Most of the approaches used are re-usable, which is a big part of why we can develop new AIs for games faster than ever. You can take the algorithm(s) that was used in one game and use it in another.

Yes, a human is still needed to decide which approach to use, but we are slowly approaching a world where building an AI becomes easier and faster. It will become absolutely irrelevant that a single AI can not play all games, because whenever a new game comes out, someone will be able to build a superhuman AI on it within a week/month.

The brains of an AI are also transferrable. Built a superhuman AI? Send it to a friend! Compare it to a human, who would need to spend enormous amounts of time to transfer their game-brain to someone else. If you want, you can bundle all those AIs into one and pretend it can play any game.

"It's amazing that most people here don't understand that human performance in all computer games relative to AIs is largely irrelevant"

>> The brains of an AI are also transferrable. Built a superhuman AI? Send it to a friend!

So far I haven't seen Google sending their AIs to a friend.

What do you mean? Basically all Neural-network models (from Google and others) are freely available. And to top that you can also get pre-trained weights for the models for free.

https://www.tensorflow.org/hub/

https://github.com/tensorflow/models

I mean the Alpha* family- AlphaGo, AlphaStar etc. I don't think they're sharing their analytics models either, or their DMT models, etc.

"All" neural network models is a stretch. Some researchers, including some that work in the industry, do releast their models. The majority don't.

With transfer learning, you can download some of the worlds most advanced pre-trained NLP models and adapt them to a specific data set.

https://www.analyticsvidhya.com/blog/2019/03/pretrained-mode...

They are putting ML inference on the Pixel phones.