The best Hacker News stories from Show from the past day
Latest posts:
Show HN: Procal: A simple Qt-based programming calculator
Show HN: Procal: A simple Qt-based programming calculator
Show HN: Practice Job Interview with ChatGPT API
Hi HN!<p>ChatGPT API was just released and I'm eager to hack something with it.<p>So I created PracticeInterview.co to help people practice for their next job interview.<p>ChatGPT acts as the interviewer and you can choose to interview for various roles such as Finance Manager, Social Media Manager, and Software Engineer.<p>I think this is a cool implementation of ChatGPT and the interview sessions so far has been pretty coherent.<p>Please give it a try! It's free, no logins required, and your interview session is saved so you can comeback to it later.<p>Since it's an MVP, I would welcome all feedback. Thanks HN!
Show HN: Zipslicer, a library for loading LLM checkpoints on consumer hardware
This is a low-level opensource library I developed for my own use and decided to share, as it makes it possible to process large checkpoints of neural networks without renting high-RAM instances, on a regular PC. It replaces torch.load() with a custom function that produces a dictionary that materializes tensors on the fly. Compared to other solutions it doesn't require sharding or re-encoding checkpoints and uses them completely as-is.<p>It is a foundation to make it possible to run inference and compress language models and other large models one layer at a time - in principle, even one tensor at a time.<p>I describe the rationale and technical details of the library's design in the blogpost: <a href="https://kir-gadjello.github.io/posts/zipslicer/" rel="nofollow">https://kir-gadjello.github.io/posts/zipslicer/</a>
Show HN: Zipslicer, a library for loading LLM checkpoints on consumer hardware
This is a low-level opensource library I developed for my own use and decided to share, as it makes it possible to process large checkpoints of neural networks without renting high-RAM instances, on a regular PC. It replaces torch.load() with a custom function that produces a dictionary that materializes tensors on the fly. Compared to other solutions it doesn't require sharding or re-encoding checkpoints and uses them completely as-is.<p>It is a foundation to make it possible to run inference and compress language models and other large models one layer at a time - in principle, even one tensor at a time.<p>I describe the rationale and technical details of the library's design in the blogpost: <a href="https://kir-gadjello.github.io/posts/zipslicer/" rel="nofollow">https://kir-gadjello.github.io/posts/zipslicer/</a>
Show HN: Nosey Parker, a fast and low-noise secrets detector for textual data
Nosey Parker is an Apache-licensed command-line tool that finds secrets and sensitive information in textual data. It's useful both for offensive and defensive security testing.<p>The big idea: textual content in, hardcoded secrets out. These include things like API keys and passwords.<p>It should do a reasonable job on any textual input. It will recursively scan any directories it is pointed at. It also has special support for scanning the complete contents of Git repositories.<p>The default rules in Nosey Parker have been carefully chosen to minimize false positives. Many API tokens these days have well-specified formats that are amenable to precise matching with regular expressions, and these are the kind of things that the default rules detect. Additionally, its findings are deduplicated. Together, these give much higher signal-to-noise compared to similar tools.<p>Nosey Parker is fast: it can scan 100GB of Linux kernel commit history in just over a minute on my laptop. This speed comes from several factors, but most significantly from using the amazing Hyperscan library for simultaneous matching of all regex rules in a single pass. In comparison with similar tools on large inputs, Nosey Parker is usually 1-3 orders of magnitude faster.<p>Nosey Parker was originally created to help construct a labeled dataset of secrets for machine learning purposes. But it proved surprisingly useful on its own. In the past year, an internal, proprietary version (with added machine learning capabilities) has been regularly used in security engagements at Praetorian.<p>In late 2022, Nosey Parker was reimplemented in Rust, released as open-source, and presented at Black Hat Arsenal.<p>It now supports enumeration and scanning of GitHub repositories by providing just usernames or organization names. It also recently got support for SARIF output, which several other tools understand.
