The best Hacker News stories from Show from the past day

from

All Show

from the past*

day week month

with these search terms:

Create follow Go back

Latest posts:

Show HN: Erin – Open-source and self-hosted TikTok feed for your own videos

Show HN: Epublifier – scrape pages (books, manuals) for offline reading

Show HN: Epublifier – scrape pages (books, manuals) for offline reading

Show HN: Epublifier – scrape pages (books, manuals) for offline reading

Show HN: Semantic Macros Text Editor

Show HN: Semantic Macros Text Editor

Show HN: I created a web app to encrypt/decrypt messages using Web Crypto API

Show HN: I created a web app to encrypt/decrypt messages using Web Crypto API

Show HN: Create mind maps to learn new things using AI

Enter a topic and get a learning mind map generated by an LLM with links to learn more about each subtopic.<p>You can use it with local models (through Ollama) or external models.<p>If you have any feedback, please share it! Hope it's useful<p>Demo: <a href="https://youtu.be/Y-9He-tG3aM" rel="nofollow">https://youtu.be/Y-9He-tG3aM</a>

Show HN: Create mind maps to learn new things using AI

Enter a topic and get a learning mind map generated by an LLM with links to learn more about each subtopic.<p>You can use it with local models (through Ollama) or external models.<p>If you have any feedback, please share it! Hope it's useful<p>Demo: <a href="https://youtu.be/Y-9He-tG3aM" rel="nofollow">https://youtu.be/Y-9He-tG3aM</a>

Show HN: HN Update – Hourly news broadcast of top HN stories

I feel like it was inevitable, with the recent buzz around NotebookLM. I'm just surprised that it hasn't been done yet.

Show HN: HN Update – Hourly news broadcast of top HN stories

I feel like it was inevitable, with the recent buzz around NotebookLM. I'm just surprised that it hasn't been done yet.

Show HN: HN Update – Hourly news broadcast of top HN stories

I feel like it was inevitable, with the recent buzz around NotebookLM. I'm just surprised that it hasn't been done yet.

Show HN: I wrote an autodiff in C++ and implemented LeNet with it

Show HN: Desktop app displaying files on a 2D canvas

Hey all! I always wanted to arrange my text/markdown/pdf files on a 2D canvas and visualize them without opening all the windows. An extra feature I added is also visualizing folders within - so kind of a 3D visualization? It was also important to be an offline desktop app, rather than online tool like Miro or Mural, because once I edit files in Sublime or AdobePDF then I want changes to sync in the canvas right away.<p>Some technical points and lessons learned: being Android developer helped a lot with this project since I used Kotlin Multiplatform with Compose Desktop renderer (actually skiko). It runs on JVM under the hood, which was exciting at first since I can use the app on all of my Mac/Windows/Linux machines. Right? Wrong. One lesson I learned wasn’t “write once - run everywhere”, it was “write once - test everywhere; repeat”. On the other hand, using Kotlin Multiplatform will allow me easily to port to Android and port the logic to iOS.<p>Anyways, I released LimanDoc v1.0.3, still in Proof-Of-Concept, so I hope to get some feedback and features you think would be helpful.<p>I was thinking these features would be great for future releases: - adding a local LLM support to search/summarize your docs, books, videos, etc; - sync on local network (including future mobile apps) - Templates, groups, and better diagram integration like in Drawio.

Show HN: Desktop app displaying files on a 2D canvas

Hey all! I always wanted to arrange my text/markdown/pdf files on a 2D canvas and visualize them without opening all the windows. An extra feature I added is also visualizing folders within - so kind of a 3D visualization? It was also important to be an offline desktop app, rather than online tool like Miro or Mural, because once I edit files in Sublime or AdobePDF then I want changes to sync in the canvas right away.<p>Some technical points and lessons learned: being Android developer helped a lot with this project since I used Kotlin Multiplatform with Compose Desktop renderer (actually skiko). It runs on JVM under the hood, which was exciting at first since I can use the app on all of my Mac/Windows/Linux machines. Right? Wrong. One lesson I learned wasn’t “write once - run everywhere”, it was “write once - test everywhere; repeat”. On the other hand, using Kotlin Multiplatform will allow me easily to port to Android and port the logic to iOS.<p>Anyways, I released LimanDoc v1.0.3, still in Proof-Of-Concept, so I hope to get some feedback and features you think would be helpful.<p>I was thinking these features would be great for future releases: - adding a local LLM support to search/summarize your docs, books, videos, etc; - sync on local network (including future mobile apps) - Templates, groups, and better diagram integration like in Drawio.

