Show HN: Zenode – an AI-powered electronic component search engine https://ift.tt/mwRQDeY

Show HN: Zenode – an AI-powered electronic component search engine TL;DR - My cofounder Collin and I built an AI version of Digi-Key to help PCB designers find and use parts, except with a way bigger catalog, modern refinement tools, and an AI that can actually read the damn datasheets for you. *The problem* Modern circuit board design is filled with absurdly tedious tasks, where one small mistake can brick a project and cost thousands. The worst (in our opinion) is reading datasheets, which eats up to 25% of the first part of any project: 1. First, you slog through catalogs to find viable parts, using search tools that are still stuck in the dark ages. There are ~80M unique components in today’s supply chain, yet the tools we have to look through them are just digitized versions of the same paper catalogs our grandparents got in the mail. 2. During the design, you spend a ton of time flipping between different 10-100-page PDFs for every component in every subcircuit, hoping like hell you don’t miss some tiny spec in a footnote somewhere that kills your design. 3. And god help you when the requirements inevitably change and now you have to figure out what subsystems are affected! *What we built* Zenode is an AI-powered electronics search engine that actually helps engineers find and understand components. Our core features: 1. Largest and Deepest Part Catalog → We have merged dozens of existing part catalogs and documents from major distributors and manufacturers 2. Discovery Search → natural language queries to quickly find categories, set filters, and rank results 3. Modern Parametric Filters → rebuilt from scratch to move off the string values pervasive in industry and build numeric ranges that actually work. 4. Interactive Documents → AI constrained to a single part’s datasheet/manuals. Ask a question, get the answer with a highlighted source for quick reference. 5. Deep Dive → search across dozens of parts simultaneously (“what’s the lowest-power accelerometer available?”) instead of slogging one by one. *What we learned* 1. By far the hardest part of the last 2 years has been wrangling 3 TB of messy, inconsistent data into something usable. We had to teach the AI how to handle hand-drawn figures, normalize different unit variables and names that mean the same thing, and navigate conflicting information present between different datasheet versions of the same part. It’s been a nightmare 2. We originally built custom PDF parsers and AI extractors, which were best in class for ~3 months until generalized AI passed them. So we stopped reinventing wheels and doubled down on data quality instead. 3. The killer feature wasn’t the AI searching a single part, but what we heard repeatedly from users is that they want the AI to read across multiple parts, hence why we’ve launched deep dive! *Where it’s strong* - Speed: rips through a 1,000-page microcontroller datasheet in seconds. - Breadth: 40M+ part sources unified into one catalog, and more than just datasheets, application notes, errata, etc. - Comparisons: Deep Dive lets you ask across multiple parts, not just one at a time. *Where it’s not* - Pricing/availability: currently outdated (for now we expect folks to check existing aggregators like Octopart). - Accuracy: good enough to match my mediocre skills; not yet at Collin's level, but we're starting tuning and this will improve rapidly! *Try it* It’s live today (zenode.ai). Sign up for a free account and If you put “Hacker News” in during signup in the “where did you hear about us” field, we’ll give you 1,000 bonus credits (once we finish building that, so sometime this week ). *Feedback we’d love* 1. Should Deep Dive results auto-become filters you can refine further? 2. Do you want the ability to mark preferred parts / exclude others? 3. Is “Deep Dive on a BOM” (alt discovery + manufacturability checks on a list of known components from different categories) the killer feature? https://zenode.ai/ September 22, 2025 at 08:27PM

Walk & Roll to School Week Starts Oct. 6: Help Your Class Win the Golden Sneaker Contest

Walk & Roll to School Week Starts Oct. 6: Help Your Class Win the Golden Sneaker Contest
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Students and caregivers head to school together during Walk & Roll to School Week 2024. Time to lace up your shoes and join us for our annual Walk & Roll to School Week happening Oct. 6 to 10, 2025. Every year, thousands of students across the country walk, bike, scoot and roll to school as a fun and sustainable way of getting around. There are many ways for students and their families to participate. Do one or do them all! Walk, roll, bike and scoot to school every day – it’s that easy! Keep an eye out and join any special events your school might be hosting to celebrate Walk & Roll to School...

Published September 22, 2025 at 05:30AM
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Show HN: Python Audio Transcription: Convert Speech to Text Locally https://ift.tt/HpKtjI4

Show HN: Python Audio Transcription: Convert Speech to Text Locally https://ift.tt/iGK4HMS September 22, 2025 at 11:48PM

Show HN: I wrote an OS in 1000 lines of Zig https://ift.tt/PuLrQSw

Show HN: I wrote an OS in 1000 lines of Zig https://ift.tt/jqQWH1r September 18, 2025 at 08:35PM

Show HN: I made Android boot on Apple Silicon https://ift.tt/D7rOg2d

Show HN: I made Android boot on Apple Silicon https://twitter.com/mishushakov/status/1969797255353053264 September 21, 2025 at 11:18PM

Show HN: The Atlas – I Built a 3D Universe Simulation with Python and Three.js https://ift.tt/LgJs9n6

Show HN: The Atlas – I Built a 3D Universe Simulation with Python and Three.js Hi HN! I’ve spent the summer of the past 2 years building The Atlas, a procedural universe simulator that generates 1 sextillion galaxies (10²¹) from a single mathematical seed. Think No Man’s Sky meets theoretical physics, but running entirely in your browser. Everything is purely deterministic, the universe is calculated from SHA-256 hashed seeds using the golden ratio as primordial constant. There’s no database, no pre-saved data, just pure math. Time itself is treated as a coordinate, so the universe exists as a 4D structure where any moment can be computed on demand. Shut it down for weeks, restart, and planets have still been orbiting. Open the same world on multiple devices and you’ll see identical cloud formations, lava flows, even particle effects—always perfectly synchronized (if your clocks are synced). The simulation applies real physics, Kepler’s laws, tidal locking, Roche limits, hydrostatic relaxation for moons, and orbital temperature variations. Scale is mind-boggling, 300 tredecillion potential planets, far beyond anything that could ever be explored. The backend runs on Python/Flask with Hypercorn, the frontend on React + Three.js, connected via a custom MIT-licensed “vite-fusion” plugin we made. Everything is generated in real time, no storage needed. The Atlas includes 26+ planet types, fictional elements, moons evolving over geological timescales, and rare life forms that display Arecibo-style messages when analyzed. There’s resource mining and spaceship progression as gamification features. At its core, it’s a playable implementation of Einstein’s block universe theory, all moments exist simultaneously in the mathematical structure, you’re just moving through different temporal slices. You can try the live demo or run your own universe locally. When installed, you can choose between Core Continuum (a shared seed universe evolving since 1986, my birth year) or Design the Multiverse (your own unique cosmos with a fresh seed). I’d love feedback on the procedural generation algorithms and ideas for expanding the physics simulation! - GitHub: https://ift.tt/MLeDBnE - Docker: bansheetech/atlas:latest - Demo: https://the-atlas.koyeb.app - Alt Demo: https://ift.tt/49nR6rj Thanks for reading this far! <3 https://github.com/SurceBeats/Atlas September 21, 2025 at 09:26PM

Show HN: Parsing Crusader Kings III data files to generate mods https://ift.tt/tRwk35X

Show HN: Parsing Crusader Kings III data files to generate mods https://ift.tt/VhAd1nP September 22, 2025 at 01:05AM