Emulators and AI

[Lainon]

This stuff is still firmly in the lab. As far as your want of some kind of cabinet that fires up, figures out how to play games and then maybe even does pretty good at them, we are far, far, far off. I'm talking decades at least.

It's not decades off when it's being done on current hardware using ML or DL techniques and a bit of python. You really just need a scripting language, a way to extract frames from a video (ffmpeg, etc), a way to tag frames for data, then using an object detection model like yolo or others out there to create a dataset. Then it's a matter of using the training dataset.

AI has been big in the news lately, but it's good only at certain narrow things. It would take more of a generalized intelligence to be able to recognize the content in real time from the screen, figure out what it's looking at and send back game inputs quick enough to matter.

This misrepresentation of the term "AI" only further confuses people in the conversation and elsewhere. LLMs are general purpose sure, however ML/DL models are usually quite specialized at running specific tasks. What's shown the news today is AI in the broad sense sure, but they're just LLMs, most of which can run locally on consumer hardware (a la llama 4).

An example, OpenAI's Five is an algorithm (trained using ML/DL methods) that plays Dota 2 at a competitive level and came out in 2017.

I've built a few detection systems using openly available object detection models and it's not entirely complicated or definitely not decades away, it's rather who want's to spent the time to make something described in the thread.

 

[OpenVMS]

It's not decades off when it's being done on current hardware using ML or DL techniques and a bit of python. You really just need a scripting language, a way to extract frames from a video (ffmpeg, etc), a way to tag frames for data, then using an object detection model like yolo or others out there to create a dataset. Then it's a matter of using the training dataset.


This misrepresentation of the term "AI" only further confuses people in the conversation and elsewhere. LLMs are general purpose sure, however ML/DL models are usually quite specialized at running specific tasks. What's shown the news today is AI in the broad sense sure, but they're just LLMs, most of which can run locally on consumer hardware (a la llama 4).

An example, OpenAI's Five is an algorithm (trained using ML/DL methods) that plays Dota 2 at a competitive level and came out in 2017.

I've built a few detection systems using openly available object detection models and it's not entirely complicated or definitely not decades away, it's rather who want's to spent the time to make something described in the thread.

I think the difficulty is really upped because he doesn't just have a game or two that he wants it supported on -- he wants to toss a whole ROM collection at it and watch it go. Sooner or later someone'll do it, probably just not today.