Show HN: What happens if you make a crossword out of Reddit r/gaming

As a fan of dense New York Times-style crosswords, I challenged myself to create topic-specific puzzles. It turns out that generating crosswords and efficiently placing words is a non-trivial computational problem.<p>I started the project, "Joystick Jargon" combining traditional crossword elements with gaming-related vocabulary. Here's the technical process behind it:<p>1. Data Source: Used a 3.8 Million Rows Reddit dataset from Hugging Face (<a href="https://huggingface.co/datasets/webis/tldr-17" rel="nofollow">https://huggingface.co/datasets/webis/tldr-17</a>).<p>2. Data Filtering: Narrowed down to gaming-related subreddits (r/gaming, r/dota2, r/leagueoflegends).<p>3. Keyword Extraction: Employed ML techniques, specifically BERT-embeddings and cosine similarity, to extract keywords from the subreddits.<p>4. Data Preprocessing: Cleaned up data unsuitable for crossword puzzles.<p>5. Grid Generation: Implemented a heuristic crossword algorithm to create grids and place words efficiently.<p>6. Clue Generation: Utilized a Large Language Model to generate context-aware clues for the placed words.<p>The resulting system creates crossword puzzles that blend traditional elements with gaming terminology, achieving about a 50-50 mix.<p>This project is admittedly overengineered for its purpose, but it was an interesting exploration into natural language processing, optimization algorithms, and the intersection of traditional word games with modern gaming culture.<p>A note on content: Since the data source is Reddit, some mature language may appear in the puzzles. Manual filtering was minimal to preserve authenticity.<p>You can try the puzzles here: <<a href="https://capsloq.de/crosswords/joystick-jargon" rel="nofollow">https://capsloq.de/crosswords/joystick-jargon</a>><p>I'm curious about the HN community's thoughts on this approach to puzzle generation? What other domains might benefit from similar computational techniques for content creation?

Show HN: What happens if you make a crossword out of Reddit r/gaming

As a fan of dense New York Times-style crosswords, I challenged myself to create topic-specific puzzles. It turns out that generating crosswords and efficiently placing words is a non-trivial computational problem.<p>I started the project, "Joystick Jargon" combining traditional crossword elements with gaming-related vocabulary. Here's the technical process behind it:<p>1. Data Source: Used a 3.8 Million Rows Reddit dataset from Hugging Face (<a href="https://huggingface.co/datasets/webis/tldr-17" rel="nofollow">https://huggingface.co/datasets/webis/tldr-17</a>).<p>2. Data Filtering: Narrowed down to gaming-related subreddits (r/gaming, r/dota2, r/leagueoflegends).<p>3. Keyword Extraction: Employed ML techniques, specifically BERT-embeddings and cosine similarity, to extract keywords from the subreddits.<p>4. Data Preprocessing: Cleaned up data unsuitable for crossword puzzles.<p>5. Grid Generation: Implemented a heuristic crossword algorithm to create grids and place words efficiently.<p>6. Clue Generation: Utilized a Large Language Model to generate context-aware clues for the placed words.<p>The resulting system creates crossword puzzles that blend traditional elements with gaming terminology, achieving about a 50-50 mix.<p>This project is admittedly overengineered for its purpose, but it was an interesting exploration into natural language processing, optimization algorithms, and the intersection of traditional word games with modern gaming culture.<p>A note on content: Since the data source is Reddit, some mature language may appear in the puzzles. Manual filtering was minimal to preserve authenticity.<p>You can try the puzzles here: <<a href="https://capsloq.de/crosswords/joystick-jargon" rel="nofollow">https://capsloq.de/crosswords/joystick-jargon</a>><p>I'm curious about the HN community's thoughts on this approach to puzzle generation? What other domains might benefit from similar computational techniques for content creation?

How to leverage Claude's capabilities with interactive visualization

Show HN: Gomponents, HTML components in pure Go

Hey everyone! I just released v1.0.0 of gomponents last week. It's an HTML component builder in pure Go, with a DSL-like HTML syntax. It's been 4 years in the making, and makes it really easy to build HTML in your web apps.