Show HN: Nosey Parker, a fast and low-noise secrets detector for textual data
Nosey Parker is an Apache-licensed command-line tool that finds secrets and sensitive information in textual data. It's useful both for offensive and defensive security testing.<p>The big idea: textual content in, hardcoded secrets out. These include things like API keys and passwords.<p>It should do a reasonable job on any textual input. It will recursively scan any directories it is pointed at. It also has special support for scanning the complete contents of Git repositories.<p>The default rules in Nosey Parker have been carefully chosen to minimize false positives. Many API tokens these days have well-specified formats that are amenable to precise matching with regular expressions, and these are the kind of things that the default rules detect. Additionally, its findings are deduplicated. Together, these give much higher signal-to-noise compared to similar tools.<p>Nosey Parker is fast: it can scan 100GB of Linux kernel commit history in just over a minute on my laptop. This speed comes from several factors, but most significantly from using the amazing Hyperscan library for simultaneous matching of all regex rules in a single pass. In comparison with similar tools on large inputs, Nosey Parker is usually 1-3 orders of magnitude faster.<p>Nosey Parker was originally created to help construct a labeled dataset of secrets for machine learning purposes. But it proved surprisingly useful on its own. In the past year, an internal, proprietary version (with added machine learning capabilities) has been regularly used in security engagements at Praetorian.<p>In late 2022, Nosey Parker was reimplemented in Rust, released as open-source, and presented at Black Hat Arsenal.<p>It now supports enumeration and scanning of GitHub repositories by providing just usernames or organization names. It also recently got support for SARIF output, which several other tools understand.
Show HN: Classic FPS Wolfenstein 3D brought in the browser via Emscripten
Show HN: Classic FPS Wolfenstein 3D brought in the browser via Emscripten
Show HN: Classic FPS Wolfenstein 3D brought in the browser via Emscripten
Show HN: Quality News – Towards a fairer ranking algorithm for Hacker News
Hello HN!<p>TLDR;<p>- Quality News is a Hacker News client that provides additional data and insights on submissions, notably, the upvoteRate metric.<p>- We propose that this metric could be used to improve the Hacker News ranking score.<p>- In-depth explanation: <a href="https://github.com/social-protocols/news#readme">https://github.com/social-protocols/news#readme</a><p>The Hacker News ranking score is directly proportional to upvotes, which is a problem because it creates a feedback loop: higher rank leads to more upvotes leads to higher rank, and so on...<p><pre><code> →
↗ ↘
Higher Rank More Upvotes
↖ ↙
←
</code></pre>
As a consequence, success on HN depends almost entirely on getting enough upvotes in the first hour or so to make the front page and get caught in this feedback loop. And getting these early upvotes is largely a matter of timing, luck, and moderator decisions. And so the best stories don't always make the front page, and the stories on the front page are not always the best.<p>Our proposed solution is to use upvoteRate instead of upvotes in the ranking formula. upvoteRate is an estimate of how much more or less likely users are to upvote a story compared to the average story, taking account how much attention the story as received, based on a history of the ranks and times at which it has been shown. You can read about how we calculate this metric in more detail here: <a href="https://github.com/social-protocols/news#readme">https://github.com/social-protocols/news#readme</a><p>About 1.5 years ago, we published an article with this basic idea of counteracting the rank-upvotes feedback loop by using attention as negative feedback. We received very valuable input from the HN community (<a href="https://news.ycombinator.com/item?id=28391659" rel="nofollow">https://news.ycombinator.com/item?id=28391659</a>). Quality News has been created based largely on this feedback.<p>Currently, Quality News shows the upvoteRate metric for live Hacker News data, as well as charts of the rank and upvote history of each story. We have not yet implemented an alternative ranking algorithm, because we don't have access to data on flags and moderator actions, which are a major component of the HN ranking score.<p>We'd love to see the Hacker News team experiment with the new formula, perhaps on an alternative front page. This will allow the community to evaluate whether the new ranking formula is an improvement over the current one.<p>We look forward discussing our approach with you!<p>Links:<p>Site: <a href="https://news.social-protocols.org/" rel="nofollow">https://news.social-protocols.org/</a><p>Readme: <a href="https://github.com/social-protocols/news#readme">https://github.com/social-protocols/news#readme</a><p>Previous Blog Post: <a href="https://felx.me/2021/08/29/improving-the-hacker-news-ranking-algorithm.html" rel="nofollow">https://felx.me/2021/08/29/improving-the-hacker-news-ranking...</a><p>Previous Discussion: <a href="https://news.ycombinator.com/item?id=28391659" rel="nofollow">https://news.ycombinator.com/item?id=28391659</a>
