Post #4131041

2026-07-19 20:06 UTC

If you don’t intend to sell or distribute that game, the only aspects left that I can think of are: you’re not helping yourself by using AI, you’re just making yourself dumber, so if your goal is simply to make a game, fine, but if you want to maintain your coding skills, it’s a bad idea. the extra energy consumption, which happens regardless if you’re using your GPU or someone else’s GPU. Might even be worse if everyone uses their own GPU, because there’s a whole ass PC system built around that GPU that also consumes power. But I dunno if that’s the case, actually. I guess this is moot if you’re off the power grid with your own power source, such as full solar or something. how has the open source model been trained? On what data?

Replies (1)

@Epp@lemmus.org 2026-07-19 20:58

Even if I did intend to sell the game, what change is there? Everything created was something that did not exist prior my prompt to create it. I’m making myself dumber in the same sense that learning to read & write weakens my memory skills, using a calculator weakens my math skills, or driving a car weakens my physical stamina. Everything is a trade off, and like in everything else, balance is the key consideration. Correct, I personally have a solar array with a battery system. I typically have an overage, and feed my power back into the network. Even if I didn’t, though, using my GPU for AI uses less electricity than playing a game with it, and even that is dwarfed by microwaving food, using a hair dryer, clothes dryer, etc. Power consumption is a common concern that is shared with everything, so there’s no justification to make it an ethical one just for AI. In my case, I’m using Qwen, and Kimi, which are both models trained by other models - essentially compressing the original training so a good analogy, if these were people, is my models were trained by professors who themselves trained themselves by reviewing the entirety of the Internet. It’s important, though, to highlight the fact that as neural networks this training is not retention of data - it’s simply adjusting the weights of simulated synapses based on the tagging of input. So many people seem to think that training means the model has like a compressed database of source material, but that is not the case - even on the original models that trained using pirated data, at no point is the training data incorporated into the model. It informs the model, in the same way you are informed about art by watching a Disney movie. Sure, you might be able to recreate something you saw from memory if you focused on doing that, but it’s not like you can make a perfect copy from your memory. The LLM are NOT idetic.

Open ##4131040