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Many Machine Learning Studies Don't Actually Show Anything Meaningful, But They Spread Fear, Uncertainty, and Doubt (theoutline.com)
Michael Byrne, writing for the Outline: Here's what you need to know about every way-cool and-or way-creepy machine learning study that has ever been or will ever be published: Anything that can be represented in some fashion by patterns within data -- any abstract-able thing that exists in the objective world, from online restaurant reviews to geopolitics -- can be "predicted" by machine learning models given sufficient historical data. At the heart of nearly every foaming news article starting with the words "AI knows ..." is some machine learning paper exploiting this basic realization. "AI knows if you have skin cancer." "AI beats doctors at predicting heart attacks." "AI predicts future crime." "AI knows how many calories are in that cookie." There is no real magic behind these findings. The findings themselves are often taken as profound simply for having way-cool concepts like deep learning and artificial intelligence and neural networks attached to them, rather than because they are offering some great insight or utility -- which most of the time, they are not.
without the fun part.
That's what Skynet wants you to think.
When AI can teach itself how to use a programming language from documents found on the internet or solve a long unsolved mathematical puzzle, that'll be something to talk about.
---Technology will liberate us if it doesn't enslave us first.
The human brain sees pattern everywhere it looks too.
I'm retired now but I've been doing a lot of reading and experimentation with decision tree based classification methods. I like these because the produce models you can examine critically, as opposed to so-called "deep learning" algorithms which produce results that you pretty much have to judge by their giving you the result you expect. It's not that that isn't useful in some cases, but I don't find it as interesting.
Post may contain irony: discontinue use if experiencing mood swings, nausea or elevated blood pressure.
Or at least headlines are trying to achieve it.
Maybe we need to come up with a new word to describe when computers are used to generate meaningless connections between events. Or maybe we can add to Pareidolia's definition the idea that it can also find meaning in random information as well as sights and sounds. Oooo! That's it. Meta-Pareidolia. Finding meaning in random stimuli or information.
Who's this Albert person we keep hearing about? And maybe he'll even introduce a font that has unambiguous uppercase/lowercase letters.
I've been hearing about Artificial Intelligence since I read it in BYTE Magazine in the 1980's.
In the past it used to be stuff like "Scientists find that painting your room yellow leads to cancer!", now it's the same with AI. Turns out flipping through large amounts of statistical data until you happen upon a correlation is easily automated, and trash scientists will soon have to worry about their jobs.
AI has been ridiculously (and recklessly) hyped since its inception as an academic discipline. This is just more of the same. Unfortunately, the implication is that it is just as difficult today, as it was 60 years ago, to take AI seriously, despite what some fearmongers out there who, drunk with success in one area, seem to think that they are experts on everything, would like people to believe.
AI notices patterns that detect cancer. Woot! AI notices patterns that determines crime rates amongst certain population groups! Fuq no. (I can't wait until someone calls AI sexist for it noticing that females get pregnant much more often than males)
Studies simply exist to inform others of a topic of interest. The problem is not the studies being scary, the problem is that highly technical information is inappropriately being repackaged and pushed out to the general public who have no insight into topic. The problem isn't the message itself, it's the messengers.
Anons need not reply. Questions end with a question mark.
Doesn't everyone here already know this?
Yes. TFA is just stating the obvious: AI is based on technology, and not magic. Deep learning is pattern recognition and statistical classification. Real life isn't like the movies. Duh.
"AI" has simply joined "Web 2.0", "Cloud", and countless other terms that are meaningless buzzwords for use by marketing departments.
And I have a program in LISP that I wrote 30 years ago that has been saying the human race won't live past this week, every week, for three decades.
This is proof that we live in a virtual universe, probably written in Brainfuck.
AI or machine learning is just computing. That's all it is. And with better and faster computing resources, we can do more with it which makes sense. However, for "real" AI or machine learning to occur, there will need to be a biological substrate upon which such systems are to be built. I think this is the case because I believe that intelligent life is the universe's only way to "truly" conserve information.
Unless of course it's an experiment and not a shitty observational study.
Fixed it for you.
sed -e 's/Chuck Norris/Rajnikant/g' joke > fact
There are trainable models such AS neural networks/deep learning and statistical models. There are also models which habe to be configured. We can even combine them. In the end this is all just classification mechanisms. They are all good at detecting known issues. They are not able to come up with new stuff.