Crazierl
Crazierl is an experimental/hobby operating system based around BEAM. I've linked the browser based demo; I don’t recommend using a phone; it does work, slowly, on the phones I tested, but it’s very awkward to use. You can share a link with a hashtag with your friends and click the consent checkbox, and it (should) link up into dist and I’ve also included a chat application you can start with chat:start(). (quit chat with /quit, or use the shell menu with ctrl-g to switch between shells etc). The browser demo relies on the v86 javascript x86 virtual machine. You can also run Crazierl on a real x86 system, but I’ve had mixed luck on modern systems, it uses some esoteric legacy VGA features and support for that isn’t getting better. Crazierl is fairly limited: 32-bit x86, BIOS boot, only two NIC drivers virtio-net and realtek 8168. But it's got enough to become part of an Erlang dist cluster. It also supports SMP, but it’s crashy with high core counts in qemu; there’s almost certainly several concurrency bugs in the kernel. There's also a lot of excess tcp debug spew (sorry). Source code is available (Apache) https://github.com/russor/crazierl/
Theguardian
JD Vance says aliens are 'demons' and details obsession with UFOs
1-Bit Bonsai, the First Commercially Viable 1-Bit LLMs
Show HN: 1-Bit Bonsai, the First Commercially Viable 1-Bit LLMs
Cerno
Show HN: Cerno – CAPTCHA that targets LLM reasoning, not human biology
Sycamore
Show HN: Sycamore – next gen Rust web UI library using fine-grained reactivity
Ray
I've been using this daily for 4 months and figured others might find it useful. This is my first open source project so would love any feedback. Ray connects to your bank via Plaid, stores everything in an encrypted local SQLite database, and lets you ask questions about your finances in natural language. No cloud, no account, your data is stored on your machine. Before anything reaches the LLM, all PII is stripped — your name, companies, transaction details are redacted and replaced with tokens, then rehydrated locally in the response. The AI never sees who you are.
Cabinet
Hi HN, for quite some time I've been thinking how LLMs are missing the knowledge base, where I can dump CSVs, PDFs, and most important, inline web app. running on Claude Code (bring your own agent) with agents with heartbeats and jobs https://runcabinet.com It runs locally and is installable via npm. GitHub (open source): https://github.com/hilash/cabinet This is still very early. I put the first version together quickly after seeing a post by Andrej Karpathy about LLM knowledge bases, which matched closely with what I’d been building. Some people have already started trying it and opening PRs, which has been encouraging (got 374 stars in 2 days :] ) If useful: Waitlist for a hosted version: https://runcabinet.com/waitlist Discord (small, but growing): https://discord.gg/rxd8BYnN Would really appreciate feedback: does this “KB + agents” model make sense? what would you expect from a system like this? where does this fall apart? Happy to answer anything. Hila
I Built Paul Graham's Intellectual Captcha Idea
PG has posted about improving social networks using something like an "intellectual CAPTCHA" many times [1][2][3][4] - "Make users pass a test on basic concepts like the distinction between necessary and sufficient conditions before they can tweet." I felt the same way. So I built one using a mix of simple math, logic, and Twitter/X Community Noted posts. Try sample questions here - https://mentwire.com/sample - without signing up. - Invites are temporarily open to HN users. - Onboarding test + one daily question before accessing feed, post or reply. - Posts authors are anonymous until upvoted or downvoted, forcing evaluation of content on merit. - Face ID (on-device only) to post/reply, pangram checks for AI text. Sourcing good questions turned out to be much harder than I thought. If you have suggestions to scale this, I would love to hear. Eventually, could be gated across disciplines/topics to get a competence × interest graph instead of the pure interest graph of today's social networks. [1] https://x.com/paulg/status/1235949761359904768 [2] https://x.com/paulg/status/1576517990182359040 [3] https://x.com/paulg/status/1514979883948126209 [4] https://x.com/paulg/status/1505842647319126016 Repost from https://news.ycombinator.com/item?id=47577829. This link contains a full quiz and linked directly to sample to try without signing up.
Per-user isolated environments for AI agents
Show HN: Per-user isolated environments for AI agents
Output.ai
Show HN: Output.ai - OSS framework we extracted from 500+ production AI agents
An interactive map of Tolkien's Middle-earth
An interactive map of Tolkien’s Middle-earth, with events from across the legendarium plotted as markers. I have been commuting a fair bit between the East and West coast, and thanks to American Airlines' free onboard WiFi, I was able to vibe-code a full interactive map of Middle-earth right from my economy seat at the back of the bus. It's rather amazing how much an LLM knows about Tolkien's work, and it was fun to delve into many of the nooks and crannies of Tolkien's lore. Some features: - Plot on the map the journey of the main characters in both The Hobbit and The Lord of the Rings. - Follow a list of events in the chronological Timeline - Zoom in on the high-def map and explore many of the off-the-main-plotline places - Use the 'measure distances' feature to see how far apart things are. I also had a lot of fun learning about tiling to allow for efficient zooming. If you are anything like me, this should provide a fun companion to reading the books or watching the movies (note that on this site, I followed the book narrative, and did not include Peter Jackson's many departures) If you get the chance to check it out, I would love more feedback, and if there is demand, I might do the same for Game of Thrones.
I built a local data lake for AI powered data engineering and analytics
I got tired of the overhead required to run even a simple data analysis - cloud setup, ETL pipelines, orchestration, cost monitoring - so I built a fully local data-stack/IDE where I can write SQL/Py, run it, see results, and iterate quickly and interactively. You get data lake like catalog, zero-ETL, lineage, versioning, and analytics running entirely on your machine. You can import from a database, webpage, CSV, etc. and query in natural language or do your own work in SQL/Pyspark. Connect to local models like Gemma or cloud LLMs like Claude for querying and analysis. You don’t have to setup local LLMs, it comes built in. This is completely free. No cloud account required. Downloading the software - https://getnile.ai/downloads Watch a demo - https://www.youtube.com/watch?v=C6qSFLylryk Check the code repo - https://github.com/NileData/local This is still early and I'd genuinely love your feedback on what's broken, what's missing, and if you find this useful for your data and analytics work.