larme

thanks for the pointer, I will check them out

GPU programming?

What I linked is the official repo. My customization is private because I replace the original fonts with a commercial font (which I own a license) so I feel it's better not to make the repo public.

Also I think there's a youtuber who shoot some videos about using microslate.

I list some cons in a sibling comment. You may want to check if you plan to buy one

I don't have video on my hand but a photo is here: https://files.catbox.moe/z8suof.jpg

There are some cons:

- some users report text gets blurred out if used under direct sunlight for a long time. I don't use it outside so I'm not affected

- sometimes the BLE connection is sketchy. I'm not sure if it's hardware or software problem

- the editor features are very barebone so you may want to customize your own version

- beware there are unflashable edition of this device

I have an X4 and use it as a writer deck with microslate firmware[0]

I heavily customized the source code with llm so I can use emacs style keybindings and search.

[0]: https://github.com/Josh-writes/microslate-firmware

because modern browsers are monsters that a lot of us want to avoid

For me creating the exact sound is not very interesting from sound designing perspective. You can always sample the real instrument.

Like physical modeling synthesis, the interesting part is to compress the sound to some parameters that you can tweak and generate new sounds

Another approach is VAE, which also you give your some latent embedding, you can tweak the embedding to generate new sound. However the meaning of this embedding is not explicit.

People who are interested in this application should check synplant[0]. It has a ML technology called "Genopatch" which gives you 2 functionality:

1. you can try to describe a sound with some tags and it will try to generate a sound to capture the feeling of these tags

2.you can feed it with a sound sample and it will try to re-synthesize the sound with its synth engine. Though the end result will usually be just a "re-imagined" version of your input sample.

My guess is the underlying model is not a "deep" model. The main benefit is that the end result is not a wave file, but a list of generated parameters that can be synthesized by the synthplant engine. And now it comes the interesting part: you can tweak these parameters to finetune the generated sound. These parameters have actual meanings (FM ratio, reverb etc.)

[0]: https://soniccharge.com/synplant

Before LLM there has already been Fields medalist[0] who creates professional software[1].

[0]: https://en.wikipedia.org/wiki/Martin_Hairer

[1]: https://www.hairersoft.com/

This description sounds like a cult.

> It's a big democracy red flag when a majority wants to take a lot from a tiny minority

It’s not “taking”. The rich give out some money so the society has a higher probability to stay peaceful. or a violent revolution may happen.

This is really a win win situation

Go is not high performance enough. Like what others said, you implement the high performance part in C++ and use python to glue them.

Try pair reading it with a good thinking LLM like GPT 5.5 or Claude Opus. I found it help me a lot.

I have started learning SBCL internal from the beginning of this year with the help of GPT, and I really want to contribute to SBCL compiler someday in future.

Some of these models are open weight. You can try hosting them and do the price calculation yourself.

They also publish papers talking about how to save kv cache and computation powers. Because currently they don't have the most powerful nvidia cards, training and inference efficiency is very import for them.

That's amazing. I wonder how accurate is the synth engine?

It’s true that American companies have benefited from sending jobs overseas. Instead of trying to stop them, perhaps we could explore ways to share this money more fairly across the country.

Have you tried pocket 386? https://arstechnica.com/gadgets/2024/08/a-few-weeks-with-the...

Thanks for the answers!

I'm very interesting in this field (realtime audio + GPU programming). How do you deal with the latency? Do you send or multiple single vectors/buffers to GPU?

Also I think because samples in one channel need to be processed sequentially, does that mean mono audio processing won't benefit a lot from GPU programming. Or maybe you are dealing with spectral signal processing?

Wow that's really thorough

> What features has Google killed, do you think? The problem is more like google can implement whatever feature they want and force it into web standard

> How often has this been a problem, do you think? very often

> What other browsers have gone ahead, with Google holding out? Google is holding out in a sense that no other people can implement a feature-complete browser. Google is killing the "open standard" web by make the standard impossible.

I use rpi zero 2 as a coding server (paired with my iphone and a splitted keyboard) when I have slow or no internet. It's quite usable if you just mosh/ssh into it and use emacs/vim to code.

The same logic applies to capital punishment

It indicates how much does google search suck nowadays.

Ye, SE Lain has lots of tech reference. This website lists many of them: https://www.cjas.org/~leng/lain.htm

entrepreneurs suck anyway.

I didn't use google's image search for a long time so I don't know that. But I think kagi pays to use google's data as one of their source. So it's possible the image search results are the same. However the different order/ranking is what separated kagi and google.

Try jmp.chat, you can use an XMPP client to receive phone calls and sms.

I use the following services:

- phone number: jmp.chat and a textnow number as backup

- email: fastmail

- search: kagi

- map: apple map