> Nobody would say a human reading a book and learning from it is stealing. I'm not saying that a machine doing the same is equivalent, but the only think I am sure of is that I am not sure we can call it "stealing".

It is stealing. A human paid for the book, compensated the author and learnt from it. The machine DID NOT pay for the book, DID NOT compensate the author and still learnt from it anyways.

We need to define machine in terms of "human-power"... much the same as how we already define automobiles via "horse-power". A single NVIDIA GeForce RTX 3090 chip, for example, delivers roughly 35.58 teraflops of standard computing power (via 10,496 CUDA cores). That means 35.58 trillion calculations every second. In comparison, a mathematically trained human being, taking their time to solve a complex, multi-digit decimal division problem by hand takes roughly 100 to 120 seconds. That gives the human 0.01 flops. To match RTX 3090, you would need 3.56 quadrillion people working/learning in perfect sync. We can use a calculation similar to this to derive metrics on how much is being stolen for "learning/training" these models. The loot can be quantified.

EDIT: The reason I am comparing chip computation to human-power is because the authors of those digital works intended their works to only be read by humans. Not by some alien species (even if it be made of silicon) that incorporated their work into producing models.

So naturally the price should be determined based on this new species capabilities. I would not sell my software license for the same price to an Enterprise the size of Google that I would sell to a fellow developer. I price my product appropriately. With this entry of a new alien specie authors would need to have different tiers for them. Since these chips can train on petabytes of data and create models in a matter of days/weeks/months, it is obviously not comparable to a human being who has the capacity to ingest maybe 1-5 books a month at most. So the payout has to be different too.