The current assumption made by these companies is that AI training is fair use, and is therefore legal regardless of license. There are still many ongoing court cases over this, but one case was already resolved in favor or the fair use position.
The current assumption made by these companies is that AI training is fair use, and is therefore legal regardless of license. There are still many ongoing court cases over this, but one case was already resolved in favor or the fair use position.
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Amdahl’s isn’t the only scaling law in the books.
Gustafson’s scaling law looks at how the hypothetical maximum work a computer could perform scales with parallelism—idea being for certain tasks like simulations (or, to your point, even consumer devices to some extent) which can scale to fully utilize, this is a real improvement.
Amdahl’s takes a fixed program, considers what portion is parallelizable, and tells you the speed up from additional parallelism in your hardware.
One tells you how much a processor might do, the only tells you how fast a program might run. Neither is wrong, but both are incomplete picture of the colloquial “performance” of a modern device.
Amdahl’s is the one you find emphasized by a Comp Arch 101 course, because it corrects the intuitive error of assuming you can double the cores and get half the runtime. I only encountered Gustafson’s law in a high performance architecture course, and it really only holds for certain types of workloads.
ABSOLUTELY. I just recently capped off the Diff Eq, Signals, and Controls courses for my undergrad, and truly by the end you feel like a wizard. It’s crazy how much problem-solving/system modeling power there is in such a (relatively) simple, easy to apply, and beautifully elegant mathematical tool.
Chameleon is another good plugin for this
I’m curious what issue you see with that? It seems like the project is only accepting unrestricted donations, but is there something suspicious about shopify that makes it’s involvement concerning (I don’t know much about them)?