RyeCatcher

5 ms·

1.
Show HN: Hey, Reachy – near-real-time voice for the Reachy Mini desktop robot(runreachyrun.com)
2 points by RyeCatcher 4mo ago|0 comments
2.
Warp Decode vs. vLLM's Triton kernel: where each wins (crossover analysis)(ai.rundatarun.io)
2 points by RyeCatcher 6mo ago|0 comments
3.
by RyeCatcher 6mo ago
Hey HN, author here. Happy to answer questions. Why Rust? - Ownership model makes the CoW block table provably safe, the borrow checker enforces that you can't alias a block that's being written. That's not just style; it eli
4.
Show HN: Dendrite – O(1) KV cache forking for tree-structured LLM inference(github.com)
3 points by RyeCatcher 6mo ago|1 comments
5.
Fixing macOS window chaos: display-aware layout restore with Hammerspoon(ai.rundatarun.io)
2 points by RyeCatcher 7mo ago|0 comments
6.
by RyeCatcher 11mo ago
Author here. I've updated the article based on your feedback. Thank you. Key corrections: Ollama GPU usage - I was wrong. It IS using GPU (verified 96% utilization). My "CPU-optimized backend" claim was incorrect. FP16 vs BF1
7.
by RyeCatcher 11mo ago
Cool I’ll have a look. All reflections I made were first pass stuff.
8.
by RyeCatcher 11mo ago
Need to buy 2 and connect em. :-)
9.
by RyeCatcher 11mo ago
Totally agree. I’ve been training nanochat models all morning. Hit some speed bumps. I’ll share more later in another article. Buts it’s absolutely amazing. I fine tuned a Gemma3 model in a day yesterday.
10.
by RyeCatcher 11mo ago
I absolutely love it. I’ve been up for days playing with it. But there are some bleeding edge issues. I tried to write a balanced article. I would highly recommend for people that love to get their hands dirty. Blows away any consumer GPU.
11.
by RyeCatcher 11mo ago
Would love to hear from others using the spark for model training and development.
12.
Nvidia DGX Spark: When benchmark numbers meet production reality(publish.obsidian.md)
152 points by RyeCatcher 11mo ago|117 comments