How to recognize AI snake oil [pdf]
261–270 of 364 posts
Re: How to recognize AI snake oil [pdf]
#262Earlier quoted context omitted.
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.…
Re: How to recognize AI snake oil [pdf]
#263Earlier quoted context omitted.
FYI, I too looked at his categorisation of what was/was advancing/was not snake oil and didn't exactly agree with all his decisions either. Medical imaging diagnosis was one of them. Speech recognition/transcription was another. I don't know if it's my accent or my speech patterns(though foreigners regularly compliment my wife and myself on our pronunciation), but the tech hasn't gotten noticeably better for me since…
I feel like it’s gotten loads better. You can watch as the voice recognition on your phone changes the words it recognizes to match the context in the sentence. Sometimes it gets a word wrong and fixes it after a half second. Google translate does magical things recognizing common phrasing constructions and bad accents, stuff that Dragon could never do. I built a lipsync pipeline for video games based on Dragon a dec…
It is one of my most frustrating everyday software experiences.
Not only is it not getting better, its actually getting worse, because before I at least had the correct sentence. Now my correct sentence is mangled as it tries to force corrections/substitutions, and I have to continually go back and manually-correct the auto-correct.
It seems to work for me on short pre-formed sentences and toy examples (if you communicate using pre-formed phrases and use well-worn cliches in your writing, it seems to pick up and predict for them). I wonder whether the "increased accuracy" of modern solutions aren't just functionally having access to a larger library of lookup rules of stored common/popular phrases and direct translations (a huge part of practical 'AI' advancement has been on the scaling-infrastructure/collection of new-scales-of-data rather than the AI techniques themselves IMO) effectively mined from its training data, but the moment I try to write or dictate anything new, original, or lengthy and it turns absolutely pear-shaped.
Re: How to recognize AI snake oil [pdf]
#264I don't have time to read the entire paper but I would like to share an anecdote. I worked at a company with a well staffed/funded machine learning team. They were in charge of recommendation systems - think along the lines of youtube up next videos. My team wanted better recommendations (really, less editorial intensive) so the ML team spent weeks crafting 12 or more variants of their recommendation system for our c…
Since we are sharing anecdotes, I can report it's been 20 years of buying stuff on the internet and the combined billions of ad tracking research dollars spent by Amazon and Google have not yet come up with a better algorithm than to bombard me with ads for the exact same thing I just bought .
Re: How to recognize AI snake oil [pdf]
#265Re: How to recognize AI snake oil [pdf]
#266Earlier quoted context omitted.
Dirty secret: "The customers who bought also bought" algorithm doesn't require ML/AI. You can accomplish that with relational algebra on a precomputed data warehouse job and only for products with strong correlation. The intelligence of the customers is enough agency to instil a semblance of intelligence in the data.
Yes, this is the straightforward ‘collaborative filtering’ algorithm. I suppose the line between ‘algorithm’ and AI/ML is not well defined though. At what point does a technique become ‘AI’? I don’t know a good answer.
Re: How to recognize AI snake oil [pdf]
#267Earlier quoted context omitted.
That sounds odd, like they don't really need machine learning (unless it is to snare investors?).
Snaring customers too. I swear, people are obsessed with "machine learning" even when the domain really isn't suited for it.
Re: How to recognize AI snake oil [pdf]
#268Perhaps ML could be applied here to help filter out the barrage of AI snake oil. Funding, anyone?
Re: How to recognize AI snake oil [pdf]
#269Earlier 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…
It's quite common in games for AI to pick a random decision. Simply put, a good AI is a character/NPC that appears to have a mind of its own, and its own life. Nothing beats random at explaining someone's behaviour based on a personal history you don't know. If AI responded/acted based on a predefined set of patterns that could be recognizable, the player would automatically feel it (pattern matching) and makes the N…
Re: How to recognize AI snake oil [pdf]
#270I don't have time to read the entire paper but I would like to share an anecdote. I worked at a company with a well staffed/funded machine learning team. They were in charge of recommendation systems - think along the lines of youtube up next videos. My team wanted better recommendations (really, less editorial intensive) so the ML team spent weeks crafting 12 or more variants of their recommendation system for our c…
Since we are sharing anecdotes, I can report it's been 20 years of buying stuff on the internet and the combined billions of ad tracking research dollars spent by Amazon and Google have not yet come up with a better algorithm than to bombard me with ads for the exact same thing I just bought .