Well, they're just wrong lol. Traditionally, AI is about agents making rational decisions in an environment. The "game dev" definition they used, "AI is any computer process that’s driving...
AI purists don’t consider the AI that works under the hood of video games to be "true AI," which is trained from real-world data to make decisions about the world around it
Well, they're just wrong lol. Traditionally, AI is about agents making rational decisions in an environment. The "game dev" definition they used, "AI is any computer process that’s driving decision-making by an agent" is a pretty solid one, and good on them for having a real basis when talking about "AI".
Then they have this bullet point though
"We can rebuild you": AI can improve the look of old games
Aw, c'mon, that doesn't fit your own definition. What part of ESRGAN involves an agent, in an environment, making decisions? If you really want to stretch it you can say the discriminator, but obviously this is going into "machine learning NEURAL NETWORKS = AI".
A side note:
Training AI to identify something new based on previous examples is a major field of modern computer science and often called machine learning.
Modern? Linear regression was studied by Gauss in 1909 :(, that's before computers existed. And a "neural network" is, in the end, a bunch of linear functions of the form z = wx + b, put into typically relu, which is just relu(x) = max(x, 0), and fed into more layers. Fitting linear lines is what machine learning is all about.
Well, they're just wrong lol. Traditionally, AI is about agents making rational decisions in an environment. The "game dev" definition they used, "AI is any computer process that’s driving decision-making by an agent" is a pretty solid one, and good on them for having a real basis when talking about "AI".
Then they have this bullet point though
Aw, c'mon, that doesn't fit your own definition. What part of ESRGAN involves an agent, in an environment, making decisions? If you really want to stretch it you can say the discriminator, but obviously this is going into "
machine learningNEURAL NETWORKS = AI".A side note:
Modern? Linear regression was studied by Gauss in 1909 :(, that's before computers existed. And a "neural network" is, in the end, a bunch of linear functions of the form z = wx + b, put into typically relu, which is just relu(x) = max(x, 0), and fed into more layers. Fitting linear lines is what machine learning is all about.