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Products that do what Generate PCB Footprints from text using AI does
Hi HN! This is a little project to generate PCB footprints from text descriptions. It works by teaching an LLM a compressed DSL representation for footprints. I think this is generally a good technique if you're trying to get LLMs to work on spatial problems. Right now I'm focused on reproducing footprint shapes, but after that I'll benchmark the correctness of the footprints using % overlap on known package descriptions, as well as a kicad_mod export I built this because I realized I needed to use AI to help tscircuit catch up to the decades of electronic design tool progress that I'm not…
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Prompt to production-ready Hardware designs for manufacture
May 2026
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Hi folks, we just released the ability to export our library of schematic symbols and PCB footprints to Mentor PADS. This is a beta release so it would be great to get your feedback. To try it, search for a part on SnapEDA (http://www.snapeda.com), click download and then select "PADS" as the format. You can try it out on this part here directly if you prefer: http://www.snapeda.com/parts/PIC32MX250F128B-I/SS/Microchip/view-part/
2015
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To be specific, the content is generated by a GPT-2 based model. https://amzn.to/2TCc0v2 Let me know if you have any questions :-)
2020
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Hey HN! We've built an AI powered technical writer that allows you to automate creating comprehensive, MDX-formatted documentation with just a few clicks. How It Works: - Upload screenshots: Start by uploading screenshots of your product. - Describe features: Provide a brief description of the features you want documented. - Generate documentation: Our AI will analyze your inputs and automagically generate detailed documentation in MDX format. - Deploy instantly: With just one click, you can deploy your new documentation online. Continuous Integration: Automated updates: Integrate our npm…
2024 · app.paparazzidocs.com
- 13GB
This project began when I decided it would be easier to write an autorouter than route a 8000+ net backplane by hand. This is a KiCad plugin with a few different algorithms, the coolest of which is a 'Manhattan routing grid' autorouter that routes along orthogonal traces. The basic idea was to steal an algorithm from FPGA routing and apply it to PCBs. I'm using CuPy for speeding up the routing; CPU-bound is at least 10x slower than the GPU version. This is in a very pre-alpha state, but it does _technically_ work. It's not great by any measure but then again it is an autorouter. I have a…
Oct 2025 · github.com
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I built a tool to roast landing pages with AI agents. I was gathering feedback from watching landing page roast videos, and figured out I could prompt LLMs to analyse a screenshot and roast based on the same criteria. It's not 100% accurate yet, but it has been really insightful when I've tested it on my own websites. Let me know what you think!
2024 · roastmylandingpage.io
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Hey there HN! We're Vivek and Si-Yan from Cartograph (https://cartograph.app). We've built an AI-powered code documentation platform that automatically generates reference documentation and creates a visual interactive map of the codebase that serves as both high level architecture diagram and allows you to zoom in to specific implementations. How it works: We use static analysis to read a codebase and get its symbols and their dependencies, creating a complete map that includes function calls. We use LLMs (Gemini + Claude) to add metadata to this map, as well as augment it in…
2024 · cartograph.app
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Hey HN, this is deepan from trulytyped (https://trulytyped.com). I am building a document writing app which makes it extremely easy to figure out how a document was created. Now that any text can be AI generated, how do you tell if something was actually generated or composed. It is impossible to detect AI after a piece of text has been generated. No amount of watermarking, linguistic checks or vibe checks work consistently. The AI detectors that schools and journals use are easy to bypass. Why do we need to solve this problem - First of all, this is not an anti-AI stance. I have…
May 2026 · trulytyped.com
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Hey HN, I built Blooming, a visual AI workspace where you drag-and-drop “nodes” (text, image, video) onto a whiteboard and chain AI text, image and video models together. It's kinda like n8n but for AI art: • Node-based canvas • Multi-model switching (test different models side by side and iterate multiple versions) • Pipe text or image output to other nodes to refine prompts, turn them into videos or explain images Demo link: https://youtu.be/TdFzhxeRFNg I’d love your feedback on UI clarity, performance, and which models to integrate next. What’s confusing or missing for AI…
2025 · blooming1000.com
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As a former CIO who managed teams working with millions of lines of legacy code (Visual Basic, Sybase, Oracle Forms, and worse), I feel the pain of maintaining and onboarding developers to legacy systems. Believing that LLM-enabled tools can play a role in solving this, I've built a tool that automatically generates documentation for legacy codebases using the Model Context Protocol (MCP) & Claude Sonnet. At first glance, I think this approach has merit. Some samples are in the README. I welcome your thoughts. The Problem: - Legacy codebases are notoriously difficult to understand and…
2025 · github.com
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2024 · cadwithai.com
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I wanted a very simple way to dump prompts, links, and todo lists into my claude code and codex agents. And to work outside of the context window. This works particularly well for sharing "Projects" between Claude/ChatGPT etc. It's open source here; https://github.com/Vochsel/dump.page Anything you dump on the board becomes an llms.txt - spatially sorted implicitly and explicity sorted via connection edges. Would love HN's thoughts!
Mar 2026 · dump.page
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Let's try a small experiment with LLMs that have a large context length: feed an entire book into the context window and ask it to generate a list of characters, their relationships, and physical descriptions—data that can later be used for image generation. In this repository, you can find two tools: a script that extracts data from book text using an LLM (Gemini or OpenRouter API) and an HTML/JS (D3) visualization of the character graph. An external text-to-image model can be used to generate character illustrations (a Google Colab example is provided). Explore the visualizations,…
2025 · github.com
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Hey HN, I’m excited to share a tool I’ve been working on: AI Describe Image. It’s an AI-powered tool that automatically generates detailed descriptions for images. If you’re a content creator, marketer, or web developer, this tool can help streamline the process of creating image descriptions for blogs, websites, or social media. What It Does: Automatically generates descriptions for any image you upload. Designed to improve accessibility by providing descriptive text for images, ensuring that screen readers can convey the visual content to visually impaired users. Optimized for SEO: The…
2024 · alttextgenerator.co
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Hey HN, I built ProductMap AI, a tool that automatically identifies features implemented in source code and organizes them in a visual hierarchy. The goal is to help developers quickly understand poorly documented codebases. Link: https://product-map.ai/ I’d love feedback from the HN community! Let me know what you think. Would this be useful for you?
2025 · product-map.ai
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2016 · blog.snapeda.com
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