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charronia t1_j988nc7 wrote

Sounds like a liability nightmare. You put one of these in your cars, without being able to predict what it's gonna do in any given situation because it keeps modifying itself.


Hawk13424 t1_j98wlhk wrote

Kind of like people?


whiteknives t1_j99cw87 wrote

People are, indeed, liability nightmares.

They’re easily distracted, highly variable in vision acuity and intelligence, unpredictable, prone to fatigue, and their judgment is readily compromised by any number of external factors.

If cars were invented today, humans would almost certainly be banned from driving them.


Toysoldier34 t1_j99wx6f wrote

Did you read it and understand what is going on? Machine learning by nature is always evolving and modifying itself, that is what makes it good. That said, it can still be saved in a form that doesn't change, like what they would use as different versions for cars.

Some parts from the article to reread.

> “Their method is beating the competition by several orders of magnitude without sacrificing accuracy,” said Sayan Mitra, a computer scientist at the University of Illinois, Urbana-Champaign. > > As well as being speedier, Hasani said, their newest networks are also unusually stable, meaning the system can handle enormous inputs without going haywire. “The main contribution here is that stability and other nice properties are baked into these systems by their sheer structure,” said Sriram Sankaranarayanan, a computer scientist at the University of Colorado, Boulder. Liquid networks seem to operate in what he called “the sweet spot: They are complex enough to allow interesting things to happen, but not so complex as to lead to chaotic behavior.”