Show HN: Quality News – Towards a fairer ranking algorithm for Hacker News
Hello HN!<p>TLDR;<p>- Quality News is a Hacker News client that provides additional data and insights on submissions, notably, the upvoteRate metric.<p>- We propose that this metric could be used to improve the Hacker News ranking score.<p>- In-depth explanation: <a href="https://github.com/social-protocols/news#readme">https://github.com/social-protocols/news#readme</a><p>The Hacker News ranking score is directly proportional to upvotes, which is a problem because it creates a feedback loop: higher rank leads to more upvotes leads to higher rank, and so on...<p><pre><code> →
↗ ↘
Higher Rank More Upvotes
↖ ↙
←
</code></pre>
As a consequence, success on HN depends almost entirely on getting enough upvotes in the first hour or so to make the front page and get caught in this feedback loop. And getting these early upvotes is largely a matter of timing, luck, and moderator decisions. And so the best stories don't always make the front page, and the stories on the front page are not always the best.<p>Our proposed solution is to use upvoteRate instead of upvotes in the ranking formula. upvoteRate is an estimate of how much more or less likely users are to upvote a story compared to the average story, taking account how much attention the story as received, based on a history of the ranks and times at which it has been shown. You can read about how we calculate this metric in more detail here: <a href="https://github.com/social-protocols/news#readme">https://github.com/social-protocols/news#readme</a><p>About 1.5 years ago, we published an article with this basic idea of counteracting the rank-upvotes feedback loop by using attention as negative feedback. We received very valuable input from the HN community (<a href="https://news.ycombinator.com/item?id=28391659" rel="nofollow">https://news.ycombinator.com/item?id=28391659</a>). Quality News has been created based largely on this feedback.<p>Currently, Quality News shows the upvoteRate metric for live Hacker News data, as well as charts of the rank and upvote history of each story. We have not yet implemented an alternative ranking algorithm, because we don't have access to data on flags and moderator actions, which are a major component of the HN ranking score.<p>We'd love to see the Hacker News team experiment with the new formula, perhaps on an alternative front page. This will allow the community to evaluate whether the new ranking formula is an improvement over the current one.<p>We look forward discussing our approach with you!<p>Links:<p>Site: <a href="https://news.social-protocols.org/" rel="nofollow">https://news.social-protocols.org/</a><p>Readme: <a href="https://github.com/social-protocols/news#readme">https://github.com/social-protocols/news#readme</a><p>Previous Blog Post: <a href="https://felx.me/2021/08/29/improving-the-hacker-news-ranking-algorithm.html" rel="nofollow">https://felx.me/2021/08/29/improving-the-hacker-news-ranking...</a><p>Previous Discussion: <a href="https://news.ycombinator.com/item?id=28391659" rel="nofollow">https://news.ycombinator.com/item?id=28391659</a>
Show HN: ChatGPT Bot Trained on Reddit Data
I'm heavily relying on Reddit for my online research, but there are many repetitive questions and recommendations on subreddits, so I trained a GPT bot on over 100k r/BuyItForLife comments and posts to embody the collective knowledge of this Reddit community (and soon many other subreddits).<p>Some posts I answered with the bot:<p>- Request Post: Dishwashers. What’s currently the best dishwasher for home use?<p>- Bot Answer: <a href="https://www.looria.com/bot?q=what's+currently+the+best+dishwasher+for+home+use" rel="nofollow">https://www.looria.com/bot?q=what's+currently+the+best+dis...</a><p>- Request Post : Recommendations for hiking shoes?<p>- Bot Answer: <a href="https://www.looria.com/bot?q=Recommendations+for+hiking+shoes" rel="nofollow">https://www.looria.com/bot?q=Recommendations+for+hiking+shoe...</a><p>------------<p>It's far from perfect and comes with limitations:<p>- Outdated information: I'll try to improve this by factoring in recency and some additional product information like prices, specs, etc, that I'm collecting. I also want to add more statistical significance to the results, e.g. by feeding in the amount of product recommendations over time.<p>- Hallucination: As always with these bots, they sometimes make things up. More training data should help here.<p>- Performance: Generating the answers is pretty slow and I'll look into improving this.<p>Take it with a grain of salt and look at it as a fun experiment :) Would love to hear your feedback!
