Alternatives
Products that do what Micro-RLE ≤264-byte compression for UART/MCU logs, zero RAM growth does
I needed to stuff twice the telemetry through the same 115 kbaud line on a Cortex-M0+ that only had 8 kB flash left. Micro-RLE is the smallest drop-in I could come up with: 264 B of Thumb code, 36 B of state, no malloc, worst-case 14 cycles/byte and still lossless for every 8-bit pattern. On the usual sensor streams (ADC, IMU, GPS) it’s 33-70 % smaller than raw output and boots in < 600 µs, so you can fire-and-forget from main() before the PLL even locks. Repo is a single .c file and a 3-function API—replace the weak emit() hook with your UART / DMA / ring-buffer and you’re…
- 1MH
2021 · twitter.com
- 2
- 3AM
2018 · lambdaway.free.fr
- 4
- 5AA
2020 · github.com
- 6AM
2021 · github.com
- 7TC
2015 · github.com
- 8IS
2016 · github.com
- 9IB
Definitely one of those "20 minute adventure gone wrong" projects where all I wanted initially was a quick wireless rubber ducky for bitlocker keys and the like and then I kept adding stuff like AES-256..... Currently working on adding WebAuthn/FIDO support because the hardware is already there and scope creep is a lifestyle at this point. Would love feedback, especially on the security side. Repo and PCB files are fully open source.
Jul 2026 · github.com
- 10
This project is a little performance-optimization experiment focused on reducing the size of Go binary patches, which can be useful for quick incremental updates of live services. When a Go program grows by a few bytes through an incremental change, a bunch of related references and offsets throughout the compiled binary end up changing that makes general-purpose binary-diff encoders inefficient: `zstd --patch-from` produces a 530kb patch for a one-line change in a 30MB binary. bsdiff improves upon this (150KB patch) thanks to a delta compression algorithm that can handle relative offsets.…
9d ago · github.com
- 11OA
2016 · github.com
- 12
I made this after seeing someone posit the idea online yesterday over lunch then spent some time refining it. So far it's pretty impressive IMO! Right now I am running Qwen3-30B-A3B on my 24gb unified memory m4 MacBook Pro at 50 tok/sec and this should definitely not be working for such a large model on my middling hardware. Things are detailed in the README to get up and running and DESIGN.md has details on all the choices and such made along the way.
23d ago · github.com
- 13MA
Howdy HN, I've been working on micron for quite some time now, and I've finally gotten it to a state where I'm ready to share it with other people. I've really been pruning and testing it quite heavily for the past few weeks looking to flush out any bugs/inconsistencies. micron is a header-only C++23 core systems library that runs on Linux without libc, without libm, without the STL, and without any external dependencies at all. Fully freestanding. To my knowledge this is probably the only project of this kind, and the only libc implementation not in C. There _might_ be some Rust libc…
Jun 2026 · github.com
- 14JN
We’ve been experimenting with how far a tiny model can go when it’s good at calling external tools - and have just released Jan-nano, a 4 B model trained for MCP. Jan-nano: - tops DeepSeek-V3-671B on MCP tool-use (SimpleQA 80.7%) - handles live web search and multi-step deep research - runs fully on-device (≈4GB VRAM) Tech notes - Base: Qwen3-4B - Fine-tuning: DAPO - We're going to release the full technical report soon Links - Demo tweet: https://x.com/menloresearch/status/1934809407604576559 - Model + GGUF:…
2025 · twitter.com
- 15SL
I'd like to share a little toy project of mine, a really simple image codec that can do lossy to full lossless image compression with complete scalability at a byte level granularity - you can compress an image just once, even fully losslessly if needed, and then get any lossy version possible by simply stopping decompression at any offset in the compressed data. This "encode onde, serve many" approach is especially interesting for providing downscaled low quality image previews (LQIP) in as tight a storage budget as possible, and then allowing seamless, transparent refinement as deemed…
2024 · github.com
- 16UF
May 2026 · github.com
- 17R0
I built a tiny physics solver LLM that performs surprisingly well on easy-to-medium difficulty physics problems. Most LLMs today still struggle with physics QA (as PhyBench recently highlighted), so I wanted to see how far I could push a small model with careful data and minimal compute. Model: Qwen3-1.7B Supervised Finetuning: ~1500 curated examples spanning kinematics, EM, acoustics, and more RL Fine-tuning: GRPO, 1-shot RLVR style (single example, 70 steps) Total cost: ~$5 on H100 It started with a cold-start SFT (~3 epochs, loss to 0.3), then I ran RL with accuracy reward that climbed…
2025 · huggingface.co
- 18PR
MicroPython (lexer, compiler and VM) on the SNES: 3.58 MHz 65816, 56 KB Python heap, 16-bit int. The REPL runs right inside the post via EmulatorJS and also works on real hardware via flashcart. I did this as a benchmark for Claude Fable. When the export ban hit, switching to Opus got the project stuck for three weeks; Fable came back and found the real bug in ninety minutes. Along the way: 23 compiler bugs and 4 MicroPython bugs, each root-caused with a minimal reproducer and filed upstream. If you run it on real hardware, I want a picture!
Jul 2026 · fabian-kuebler.com
- 19RS
2016 · gammarf.io
- 20MA
I want to be very upfront: this IDE's code is 100% generated by LLMs supervised by me, I am not hiding this fact. This submission was written by a human. microide's focus is performance and privacy, I was very tired of having AI integrated on every tool (ironic, I know, having vibecoded this one), and the decline in software performance. After trying quite a few IDEs none were what I wanted so I started microide. microide also does not have any kind of telemetry nor networking capabilities by design, no accounts, no update checks, none. Since I only use CLI-based LLM tools, microide has a…
Jul 2026 · pablojimenezmateo.github.io
- 21CA
Thought I'd dive into this cool streaming/approximation algorithms problem I encountered a few months ago. TLDR: we can create our own custom floating point representation for encoding and decoding integers and use this to index into a tiny 2D histogram, upper-bounding approximation error based on the number of bits per integer we specify to keep. --- Broadly useful for aggregating statistics from massive data streams of user data. Also turns out this is incredibly similar to data structures used in production, like HDRHistogram.
Jan 2026 · alexkranias.com
- 22DF
Hi HN, We’re the team at MyDecisive.ai, and today we’re giving developers a peek at Octant — point-and-click control and visibility for your OpenTelemetry. You've likely felt the pain of the "observability tax," especially if you manage K8S clusters. The modern standard is to instrument everything with OpenTelemetry, but piping all those rich OTLP logs, metrics, and traces straight to a SaaS vendor (Datadog, Splunk, Honeycomb) gets expensive fast. You end up paying massive ingestion and storage costs for noisy, low-value data just so it's searchable when something breaks. With Octant you get…
Jun 2026
- 23OS
It uses claude code with GLM-6 model which is cheap yet powerful for most of the cases. for deployment Cloudflare Workers. It is a 2 weeks of hard work! Lemme know what you think!
Oct 2025 · github.com
- 24SM
To get benefits from sparsity, you usually need to have very sparse matrices, impose some structure on the sparsity pattern or have specialized hardware. None of it is the case if you want to rune pruned LLMs on consumer devices. I wanted to see how far can you push it on a GPU and ended up with this. Blog: https://www.grizzlytech.dev/blog/macko-spmv Paper: https://arxiv.org/abs/2511.13061 Code (example with torch): https://github.com/vlejd/macko_spmv
Nov 2025 · github.com
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