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Quake 1 port for Apple Watch

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Re: Quake 1 port for Apple Watch

#82
Nice work!

How about Quake on Amazon Echo + Alexa? Build it like a Text Adventure but use NLP + Computer Vision to describe the scene and you shoot and move by describing what you want. Great for people with poor vision or has a nostalgia for the 80s.

Re: Quake 1 port for Apple Watch

#83
post #48

This is so cute and cool! While I don't know, whether I want to play long Quake sessions on my watch, it shows that the Apple watch is a quite powerful compute device. Actually, it should be more powerful than most workstations of the 90ies, as it has a dual-core 64bit Processor. It also shows, how much the watch and some other Apple devices are held back by the software restrictions. Basically any software released…

> it shows that the Apple watch is a quite powerful compute device.

I would have honestly expected the watch to be able to play much more than Quake.

Re: Quake 1 port for Apple Watch

#84
post #48

This is so cute and cool! While I don't know, whether I want to play long Quake sessions on my watch, it shows that the Apple watch is a quite powerful compute device. Actually, it should be more powerful than most workstations of the 90ies, as it has a dual-core 64bit Processor. It also shows, how much the watch and some other Apple devices are held back by the software restrictions. Basically any software released…

TBH I would say in the case of the watch, it's held back much more by energy budgets than software; the software is just enforcing that. It's cute that you can run Quake on it, but for how long before it killed the battery? 20 mins? You can see Apple pushing the bounds of what it can get away with and still maintain acceptable battery life from generation to generation.

Yeah you can’t directly use Metal or MetalKit on the watch, so you can’t do completely custom rendering of anything in the GPU (which is why this port has to use software rendering), but even if you could would probably just be blowing through the battery in under an hour.

SceneKit is available. Not sure what the battery life is like when it’s used for anything other than displaying a simple 3D model briefly (e.g. like the fitness medals).

Re: Quake 1 port for Apple Watch

#85
post #48

This is so cute and cool! While I don't know, whether I want to play long Quake sessions on my watch, it shows that the Apple watch is a quite powerful compute device. Actually, it should be more powerful than most workstations of the 90ies, as it has a dual-core 64bit Processor. It also shows, how much the watch and some other Apple devices are held back by the software restrictions. Basically any software released…

Who is stopping you from doing what exactly? What would be true if you were not stopped? Who is not free to experiment and distribute? What does the huge field consist of?

Apple only allows running software on Apple devices if Apple has signed it, and the SDK for watchOS has some artificial limitations.

Re: Quake 1 port for Apple Watch

#86

Earlier quoted context omitted.

Indeed. Currently playing Prodeus which is made by a couple of people using unity. Runs with about ~100 FPS whereas Doom Eternal hits about twice as that while looking much, much better. In fact, there's a recent game called HOAT or something. Built by a single guy using the Quake engine. Had to return it because it was running with 30fps on my machine.

It's not using the Quake engine, or it wouldn't be running at 30 fps on current hardware. It's probably Unity or something more modern and bloated.

If the parent comment meant HROT, it’s using a custom engine written in Pascal.

Re: Quake 1 port for Apple Watch

#87
post #14

Earlier quoted context omitted.

I have some experience with ML and I have no idea what you're talking about. It kinda sounds like neural architecture search and sparse models created using weight pruning. Lots of people are working on both of those things, but IMO the latter (if that's what you mean by "Can you add weights non uniformly?") is a dead end for most use cases where you have some sort of accelerator or deep learning instructions availab…

I’m unfortunately the sickest I’ve been in years, so this will have to wait. Maybe it’s part of why my comment sounded strange. There is an idea here, and it’s a mistake to dismiss it out of hand. Adding weights non uniformly during training (not after) is the key to smaller models that outperform present day GPT3. A sketch of the algorithm is to start with a 2x2 block of weights, sum the gradients across 10 training…

Sounds kinda like progressive growing except you're not doubling the resolution uniformly. See ProGAN and its successors. You'd still need to add a large block of weights at a time for performance reasons.

Edit: Ah I checked your profile and you already know all this. You probably should have mentioned that lol

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