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How to recognize AI snake oil [pdf]

cs.princeton.edu

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Re: How to recognize AI snake oil [pdf]

#31

Post by monocasa »

mrweasel wrote: post #27
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.

Even companies like Facebook, Apple and Google employee humans to do work that people believe is done by "computers" and non of the companies seem keen on informing the public that they do in fact have humans scanning through massive amounts of data. So perhaps it is in fact cheaper, or the problems they face remains to hard for current types of AI. Given the number of people Facebook employees to censor content and…

Well, just about any ML task needs people to prune and correct the training data.

Re: How to recognize AI snake oil [pdf]

#33

Post by wlesieutre »

Tistel wrote: post #16

I worked at a place that was selling ML powered science instrument output analysis. It did not work at all (fake it till you make it is normal, was told). So there was a person in the loop (machine output -> internet -> person doing it manually pretending to be machine -> internet -> report app). The joke was “organic neural net.” Theranos of the North! ML is a great and powerful pattern matcher (talking about NN not…

There's a recent xkcd about your company: https://xkcd.com/2173/

"We trained a neural network to oversee the machine output"

Re: How to recognize AI snake oil [pdf]

#35

Post by scottlegrand2 »

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.

20+ years ago I used to refer to this is as artificial artificial intelligence (AAI) specifically as part of a pitch to MGM for an MMORPG to run their non-player characters. Not surprisingly, it didn't catch on...

Re: How to recognize AI snake oil [pdf]

#36

Post by sanchezdev »

formalsystem wrote: post #15

Over the years my heuristic has turned into: "Did the team formulate their problem as a supervised learning problem?" - If not it's probably BS. In longform if anyone is interested https://medium.com/@marksaroufim/can-deep-learning-solve-my-... EDIT: I would consider autoencoders, word2vec, Reinforcement Learning examples of turning a different problem into a supervised learning problem EDIT 2: Social functions like…

I basically agree with this rule. I find that my colleagues who overly hype unsupervised approaches typically don't have much experience working on ML problems without labeled data. My suspicion of this comes from the fact that whenever I give a talk on ML I always have a wealth of personal experience to draw on for examples. My colleagues almost always reuse slides from projects they never worked on.

Re: How to recognize AI snake oil [pdf]

#37

Post by rm_-rf_slash »

Tistel wrote: post #16

I worked at a place that was selling ML powered science instrument output analysis. It did not work at all (fake it till you make it is normal, was told). So there was a person in the loop (machine output -> internet -> person doing it manually pretending to be machine -> internet -> report app). The joke was “organic neural net.” Theranos of the North! ML is a great and powerful pattern matcher (talking about NN not…

We won’t ever have an AI winter like in the 70s again. A lot of ML is already very useful across many domains (computer vision, NLP, advertising, etc). Back then, there was almost no personal computing, almost no internet, smol data, and so on. Stuff you need for ML to be useful and used.

So what if some corporate hack calls linear regression “AI”? The results speak for themselves. The ML genie is too profitable to go back in the bottle.

Re: How to recognize AI snake oil [pdf]

#38

Post by SkyBelow »

What I dislike far more than the idea of using such systems to predict social outcome is that the usage of such systems is done behind closed doors. I would be much more willing to accept such systems if the law required any system to be fully accessible online, including the current neural network, how it was trained, and training data used to train it (if the training data cannot be shared online, then the neural network trained from it cannot be used by the government).

Independent companies using AI is far less a concern for me. If they are snake oil, people will learn how to overcome them. Government (especially parts related to enforcement) is what I find scary.

Re: How to recognize AI snake oil [pdf]

#40

Post by sillysaurusx »

sanchezdev wrote: post #36
formalsystem wrote: post #15

Over the years my heuristic has turned into: "Did the team formulate their problem as a supervised learning problem?" - If not it's probably BS. In longform if anyone is interested https://medium.com/@marksaroufim/can-deep-learning-solve-my-... EDIT: I would consider autoencoders, word2vec, Reinforcement Learning examples of turning a different problem into a supervised learning problem EDIT 2: Social functions like…

I basically agree with this rule. I find that my colleagues who overly hype unsupervised approaches typically don't have much experience working on ML problems without labeled data. My suspicion of this comes from the fact that whenever I give a talk on ML I always have a wealth of personal experience to draw on for examples. My colleagues almost always reuse slides from projects they never worked on.

I'm a little surprised to see this sentiment. Some of the most important advances in the field have been unsupervised tasks:

- OpenAI: Dota 2 (PPO), GPT-2...

- NVidia: StyleGAN, BigGAN, ProGAN...

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