A lot of people in this thread complaining about DPIs and similar specs. Am I really the weird one for still thinking a 24" 1080p (≈92 DPI) display is absolutely fine for 99% of tasks?
The people praising 4K now will be calling it shit in just a few years time. Maybe I am coping for not having grown up with HD TV.
I really believe that if Netflix launched its interactive media with a miniseries of Goosebumps: Choose Your Own Adventure adaptations (instead of... whatever Bandersnatch was...) the format could have been a huge success.
I still want to Escape from the Carnival of Horrors(TM).
Wouldn't that effectivly be a Visual Novel (DDLC) or Graphic Novel (Maniac Mansion)? If you have good IP and Story, aren't games in this style pretty straightforward to create?
Isn't this effectively how the interactive materials behave, or am I misunderstanding? It was my understanding that they all were analogous to DVD-style interactive extras where you essentially choose left or right at points in the story.
First off, well done, this looks exciting. I haven't had a chance to interact with the library yet — should torchao be seen as a dev-friendly quantization interface? I.e., if my team was working on new quantization techniques, does the API provide easy tooling for implementing and benchmarking new quantization algorithms? Or is this closer to a "toolbox of finished (generally) finished products"?
It's both! For this blog we decided to discuss our best end user facing numbers to keep things simple. We briefly hint at our contributor guide here https://github.com/pytorch/ao/issues/391 which does a tour of the APIs we provide developers implementing new algorithms
But we have had quantization algorithm developers such as HQQ or Autoround merge their code in to get composability and serialization for free. We view quantization algorithms as the top layer and going down you have quantized tensors, quant primitives like dequant/quant and finally basic dtypes like uint1-7 and float3-8. Personally why I spent so much time on AO was I was hoping we could make it easier for people to express their quantization algorithms in easy to read PyTorch code and if they must use custom kernels we also have some tutorials for how to integrate custom cuda and triton ops.
Most of those discussions have been happening on #torchao on discord.gg/gpumode so if you need to chat back and forth feel free to reach out to the team there otherwise Github also works.
I have had a lot of luck using the Plasma desktop environment (on Arch). Super customizable, to the level of hyper specificity you've described (down to the pixel, sometimes), and is mostly intuitive how to make these customizations.
My local machine basically looks/runs like Windows 10, but with the KDE Plasma logo in the corner instead of Microsoft Windows.
I'm 2/3rd of the way through Love in Time of Cholera and it's only chapter four (@200+pages, so far)... otherwise, an absolutely beautiful story of unrequited/parasocial love.
By far the worst chapter structure (and "book") is The Sound and The Fury. It seems like an exercise in-the-second-person, gone wrong. Sensorial overload... and isn't the point of a good story <TO MAKE SENSE>?
