The best Hacker News stories from Show from the past day
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Show HN: CozoDB, Hybrid Relational-Graph-Vector Database
Hi HN! We're thrilled to share CozoDB v0.6, a monumental update to our FOSS database, which already unifies relational and graph features. With the addition of vector search, CozoDB becomes an even better companion for LLMs like ChatGPT.<p>This release introduces vector search using HNSW indices within Datalog, enabling seamless integration with powerful features such as ad-hoc joins, recursive Datalog, and classical whole-graph algorithms. This update significantly broadens CozoDB's capabilities.<p>Check out the linked release note for an in-depth look at the new features, comparisons to other systems, and intriguing AI development possibilities. We'd love for you to take a look! I'll be here to answer any questions you might have.<p>Looking forward to your feedback!
Show HN: A 15 min daily stretch routine for desk workers
Show HN: A 15 min daily stretch routine for desk workers
Show HN: A 15 min daily stretch routine for desk workers
Show HN: A 15 min daily stretch routine for desk workers
Show HN: GoGoBrowse – A Peer to Peer Web Browser
Hi HN!<p>GoGoBrowse is a side project I've been working on that allows 2 users to browse the web together while voice chatting.<p>It's a proof of concept for a new model of browsing the web I've been thinking about. My thought is that before a leap to a 3D Metaverse, we need a 2D Metaverse, which is simply social web browsing. I wrote more about it here: <a href="https://gogobrowse.com/before-the-metaverse-we-need-a-new-web-browser" rel="nofollow">https://gogobrowse.com/before-the-metaverse-we-need-a-new-we...</a><p>Though the goal of an entirely social web browser is still quite a ways off, I think of this as a small first step in that direction.<p>I'd love any feedback on the app itself, and the general concept of social web browsing.
Show HN: Kinde – auth, feature flags and billing (Q3) in one integration
Show HN: Kinde – auth, feature flags and billing (Q3) in one integration
Show HN: Checksum – generate and maintain end-to-end tests using AI
Hey HN!<p>I’m Gal, co-founder at Checksum (<a href="https://checksum.ai" rel="nofollow">https://checksum.ai</a>). Checksum is a tool for automatically generating and maintaining end-to-end tests using AI.<p>I cut my teeth in applied ML in 2016 at a maritime tech company called TSG, based in Israel. When I was there, I worked on a cool product that used machine learning to detect suspicious vehicles. Radar data is pretty tough for humans to parse, but a great fit for AI – and it worked very well for detecting smugglers, terrorist activity, and that sort of thing.<p>In 2021, after a few years working in big tech (Lyft, Google), I joined a YC company, seer W21, as CTO. This is where I experienced the unique pain of trying to keep end-to-end tests in a good state. The app was quite featureful, and it was a struggle to get and maintain good test coverage.<p>Like the suspicious maritime vehicle problem I had previously encountered, building and maintaining E2E tests had all the markings of a problem where machines could outperform humans. Also, in the early user interviews, it became clear that this problem wasn’t one that just went away as organizations grew past the startup phase, but one that got even more tangled up and unpleasant.<p>We’ve been building the product for a little over a year now, and it’s been interesting to learn that some problems were surprisingly easy, and others unusually tough. To get the data we need to train our models, we use the same underlying technology that tools like Fullstory and Hotjar use, and it works quite well. Also, we’re able to get good tests from relatively few user sessions (in most cases, fewer than 200 sessions).<p>Right now, the models are really good at improving test coverage for featureful web-apps that don’t have much coverage (ie; generating and maintaining a bunch of new tests), but making existing tests better has been a tougher nut to crack. We don’t have as much of a place in organizations where test coverage is great and test quality is medium-to-poor, but we’re keen to develop in that direction.<p>We’re still early, and spend basically all of our time working with a small handful of design partners (mostly medium-sized startups struggling with test coverage), but it felt like time to share with the HN community.<p>Thanks so much, happy to answer any questions, and excited to hear your thoughts!
Show HN: Checksum – generate and maintain end-to-end tests using AI
Hey HN!<p>I’m Gal, co-founder at Checksum (<a href="https://checksum.ai" rel="nofollow">https://checksum.ai</a>). Checksum is a tool for automatically generating and maintaining end-to-end tests using AI.<p>I cut my teeth in applied ML in 2016 at a maritime tech company called TSG, based in Israel. When I was there, I worked on a cool product that used machine learning to detect suspicious vehicles. Radar data is pretty tough for humans to parse, but a great fit for AI – and it worked very well for detecting smugglers, terrorist activity, and that sort of thing.<p>In 2021, after a few years working in big tech (Lyft, Google), I joined a YC company, seer W21, as CTO. This is where I experienced the unique pain of trying to keep end-to-end tests in a good state. The app was quite featureful, and it was a struggle to get and maintain good test coverage.<p>Like the suspicious maritime vehicle problem I had previously encountered, building and maintaining E2E tests had all the markings of a problem where machines could outperform humans. Also, in the early user interviews, it became clear that this problem wasn’t one that just went away as organizations grew past the startup phase, but one that got even more tangled up and unpleasant.<p>We’ve been building the product for a little over a year now, and it’s been interesting to learn that some problems were surprisingly easy, and others unusually tough. To get the data we need to train our models, we use the same underlying technology that tools like Fullstory and Hotjar use, and it works quite well. Also, we’re able to get good tests from relatively few user sessions (in most cases, fewer than 200 sessions).<p>Right now, the models are really good at improving test coverage for featureful web-apps that don’t have much coverage (ie; generating and maintaining a bunch of new tests), but making existing tests better has been a tougher nut to crack. We don’t have as much of a place in organizations where test coverage is great and test quality is medium-to-poor, but we’re keen to develop in that direction.<p>We’re still early, and spend basically all of our time working with a small handful of design partners (mostly medium-sized startups struggling with test coverage), but it felt like time to share with the HN community.<p>Thanks so much, happy to answer any questions, and excited to hear your thoughts!
