grohan

8 ms·

1.
by grohan 7d ago
"load-bearing" - lol, nice easter egg. no one likes the AI-isms in writing!
2.
by grohan 8d ago
Pretty good point - I would actually argue that the imperative nature of prompting takes some of the blame here too. Your initial goal gets "steered" by the agent system and follow-up messages take precedence.
3.
Killing Coding Agent Slop with Adversarial Self-Play(usetelos.ai)
3 points by grohan 2mo ago|0 comments
4.
Ctoc: Cloc, but for Claude Token Counts(grohan.co)
1 points by grohan 7mo ago|1 comments
5.
by grohan 7mo ago
Here's a reverse engineer of the Claude token counter API as well as the model's vocabulary. Fast, offline, 96% accurate.
6.
by grohan 10mo ago
Bellard has trained various models, so it may not be the specific 169M parameter LLM, but his Transformer-based `nncp` is indeed #1 on the "Large Text Compression Benchmark" [1], which correctly accounts for both the total size of
7.
Compressed filesystems à la language models(grohan.co)
67 points by grohan 10mo ago|14 comments
8.
by grohan 2y ago
They appear to have Python bindings which seems reasonable from an API / usability perspective? https://github.com/deepseek-ai/smallpond In terms of fast FUSE - also my first question, appears to be`io_uring` + FU
9.
Technical Debt Is Entropy in Software(grohan.co)
2 points by grohan 2y ago|0 comments
10.
by grohan 3y ago
Impressive numbers. Does anyone have any read or anecdotes on how much a small/mid/large company loses from low quality of software/bad practices (or conversely profits from the opposite)? Seems like a challenging metric to m
11.
Factorials and Fun with Vim(grohan.co)
2 points by grohan 3y ago|0 comments