Show HN: ChatGPT Bot Trained on Reddit Data
I'm heavily relying on Reddit for my online research, but there are many repetitive questions and recommendations on subreddits, so I trained a GPT bot on over 100k r/BuyItForLife comments and posts to embody the collective knowledge of this Reddit community (and soon many other subreddits).<p>Some posts I answered with the bot:<p>- Request Post: Dishwashers. What’s currently the best dishwasher for home use?<p>- Bot Answer: <a href="https://www.looria.com/bot?q=what's+currently+the+best+dishwasher+for+home+use" rel="nofollow">https://www.looria.com/bot?q=what's+currently+the+best+dis...</a><p>- Request Post : Recommendations for hiking shoes?<p>- Bot Answer: <a href="https://www.looria.com/bot?q=Recommendations+for+hiking+shoes" rel="nofollow">https://www.looria.com/bot?q=Recommendations+for+hiking+shoe...</a><p>------------<p>It's far from perfect and comes with limitations:<p>- Outdated information: I'll try to improve this by factoring in recency and some additional product information like prices, specs, etc, that I'm collecting. I also want to add more statistical significance to the results, e.g. by feeding in the amount of product recommendations over time.<p>- Hallucination: As always with these bots, they sometimes make things up. More training data should help here.<p>- Performance: Generating the answers is pretty slow and I'll look into improving this.<p>Take it with a grain of salt and look at it as a fun experiment :) Would love to hear your feedback!
Show HN: Beatbot.fm – Make Songs with AI
Show HN: Mathesar – open-source collaborative UI for Postgres databases
Hi HN! We just released the public alpha version of Mathesar (<a href="https://mathesar.org/" rel="nofollow">https://mathesar.org/</a>, code: <a href="https://github.com/centerofci/mathesar">https://github.com/centerofci/mathesar</a>).<p>Mathesar is an open source tool that provides a spreadsheet-like interface to a PostgreSQL database.<p>I was originally inspired by wanting to build something like Dabble DB. I was in awe of their user experience for working with relational data. There’s plenty of “relational spreadsheet” software out there, but I haven’t been able to find anything with a comparable UX since Twitter shut Dabble DB down.<p>We're a non-profit project. The core team is based out of a US 501(c)(3).<p>Features:<p>* <i>Built on Postgres</i>: Connect to an existing Postgres database or set one up from scratch.<p>* <i>Utilizes Postgres Features</i>: Mathesar’s UI uses Postgres features. e.g. "Links" in the UI are foreign keys in the database.<p>* <i>Set up Data Models</i>: Easily create and update Postgres schemas and tables.<p>* <i>Data Entry</i>: Use our spreadsheet-like interface to view, create, update, and delete table records.<p>* <i>Data Explorer</i>: Use our Data Explorer to build queries without knowing anything about SQL or joins.<p>* <i>Schema Migrations</i>: Transfer columns between tables in two clicks in the UI.<p>* <i>Custom Data Types</i>:: Custom data types for emails and URLs (more coming soon), validated at the database level.<p>Links:<p>CODE: <a href="https://github.com/centerofci/mathesar">https://github.com/centerofci/mathesar</a><p>LIVE DEMO: <a href="https://demo.mathesar.org/" rel="nofollow">https://demo.mathesar.org/</a><p>DOCS: <a href="https://docs.mathesar.org/" rel="nofollow">https://docs.mathesar.org/</a><p>COMMUNITY: <a href="https://wiki.mathesar.org/en/community" rel="nofollow">https://wiki.mathesar.org/en/community</a><p>WEBSITE: https:/mathesar.org/<p>SPONSOR US: <a href="https://github.com/sponsors/centerofci">https://github.com/sponsors/centerofci</a> or <a href="https://opencollective.com/mathesar" rel="nofollow">https://opencollective.com/mathesar</a>
Show HN: Mathesar – open-source collaborative UI for Postgres databases
