I'm trying to make a neural audio codec using a variety of misguided methods. One I am using ESNs wrong spreading leak rates in a logarithmic fashion acting like a digital cochlea. The other is trying to do the same with a complex mass-spring-damper system to simulate the various hairs of the cochlea as well. Both approaches make super interesting visuals and appear to cluster reasonably well, but I am still learning about RVQ and audio loss (involves GANs and spectral loss). I kinda wanna beat SNAC if I can.
Readit Newsrobviren commented on Ask HN: What Are You Working On? (December 2025) · Posted by u/david927
robviren commented on Show HN: I was reintroduced to computers: Raspberry Pi airoboticist.blog/2025/12... · Posted by u/observer2022
Love to see the Pi getting some rather creative use! The most use I got out of one was as a health check endpoint for power in my garage which was holding frozen milk for my newborn, but the circuit kept tripping. Had another server email me if it couldn't reach the Pi for some reason. Just used some real simple Go code. It was not production but it worked. Not everything needs to change the world, maybe just make your day easier.
I just liked programming when it contained a comprehensible amount of abstraction. Stacks have become so tall it is not even feasible for a single human to comprehend what is occurring. I also liked when standards had less surface area. Working in healthcare it has become obvious standards only ever get added, never removed. Complexity is absurd now. I'm not championing that we all become experts in bare metal assembly, but I feel for OP and a desire to at least fundamentally understand what is happening on some level.
robviren commented on CachyOS: Fast and Customizable Linux Distribution cachyos.org/... · Posted by u/doener
I have been unable to get anything other than Cachy to run Baldur's Gate 3 as well as Windows on my Lenovo Legion 2021. Best I have found for performance and so far stable on my relative new tower.
robviren commented on A worker fell into a nuclear reactor pool nrc.gov/reading-rm/doc-co... · Posted by u/nvahalik
Can you recommend a book or two in order to learn about that culture? IMO we could use more of it in AI.
I found strong parallels between tech safety and nuclear safety.
https://www.nrc.gov/docs/ML0534/ML053410342.pdf
NRC is a good place to start. They have been at trying to prevent tech from hurting people for awhile.
robviren commented on A worker fell into a nuclear reactor pool nrc.gov/reading-rm/doc-co... · Posted by u/nvahalik
I've lived through three major nuclear incidents, and what they had in common, regardless of the political systems of the US, The Soviet Union or Japan, was not the transparency, it was the lying. It started immediately after each incident.
I'm essentially pro-nuclear, I just don't trust people who run it.
Totally valid perspective. I only became part of the industry after Fukushima. I only knew an industry by its disasters. I will say, having gone through the training programs we studied the nuclear incidents and spent a year in training before going to the plants. I just don't see parallel experiences looking back like that. The people in nuclear (at least from what I saw) want the industry to be safe and successful.
robviren commented on A worker fell into a nuclear reactor pool nrc.gov/reading-rm/doc-co... · Posted by u/nvahalik
I greatly appreciate the nuclear industry. Nuclear field engineering was my first "real" job out of college and they really committ to safety. Transparency in this industry is inspiring because everyone involved knows that one screw up and that's the end of the US nuclear industry. Good luck getting oil and gas to be accountable and as transparent about incidents. I carry the culture into the rest of my work and appreciate being involved. Wish events like this didn't happen but it is not of significant danger and I find it great that they communicate even "smaller" issues.
robviren commented on Neural audio codecs: how to get audio into LLMs kyutai.org/next/codec-exp... · Posted by u/karimf
This has got to be one of the most visually pleasing explanations I have seen of these concepts. Congrats!
I attempted some similar VQ-VAE work instead trying to tokenize rendered text. I was curious if I could make a visual llm working on 10 pt rendered font, but I also tried using PDF sources. The basic idea was to do what more advanced diffusion image models can do where they generate images of text. Make a specific image text diffusion model to do completions. Further I wondered if I could embed things like document type and language so you could have a latent representation of text more abstracted than current dictionary tokenizers. Learned a lot and thought it was all beautifully displayed in this post.
I have been playing with the idea of an LLM native programming language focusing on token efficiency, comprehension, and attention. It is interesting to see what the various large models come up with. A common theme actually reminds me quite of bit of assembly. The verb prefixing, limited statements per line, small concept surface area all appeared in multiple conversations across several larger models. The big difference being assembly lacks semantic meaning leaving some benefit on the table. I still cannot believe what some did with the tech, RCT is such a retro favorite.
robviren commented on AGI is an engineering problem, not a model training problem vincirufus.com/posts/agi-... · Posted by u/vincirufus
I have been thinking this as well. I desperately wish to develop a method that gives the models latent thinking that actually has temporal significance. The models now are so linear and have to scale on just one pass. A recurring model where the dynamics occur over multiple passes should hold much more complexity. Have worked on a few concepts in that area that are panning out.