I recently visited a museum and i really loved it. Getting up close to an image and seeing none of the fuzziness, no AI “shimmer” on photos and every stroke made sense (as in you could see that an arm moved a brush and you could see the path it took etc.). Hands made sense. And while tryptichons were not exactly precise when it comes to the anatomy of humans, no humans had anything smeared etc.
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Eccitaze@yiffit.net 1 week ago
This process is akin to how humans learn by reading widely and absorbing styles and techniques, rather than memorizing and reproducing exact passages.
Like fuck it is. An LLM “learns” by memorization and by breaking down training data into their component tokens, then calculating the weight between these tokens. This allows it to produce an output that resembles (but may or may not perfectly replicate) its training dataset, but produces no actual understanding or meaning–in other words, there’s no actual intelligence, just really, really fancy fuzzy math.
Meanwhile, a human learns by memorizing training data, but also by parsing the underlying meaning and breaking it down into the underlying concepts, and then by applying and testing those concepts, and mastering them through practice and repetition. Where an LLM would learn “2+2 = 4” by ingesting tens or hundreds of thousands of instances of the string “2+2 = 4” and calculating a strong relationship between the tokens “2+2,” “=,” and “4,” a human child would learn 2+2 = 4 by being given two apple slices, putting them down to another pair of apple slices, and counting the total number of apple slices to see that they now have 4 slices. (And then being given a treat of delicious apple slices.)
Similarly, a human learns to draw by starting with basic shapes, then moving on to anatomy, studying light and shadow, shading, and color theory, all the while applying each new concept to their work, and developing muscle memory to allow them to more easily draw the lines and shapes that they combine to form a whole picture. A human may learn off other peoples’ drawings during the process, but at most they may process a few thousand images. Meanwhile, an LLM learns to “draw” by ingesting millions of images–without obtaining the permission of the person or organization that created those images–and then breaking those images down to their component tokens, and calculating weights between those tokens. There’s about as much similarity between how an LLM “learns” compared to human learning as there is between my cat and my refrigerator.
And YET FUCKING AGAIN, here’s the fucking Google Books argument. To repeat: Google Books used a minimal portion of the copyrighted works, and was not building a service to compete with book publishers. Generative AI is using the ENTIRE COPYRIGHTED WORK for its training set, and is building a service TO DIRECTLY COMPETE WITH THE ORGANIZATIONS WHOSE WORKS THEY ARE USING. They have zero fucking relevance to one another as far as claims of fair use. I am sick and fucking tired of hearing about Google Books.
MyFairJulia@lemmy.world 1 week ago
IndustryStandard@lemmy.world 1 week ago
If you put a gazillion monkeys on a typewriter they can write Shakespeare.
If you train one ai for a ton of epochs it can write Shakespeare.
All pure mathematical ccoïncidence.
MyFairJulia@lemmy.world 1 week ago
It was the best of times, it was the BLURST OF TIMES! Stupid monkey!
CeeBee_Eh@lemmy.world 1 week ago
If you put a gazillion monkeys on a typewriter they can write Shakespeare.
This is a mathematical curiosity borne out of pure randomness. An LLM trained on a dataset to generate similar content is quite the opposite of randomness.
CeeBee_Eh@lemmy.world 1 week ago
Like fuck it is. An LLM “learns” by memorization and by breaking down training data into their component tokens, then calculating the weight between these tokens.
But this is, at a very basic fundamental level, how biological brains learn. It’s not the whole story, but it is a part of it.
there’s no actual intelligence, just really, really fancy fuzzy math.
You mean sapience or consciousness. Or you could say “human-level intelligence”. But LLM’s by definition have real “actual” intelligence, just not a lot of it.
an LLM would learn “2+2 = 4” by ingesting tens or hundreds of thousands of instances of the string “2+2 = 4” and calculating a strong relationship between the tokens “2+2,” “=,” and “4,”
This isn’t true. At all. There are math specific benchmarks made by experts to specifically test the problem solving and domain specific capabilities of LLM’s. And you can be sure they aren’t “what’s 2 + 2?”
I’m not here to make any claims about the ethics or legality of the training. All I’m commenting on is the science behind LLM’s.
Eccitaze@yiffit.net 1 week ago
Get a load of this maroon, they think LLMs are actually sapient! Thanks, I needed that laugh.
CeeBee_Eh@lemmy.world 1 week ago
Get a load of this maroon, they think LLMs are actually sapient!
I guess reading comprehension is as bad here as it’s ever been on the internet.
Eccitaze@yiffit.net 1 week ago
Fine, you win, I misunderstood. I still disagree with your actual point, however. To me, Intelligence implies the ability to learn in real-time, to adapt to changes in circumstance, and for self-improvement. Once an LLM is trained, it is static and unchanging until you re-train it with new data and update the model. Even if you strip out the sapience/consciousness-related stuff like the ability to think critically about a scenario, proactively make decisions, etc., an LLM is only capable of regurgitating facts and responding to its immediate input. By design, any “learning” it can do is forgotten the instant the session ends.
ShepherdPie@midwest.social 1 week ago
I fear the courts will side with the tech companies on this as regardless of how illegal or immoral a certain act is, if you do it on a large enough scale it becomes “okay” again in the eyes of the system. Genocide, large scale fraud, negligent financial actions, pollution/poisoning, etc. You dump toxic chemicals into one person’s cup and you get the book thrown at you. You dump toxic chemicals into an entire city’s water supply and you pay a paltry fine that is never enough to seriously damage the company because that’s bad for the economy.