Hi HN! We just released the public alpha version of Mathesar (<a href="https://mathesar.org/" rel="nofollow">https://mathesar.org/</a>, code: <a href="https://github.com/centerofci/mathesar">https://github.com/centerofci/mathesar</a>).<p>Mathesar is an open source tool that provides a spreadsheet-like interface to a PostgreSQL database.<p>I was originally inspired by wanting to build something like Dabble DB. I was in awe of their user experience for working with relational data. There’s plenty of “relational spreadsheet” software out there, but I haven’t been able to find anything with a comparable UX since Twitter shut Dabble DB down.<p>We're a non-profit project. The core team is based out of a US 501(c)(3).<p>Features:<p>* <i>Built on Postgres</i>: Connect to an existing Postgres database or set one up from scratch.<p>* <i>Utilizes Postgres Features</i>: Mathesar’s UI uses Postgres features. e.g. "Links" in the UI are foreign keys in the database.<p>* <i>Set up Data Models</i>: Easily create and update Postgres schemas and tables.<p>* <i>Data Entry</i>: Use our spreadsheet-like interface to view, create, update, and delete table records.<p>* <i>Data Explorer</i>: Use our Data Explorer to build queries without knowing anything about SQL or joins.<p>* <i>Schema Migrations</i>: Transfer columns between tables in two clicks in the UI.<p>* <i>Custom Data Types</i>:: Custom data types for emails and URLs (more coming soon), validated at the database level.<p>Links:<p>CODE: <a href="https://github.com/centerofci/mathesar">https://github.com/centerofci/mathesar</a><p>LIVE DEMO: <a href="https://demo.mathesar.org/" rel="nofollow">https://demo.mathesar.org/</a><p>DOCS: <a href="https://docs.mathesar.org/" rel="nofollow">https://docs.mathesar.org/</a><p>COMMUNITY: <a href="https://wiki.mathesar.org/en/community" rel="nofollow">https://wiki.mathesar.org/en/community</a><p>WEBSITE: https:/mathesar.org/<p>SPONSOR US: <a href="https://github.com/sponsors/centerofci">https://github.com/sponsors/centerofci</a> or <a href="https://opencollective.com/mathesar" rel="nofollow">https://opencollective.com/mathesar</a>
Show HN: Mathesar – open-source collaborative UI for Postgres databases
Hi HN! We just released the public alpha version of Mathesar (<a href="https://mathesar.org/" rel="nofollow">https://mathesar.org/</a>, code: <a href="https://github.com/centerofci/mathesar">https://github.com/centerofci/mathesar</a>).<p>Mathesar is an open source tool that provides a spreadsheet-like interface to a PostgreSQL database.<p>I was originally inspired by wanting to build something like Dabble DB. I was in awe of their user experience for working with relational data. There’s plenty of “relational spreadsheet” software out there, but I haven’t been able to find anything with a comparable UX since Twitter shut Dabble DB down.<p>We're a non-profit project. The core team is based out of a US 501(c)(3).<p>Features:<p>* <i>Built on Postgres</i>: Connect to an existing Postgres database or set one up from scratch.<p>* <i>Utilizes Postgres Features</i>: Mathesar’s UI uses Postgres features. e.g. "Links" in the UI are foreign keys in the database.<p>* <i>Set up Data Models</i>: Easily create and update Postgres schemas and tables.<p>* <i>Data Entry</i>: Use our spreadsheet-like interface to view, create, update, and delete table records.<p>* <i>Data Explorer</i>: Use our Data Explorer to build queries without knowing anything about SQL or joins.<p>* <i>Schema Migrations</i>: Transfer columns between tables in two clicks in the UI.<p>* <i>Custom Data Types</i>:: Custom data types for emails and URLs (more coming soon), validated at the database level.<p>Links:<p>CODE: <a href="https://github.com/centerofci/mathesar">https://github.com/centerofci/mathesar</a><p>LIVE DEMO: <a href="https://demo.mathesar.org/" rel="nofollow">https://demo.mathesar.org/</a><p>DOCS: <a href="https://docs.mathesar.org/" rel="nofollow">https://docs.mathesar.org/</a><p>COMMUNITY: <a href="https://wiki.mathesar.org/en/community" rel="nofollow">https://wiki.mathesar.org/en/community</a><p>WEBSITE: https:/mathesar.org/<p>SPONSOR US: <a href="https://github.com/sponsors/centerofci">https://github.com/sponsors/centerofci</a> or <a href="https://opencollective.com/mathesar" rel="nofollow">https://opencollective.com/mathesar</a>
Show HN: Mathesar – open-source collaborative UI for Postgres databases
