

#152

Post by ping_pong »

buboard wrote: post #14
avip wrote: post #10

My company is sourcing AI from MTurk. It's actually cheaper than running fat GPU model training instances. The network learns fast and adapts well to changes in inputs. I envision the sticker "human inside" strapped on our algorithms.

You should emphasize that this is Organic AI. It's low carbon and overall greener.

I like calling them MeatBots

Re: How to recognize AI snake oil [pdf]

#153

Post by cycrutchfield »

simion314 wrote: post #131
cycrutchfield wrote: post #103

Earlier quoted context omitted.

YouTube's "Up Next" recommendations do (significantly) better than random, therefore "Today ML can solve some problems".

>YouTube's "Up Next" recommendations do (significantly) better than random, therefore "Today ML can solve some problems". IMO YT AI is the opposite of intelligent , it still recommends things I disliked. for some reason this basic rule of not showing something that I explicitly disliked was to hard for it to learn, I am wondering if it is truly an AI behind it or just statistics

If the goal is simply to maximize engagement, there is no hard requirement that the algorithm should never show you things that you dislike. Essentially, what I am saying is that your belief of what their objective function is may be different from their actual objective function, and that is in no way an indication that their model is a failure.

Re: How to recognize AI snake oil [pdf]

#154

Post by GoForthAssemble »

AareyBaba wrote: post #146
JoeAltmaier wrote: post #105

Earlier quoted context omitted.

The San Jose Mercury News had a weather-forecasting contest. It was won one year by a 12-year-old, who's algorithm was "The weather tomorrow will be the same as the weather today". A kind of AI I guess.

Brilliant. I think YouTube has arrived at the same algorithm - it picks the videos I watched yesterday to recommend today.

Completely ignoring the depth of your subscriptions as well. Amazon music was much better for me. Even Google music just repeats.

Re: How to recognize AI snake oil [pdf]

#155

Post by mike_hock »

AareyBaba wrote: post #146
JoeAltmaier wrote: post #105

Earlier quoted context omitted.

The San Jose Mercury News had a weather-forecasting contest. It was won one year by a 12-year-old, who's algorithm was "The weather tomorrow will be the same as the weather today". A kind of AI I guess.

Brilliant. I think YouTube has arrived at the same algorithm - it picks the videos I watched yesterday to recommend today.

Seriously. Why would I want to watch a video that I've already watched (unless it's music maybe)?

Re: How to recognize AI snake oil [pdf]

#156

Post by chimi »

tensor wrote: post #142
chimi wrote: post #125

Earlier quoted context omitted.

It's hard to verbalize this, most of it is "intuition" but I think it boils down to "supervised learning is BS." Humans are smarter than computers. How can a human teach a computer how to do something when the human itself can't teach another human that something? We haven't solved that problem. The snake is eating its tail. You can't teach a human how to do something when the methodology to do that is the student tr…

Supervised learning in machine learning is nothing remotely like a human teaching anyone anything. It's a very clear mathematical formulation of what the objective is and how the algorithm can improve itself against that objective. The closest analogy for humans would be to define a metric and ask a human to figure out how to maximize that metric. That's something we're often pretty good at doing, often in ways that…

> Supervised learning in machine learning is nothing remotely like a human teaching anyone anything.

I disagree, I think it's exactly the same. As an example, a human teaching a human how to use an orbital sander to smooth out the rough grain of a piece of wood.

The teacher sees the student bearing down really hard with the sander and hears the RPM's of the sander declining as measured by the frequency of the sound.

The teacher would help the student improve by saying, "Decrease pressure such that you maximize the RPM's of the sander. Let the velocity of the sander do the work, not the pressure from your hand."

That's a good application of supervised learning. Hiring the right candidate for your company is not.

Re: How to recognize AI snake oil [pdf]

#157

Post by JimmyRuska »

nradov wrote: post #133
mezentius wrote: post #100

Earlier quoted context omitted.

>>The best performing variant happened to be random. Some years ago I heard an anecdote from a developer who had worked on a video game about American football. The gist of it was that they had tested various sophisticated systems for an AI opponent to choose a possible offensive/defensive play, but the one that the players often considered the most "intelligent" was the one that simply made random decisions. In cert…

Humans are great at finding "patterns" in random noise.

Sometimes being unpredictable makes for a good strategy

Re: How to recognize AI snake oil [pdf]

#158

Post by erikig »

sgt101 wrote: post #87

I read "Why are HR departments apparently so gullible?" and as someone who has worked in a corporate for 20 years I spotted my underwear. The identification of facial recognition as problematic because of accuracy doesn't match my thinking. I believe that the key issue is that given a set of targets facial recognition systems will find near misses from the wider population of all faces offered as candidates, that the…

...I spotted my underwear?

What does this mean?

Re: How to recognize AI snake oil [pdf]

#159

Post by zamadatix »

nradov wrote: post #133
mezentius wrote: post #100

Earlier quoted context omitted.

>>The best performing variant happened to be random. Some years ago I heard an anecdote from a developer who had worked on a video game about American football. The gist of it was that they had tested various sophisticated systems for an AI opponent to choose a possible offensive/defensive play, but the one that the players often considered the most "intelligent" was the one that simply made random decisions. In cert…

Humans are great at finding "patterns" in random noise.

We are very good at finding patterns where there aren't any but it's important to remember that random is actually the best answer a lot of the times. Maybe it's as simple as random plays being the hardest to predict and that's the best until you can get an AI trained on the meta of how to plan for what the current player is thinking you'll do.

Re: How to recognize AI snake oil [pdf]

#160

Post by JimmyRuska »

AareyBaba wrote: post #146
JoeAltmaier wrote: post #105

Earlier quoted context omitted.

The San Jose Mercury News had a weather-forecasting contest. It was won one year by a 12-year-old, who's algorithm was "The weather tomorrow will be the same as the weather today". A kind of AI I guess.

Brilliant. I think YouTube has arrived at the same algorithm - it picks the videos I watched yesterday to recommend today.

Well to be fair that's how all employers also hire.

If you did a good job at the last company you'll probably do a good job here.

If you did a good job yesterday, you'll probably do a good job today.

For the most part they are usually correct.

Post reply on HN