Left: Telegram digest (optional); Right: detailed digest on HTML Like probably everyone here, my to-read list only grows. Skimming arXiv listings or my feeds takes 30-60 minutes a day, 95% of it is irrelevant to what I actually work on, and newsletters don't really help: they surface what's popular, not what's relevant to my research. So I built Research Radar, a daily cron job that: Fetches every new paper in your arXiv categories (RSS + API, deduped) Scores every abstract 1-10 against a markdown file describing your research interests (cheap model, batched) Deep-reads the top scorers: downloads the PDF, extracts full text, and a strong model writes a summary, key insights, limitations, and how it relates to your own work Delivers a morning HTML digest + optional Telegram ping with the must-reads Design decisions: Nothing domain-specific in the code. Your interests live in one markdown file. Edit it and the same pipeline works for ML, physics, bio, econ, whatever Only the two scoring passes touch a model. Fetching, dedup, PDF extraction, and rendering are deterministic Python Model-agnostic backend layer: Claude Code / Codex CLIs run it on the subscription you already pay for (no API key), or any OpenAI-compatible endpoint, including fully local via Ollama / vLLM. Backends mix per pass: cheap model for skimming, strong one for the 5-10 deep reads Approximate costs, benchmarked in the repo (tokens, cost, latency, quality grades per model). Rough sizing: a 10-abstract scoring batch is ~18k input tokens with a small JSON out; a deep read sends the whole paper, 40-70k input tokens. I've been using it daily for about a month and it's been genuinely useful in my field. The repo is a generalization of my personal setup to any domain, and I haven't deeply tested fields other than mine, so feedback and GitHub issues are very welcome. The model has to say "not relevant, 3/10" a lot without drifting toward score inflation, and the whole scoring is just prompt + markdown context. So I'm curious how others would approach calibrating an LLM judge like this GitHub: https://github.com/ramazan793/research-radar submitted by /u/usedtobreath [link] [Kommentare]
A practitioner-led synthesis by Manazir Ali. Formalizes the bet that a swappable weak model wrapped in a strong harness (deterministic retrieval, curated tools, verification loops) can deliver frontier behavior, decomposes it into five testable components, and grades each against roughly 30 published sources. The harness closes knowledge, format reliability, and narrow verifiable tasks, and is worth roughly one model generation from a naive baseline. It does not close multi-turn coherence, long-horizon autonomy, or novel hard reasoning, where same-harness model spreads run 1.5 to 4x on agentic coding and 50 to 100x on METR time horizons. The engineering answer is tiered routing with frontier escalation.
← ~/reviewsSix months daily driving Linux Jun 12, 2026 This year, I got tired of Windows. It started to feel like malware. People seemed to be quite excited about batteries-included Linux distros: As another anecdote in favor of Universal Blue’s approach. My mother (who can’t use a computer but to check email or regular websites) has been swapped to Aurora and has nothing but positive feedback. Been 90 days with zero issues.1 Bluefin, Aurora, and Bazzite are taking over my home. I’ve been using desktop linux since before ubuntu, and I have never had so much confidence in my linux rigs. They are dependable, which is refreshing after boot-breaking updates have ruined my setups before.2 So I took the plunge and went all in on Bluefin Linux in February 2026. My installation was mostly smooth. First boot after install was hanging; went into BIOS and toggled off Windows UEFI mode and that seemed to do the trick. Then Bluetooth wasn’t working. After a quick Gemini chat, it was fixed; just had to turn off the computer and unplug it for a bit. Apparently Windows hibernates the Bluetooth module. The GPU (NVIDIA GeForce RTX 4070 Ti SUPER) worked perfectly out of the box. There were some early user experience snags. The default sleep settings are pretty aggressive; when it powers off for battery saving purposes, it basically turns off entirely. Had to press the power button to turn it back on. That was a quick settings toggle to fix. Bluetooth used to be a problem. Had to manually click to reconnect my AirPods every time, and my wireless keyboard + mouse had to be toggled on + off every time as well. Dusted off a wired mouse and keyboard. But after a while, the Bluetooth just … started working perfectly fine. Not sure what happened there. Had no issues with launching Steam games, except specifically Total War: Three Kingdoms. Fixed the launch errors after a bit of config and chatting with LLMs. Still-persisting bug: Uploading files to browsers, when dragging-and-dropping, sometimes runs into an error where it complains that the file is empty. But selecting an upload works. Noticed this on both copyparty and Google Drive. Am I happy? Yes. Would I switch back to Windows? Never. My computer feels lightweight, in my control, and has a bunch of little quality-of-life features (fast window-switching, screenshots get copied to clipboard automatically). FootnotesSection titled “Footnotes” https://news.ycombinator.com/item?id=46576284 ↩ https://news.ycombinator.com/item?id=46577646 ↩ more posts
How I used arenas to make the Gleam formatter faster and less memory hungry
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