This seems like a very good use of the tech. Fuzzy testing is difficult to do, and it’s all about scale
Comment on G-Assist is ‘real’: NVIDIA unveils NitroGen, open-source AI model that can play 1000+ games for you
Dojan@pawb.social 23 hours agoMakes sense. Upscaling and video interpolation instead of optimisation. Image generation instead of artists. Now this instead of actual testing.
The 💩💩💩 gaming industry is going to somehow get even worse.
Miaou@jlai.lu 15 hours ago
Dojan@pawb.social 14 hours ago
This is all on the assumption it’ll work and be useful. The track record so far is underwhelming.
riskable@programming.dev 21 hours ago
Good games are orthogonal to AI usage. It’s possible to have a great game that was written with AI using AI-generated assets. Just as much as it’s possible to have a shitty one.
If AI makes creating games easier, we’re likely to see 1000 shitty games for every good one. But at the same time we’re also likely to see successful games made by people who had great ideas but never had the capital or skills to bring them to life before.
I can’t predict the future of AI but it’s easy to imagine a state where everyone has the power to make a game for basically no cost. Good or bad, that’s where we’re heading.
If making great games doesn’t require a shitton of capital, the ones who are most likely to suffer are the rich AAA game studios. Basically, the capitalists. Because when capital isn’t necessary to get something done anymore, capital becomes less useful.
Effort builds skill but it does not build quality. You could put in a ton of effort and still fail or just make something terrible. What breeds success is iteration (and luck). Because AI makes iteration faster and easier, it’s likely we’re going to see a lot of great things created using it.