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Is there any way to save storage on similar images?
(lemmy.pe1uca.dev)
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this post was submitted on 05 Sep 2024
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computers make decisions all the time. For example, how to route my packets from my instance to your instance. Classification functions are well understood in computer science in general, and, while stochastic, can be constructed to be arbitrarily precise.
https://en.wikipedia.org/wiki/Probably_approximately_correct_learning?wprov=sfla1
Human facial detection has been at 99% accuracy since the 90s and OPs task I'd likely a lot easier since we can exploit time and location proximity data and know in advance that 10 pictures taken of Alice or Bob at one single party are probably a lot less variant than 10 pictures taken in different contexts over many years.
What OP is asking to do isn't at all impossible-- I'm just not sure you'll save any money on power and GPU time compared to buying another HDD.
Everything you just described is instruction. Everything from an input path and desired result can be tracked and followed to a conclusory instruction. That is not decision making.
Again. Computers do not make decisions.
Agree to disagree. Something makes a decision about how to classify the images and it's certainly not the person writing 10 lines of code. I'd be interested in having a good faith discussion, but repeating a personal opinion isn't really that. I suspect this is more of a metaphysics argument than anything and I don't really care to spend more time on it.
I hope you have a wonderful day, even if we disagree.
It's Boolean. This isn't an opinion, it's a fact. Feel free to get informed though.
Then it should be easy to find peer reviewed sources that support that claim.
I found it incredibly easy to find countless articles suggesting that your Boolean is false. Weird hill to die on. Have a good day.
https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=computer+decision+fairness&oq=computer+decison
LITERALLY from a "baby's first 'puter" course: https://highered.mheducation.com/sites/007256380x/student_view0/part1/chapter2/reading_selection_quiz.html#:~:text=Although%20computers%20may%20appear%20to,humans%20who%20programmed%20the%20computers.&text=Humans%20are%20smarter%20than%20computers.&text=It%20is%20extremely%20time%2Dconsuming,that%20it%20makes%20correct%20decisions.
Or if you need something more ELI5: https://www.reddit.com/r/explainlikeimfive/comments/160lwe8/eli5_where_exactly_do_computers_make_decisions/
You seem very upset, so I hate to inform you that neither one of those are peer reviewed sources and that they are simplifying things.
"Learning" is definitely something a machine can do and then they can use that experience to coordinate actions based on data that is inaccesible to the programmer. If that's not "making a decision", then we aren't speaking the same language. Call it what you want and argue with the entire published field or AI, I guess. That's certainly an option, but generally I find it useful for words to mean things without getting too pedantic.
🙄
"Pedantic Asshole tries the whole 'You seem upset' but on the Internet and proceeds to try and explain their way out of being embarrassed about being wrong, so throws some idiotic semantics into a further argument while wrong."
Great headline.
Computers also don't learn, or change state. Apparently you didn't read the CS101 link after all.
Also, another newsflash is coming in here, one sec:
"Textbooks and course plans written by educators and professors in the fields they are experts in are not 'peer reviewed' and worded for your amusement, dipshit."
Whoa, that was a big one.
I think there's probably a difference between an intro to computer science course and the PhD level papers that discuss the ability of machines to learn and decide, but my experience in this is limited to my PhD in the topic.
And, no, textbooks are often not peer reviewed in the same way and generally written by graduate students. They have mistakes in them all the time. Or grand statements taken out of context. Or are simplified explanations because introducing the nuances of PAC-learnability to somebody who doesn't understand a "for" loop is probably not very productive.
I came here to share some interesting material from my PhD research topic and you're calling me an asshole. It sounds like you did not have a wonderful day and I'm sorry for that.
Did you try learning about how computers learn things and make decisions? It's pretty neat