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Most people can't even imagine the complexity required to build an LLM. But here we are.

We throw plenty of smart people at plenty of hard ideas. If a company really wanted to, they would find a way to make this feasible.

by JAlexoid1 hours ago|

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Funny thing is that building an LLM isn't as complex as you might think.

But the problem of attribution is easily understandable to any human with a modicum of intelligence.

Imagine that you have a trillion input images, with every single one having a source associated. When training they go through lots of processes and every single image contributes a varying degree to a subset of 8billion parameters. That alone would produce a dataset that is 1T * 8B to just say how much a particular image contributed to the output...

To mimic intelligence the output is also randomized - the association is not static and every single pixel in the output has it's own lineage.

So as you can probably imagine that to calculate the actual source weights on the output you'd require to do at least 8e+21 calculations per output pixel... and require double precision floating point while you do it.

We know how to do it. It's just ridiculously expensive.

(The above example is for demonstrative purposes only)

by abustamam4 minutes ago|

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Insults aside, you chose a very expensive way to solve the attribution problem. But my rebuttal is simple: we are literally commenting in a thread about an AI image generator that paid people. It didn't work, but if a company I've never heard of can try an experiment like this, I'm sure our billion dollar AI overlords could if they wanted to.