Hi HN! We just released the public alpha version of Mathesar (<a href="https://mathesar.org/" rel="nofollow">https://mathesar.org/</a>, code: <a href="https://github.com/centerofci/mathesar">https://github.com/centerofci/mathesar</a>).<p>Mathesar is an open source tool that provides a spreadsheet-like interface to a PostgreSQL database.<p>I was originally inspired by wanting to build something like Dabble DB. I was in awe of their user experience for working with relational data. There’s plenty of “relational spreadsheet” software out there, but I haven’t been able to find anything with a comparable UX since Twitter shut Dabble DB down.<p>We're a non-profit project. The core team is based out of a US 501(c)(3).<p>Features:<p>* <i>Built on Postgres</i>: Connect to an existing Postgres database or set one up from scratch.<p>* <i>Utilizes Postgres Features</i>: Mathesar’s UI uses Postgres features. e.g. "Links" in the UI are foreign keys in the database.<p>* <i>Set up Data Models</i>: Easily create and update Postgres schemas and tables.<p>* <i>Data Entry</i>: Use our spreadsheet-like interface to view, create, update, and delete table records.<p>* <i>Data Explorer</i>: Use our Data Explorer to build queries without knowing anything about SQL or joins.<p>* <i>Schema Migrations</i>: Transfer columns between tables in two clicks in the UI.<p>* <i>Custom Data Types</i>:: Custom data types for emails and URLs (more coming soon), validated at the database level.<p>Links:<p>CODE: <a href="https://github.com/centerofci/mathesar">https://github.com/centerofci/mathesar</a><p>LIVE DEMO: <a href="https://demo.mathesar.org/" rel="nofollow">https://demo.mathesar.org/</a><p>DOCS: <a href="https://docs.mathesar.org/" rel="nofollow">https://docs.mathesar.org/</a><p>COMMUNITY: <a href="https://wiki.mathesar.org/en/community" rel="nofollow">https://wiki.mathesar.org/en/community</a><p>WEBSITE: https:/mathesar.org/<p>SPONSOR US: <a href="https://github.com/sponsors/centerofci">https://github.com/sponsors/centerofci</a> or <a href="https://opencollective.com/mathesar" rel="nofollow">https://opencollective.com/mathesar</a>
Show HN: Touca – a better alternative to snapshot testing
Hi everyone,<p>Almost 2 years ago, I left my full-time job at Canon to build tooling and infrastructure to help developers write high-level tests for complex software workflows that are not easy to unit test. I wanted to take ideas from visual regression testing, snapshot testing, and property-based testing and build a general-purpose regression testing system that developers can use to find the unintended side-effects of their day-to-day code changes during the development stage.<p>After two years of working ~70 hours per week and going through multiple iterations, we finally have a fully open-source (Apache-2.0) product that finally makes me and other members of our community happy: <a href="https://github.com/trytouca/trytouca">https://github.com/trytouca/trytouca</a><p>This week we released v2.0, a milestone version that is useful to small and large teams alike. This version comes with:<p>- An easy to self-host server that stores test results for new versions of your software workflows, automatically compares them against a previous baseline version, and reports any differences in behavior or performance.<p>- A CLI that enables snapshot testing without using snapshot files. It lets you capture the actual output of your software and remotely compare it against a previous version without having to write code or to locally store the previous output.<p>- 4 SDKs in Python, C++, Java, JavaScript that let you write high-level tests to capture values of variables and runtime of functions for different test cases and submit them to the Touca server.<p>- Test runner and GitHub action plugins that help you continuously run your tests as part of the CI and find breaking changes before merging PRs.<p>I would really appreciate your honest feedback, positive or negative, about Touca. Would love to learn if you find this useful and look forward to hearing your thoughts and answering any questions.