Show HN: Open-source Auth0 alternative Ory Kratos v0.13 released – nearing v1.0
Show HN: Open-source Auth0 alternative Ory Kratos v0.13 released – nearing v1.0
Show HN: Database for analyzing US companies, visualize using Apache SuperSet
My main motivation was that I wanted to be able to drill down and filter across all the available stocks, look at the data for myself, and narrow down on the stocks I am interested based on my own sets of criteria, and make data-driven analysis for my personal investment strategies.<p>I used PostgreSQL as the backend database for ELT data pipelines, and used Citus Data cstore_fdw for columnar compression for the final dataset. All financial data is coming from SEC Edgar, <a href="https://www.sec.gov/developer" rel="nofollow">https://www.sec.gov/developer</a>. I used Python for downloading most of the data.<p>I also run the data load development locally on my home Ubuntu server that I built 5 years ago. I bought 4TB of M2 disks for best database performance, with PRIME B360M-A motherboard and Intel Chip Coffee Lake S.<p>I built the website simply using WordPress, and I run Apache Superset using gunicorn via Apache Webserver reverse proxy.<p>The registration form I had to build myself with PHP and some JavaScript, because it needed to automatically create a SuperSet user upon registration. Otherwise, I would need to input everyone manually. I used Python again for the data integration.<p>Please don't use the database directly as an investment tool, as its in Beta, and the data still needs to undergo heavy data quality checks, please confirm all the numbers yourself, as I provide a link for every company to the SEC filings.
Show HN: Database for analyzing US companies, visualize using Apache SuperSet
My main motivation was that I wanted to be able to drill down and filter across all the available stocks, look at the data for myself, and narrow down on the stocks I am interested based on my own sets of criteria, and make data-driven analysis for my personal investment strategies.<p>I used PostgreSQL as the backend database for ELT data pipelines, and used Citus Data cstore_fdw for columnar compression for the final dataset. All financial data is coming from SEC Edgar, <a href="https://www.sec.gov/developer" rel="nofollow">https://www.sec.gov/developer</a>. I used Python for downloading most of the data.<p>I also run the data load development locally on my home Ubuntu server that I built 5 years ago. I bought 4TB of M2 disks for best database performance, with PRIME B360M-A motherboard and Intel Chip Coffee Lake S.<p>I built the website simply using WordPress, and I run Apache Superset using gunicorn via Apache Webserver reverse proxy.<p>The registration form I had to build myself with PHP and some JavaScript, because it needed to automatically create a SuperSet user upon registration. Otherwise, I would need to input everyone manually. I used Python again for the data integration.<p>Please don't use the database directly as an investment tool, as its in Beta, and the data still needs to undergo heavy data quality checks, please confirm all the numbers yourself, as I provide a link for every company to the SEC filings.
Show HN: AI Playground by Vercel Labs
Hey, Jared Palmer (creator of this playground) here. Really excited to ship this.
I’ve been building this over the past few weeks to compare LLMs from different providers like OpenAI, Anthropic, Cohere, etc. At Vercel, I manage our Frameworks division (including Next.js, Svelte, and Turbo) and wanted to also dogfood some of the latest features in a slightly larger application.
This playground takes a lot of inspiration from <a href="https://nat.dev" rel="nofollow">https://nat.dev</a> and is built on Tailwind, ui.shadcn.com, and some upcoming Vercel products we’re announcing soon. We’re going to continue adding models to compare and add other frameworks to generate code snippets from.
Show HN: AI Playground by Vercel Labs
Hey, Jared Palmer (creator of this playground) here. Really excited to ship this.
I’ve been building this over the past few weeks to compare LLMs from different providers like OpenAI, Anthropic, Cohere, etc. At Vercel, I manage our Frameworks division (including Next.js, Svelte, and Turbo) and wanted to also dogfood some of the latest features in a slightly larger application.
This playground takes a lot of inspiration from <a href="https://nat.dev" rel="nofollow">https://nat.dev</a> and is built on Tailwind, ui.shadcn.com, and some upcoming Vercel products we’re announcing soon. We’re going to continue adding models to compare and add other frameworks to generate code snippets from.
Show HN: IronBoy, a highly accurate GameBoy emulator written in Rust, runs WASM
Hey HN! Been working on this emulator on and off for the last couple years, and thought now would be a good time to try and show it off here.<p>As far as unique features... I think this is the only online GameBoy emulator with support for save files? So there's your reason to exist, I guess.<p>The WASM port was something I had in the back of my mind but I just kept putting it off because it seemed like it would've been a pain in the ass to implement, but all in all I think it took less than a week so that was a nice surprise!
Show HN: IronBoy, a highly accurate GameBoy emulator written in Rust, runs WASM
Hey HN! Been working on this emulator on and off for the last couple years, and thought now would be a good time to try and show it off here.<p>As far as unique features... I think this is the only online GameBoy emulator with support for save files? So there's your reason to exist, I guess.<p>The WASM port was something I had in the back of my mind but I just kept putting it off because it seemed like it would've been a pain in the ass to implement, but all in all I think it took less than a week so that was a nice surprise!
Show HN: ThinkGPT: a library to prompt GPT to think, memorize and self-refine
Show HN: ThinkGPT: a library to prompt GPT to think, memorize and self-refine