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Show HN: Hacker News user blogroll
I saw this [0] pretty cool thread by user revskill, and wanted a quicker way to search through it, but also to keep them all in one place so I can read them at my leisure whenever I get time.<p>Right now is like 60 lines of Ruby using Nokogiri, but I will certainly look into it further down the line and improve the list.<p>There's a cronjob checking the thread every 12 hours but I will eventually shut that down and it will become static after that.<p>There are some really awesome blogs in there. I really recommend going through the list, it made my day.<p>[0] "Could you share your personal blog here". <a href="https://news.ycombinator.com/item?id=36575081">https://news.ycombinator.com/item?id=36575081</a>
Show HN: Hacker News user blogroll
I saw this [0] pretty cool thread by user revskill, and wanted a quicker way to search through it, but also to keep them all in one place so I can read them at my leisure whenever I get time.<p>Right now is like 60 lines of Ruby using Nokogiri, but I will certainly look into it further down the line and improve the list.<p>There's a cronjob checking the thread every 12 hours but I will eventually shut that down and it will become static after that.<p>There are some really awesome blogs in there. I really recommend going through the list, it made my day.<p>[0] "Could you share your personal blog here". <a href="https://news.ycombinator.com/item?id=36575081">https://news.ycombinator.com/item?id=36575081</a>
Show HN: Hacker News user blogroll
I saw this [0] pretty cool thread by user revskill, and wanted a quicker way to search through it, but also to keep them all in one place so I can read them at my leisure whenever I get time.<p>Right now is like 60 lines of Ruby using Nokogiri, but I will certainly look into it further down the line and improve the list.<p>There's a cronjob checking the thread every 12 hours but I will eventually shut that down and it will become static after that.<p>There are some really awesome blogs in there. I really recommend going through the list, it made my day.<p>[0] "Could you share your personal blog here". <a href="https://news.ycombinator.com/item?id=36575081">https://news.ycombinator.com/item?id=36575081</a>
Show HN: Iridescent crystal with raymarching and signed distance fields
Show HN: Iridescent crystal with raymarching and signed distance fields
Show HN: Iridescent crystal with raymarching and signed distance fields
Show HN: MongoDB Protocol for SQLite
Show HN: MongoDB Protocol for SQLite
Show HN: MongoDB Protocol for SQLite
Show HN: Degrees What?
One of my pet peeves is when people specify a temperature in "degrees" when it’s not clear from the context which scale is being used. I always want to ask “degrees what?”<p>So I made this little conversion tool that uses degrees angle to convert between degrees Fahrenheit and degrees Celsius.<p>Tip: you can add a number in a query to link directly to a temperature. e.g. <a href="https://degreeswhat.com/?100" rel="nofollow noreferrer">https://degreeswhat.com/?100</a>
Show HN: Degrees What?
One of my pet peeves is when people specify a temperature in "degrees" when it’s not clear from the context which scale is being used. I always want to ask “degrees what?”<p>So I made this little conversion tool that uses degrees angle to convert between degrees Fahrenheit and degrees Celsius.<p>Tip: you can add a number in a query to link directly to a temperature. e.g. <a href="https://degreeswhat.com/?100" rel="nofollow noreferrer">https://degreeswhat.com/?100</a>
Show HN: Chrome Dev Tools Element Selector for Playwright and Scraping
Show HN: Chrome Dev Tools Element Selector for Playwright and Scraping
Show HN: Yet another macOS ChatGPT app
What I thought would take me weeks in development, took me months, but it's finally out. When ChatGPT API came out in March, my first idea of what to build with it was a spotlight-like app for my mac. The product was ready in a matter of days, but making it useful and sellable to people via some kind of distribution platform was another challenge. Coming from web development, learning how to ship a native app was a trip, but here it is, ready to share with the world. Try it out with the free trial, and I'd appreciate any kind of feedback.
Show HN: Bigcapital - An open-source alternative to QuickBooks
Show HN: Bigcapital - An open-source alternative to QuickBooks
Show HN: JobLens – AI-powered job search for 'Who Is Hiring'
There are existing HN job aggregators, but I thought we could take it a step further.
Inspired by an insightful comment on a previous thread (<a href="https://news.ycombinator.com/item?id=36163021">https://news.ycombinator.com/item?id=36163021</a>), I built a tool that aggregates job postings and intelligently categorizes them based on user-specific preferences:<p>* Country and remote work preferences<p>* Employer type (e.g., startup, corporation, government)<p>* Industry<p>* Technologies used<p>* Role type (developer, architect, product owner, etc.)<p>* Salary range (where available)<p>One of the superpowers of LLMs is reformatting information from any format X to any other format Y.
We leverage this to map all the unstructured job postings into the same unified structure. The new GPT functions feature and the extended context windows are really helpful for this.
Instead of having to build a custom NER pipeline, it works very well with GPT out-of-the box.<p>One challenge is keeping the filters consistent and merging of duplicates. Embeddings help with that.<p>What's next:<p>* Integrate additional sources. We can generate web scrapers and data processing steps on the fly that extract and transform data into the same structure.<p>* Add location distance filters.<p>* Expand beyond jobs to monitor personalized data like events or real estate. Imagine using AI to rate local events from multiple sources based on your preferences, considering factors like your interests and distance from home.<p>* Smaller improvements based on your feedback :)
Show HN: JobLens – AI-powered job search for 'Who Is Hiring'
There are existing HN job aggregators, but I thought we could take it a step further.
Inspired by an insightful comment on a previous thread (<a href="https://news.ycombinator.com/item?id=36163021">https://news.ycombinator.com/item?id=36163021</a>), I built a tool that aggregates job postings and intelligently categorizes them based on user-specific preferences:<p>* Country and remote work preferences<p>* Employer type (e.g., startup, corporation, government)<p>* Industry<p>* Technologies used<p>* Role type (developer, architect, product owner, etc.)<p>* Salary range (where available)<p>One of the superpowers of LLMs is reformatting information from any format X to any other format Y.
We leverage this to map all the unstructured job postings into the same unified structure. The new GPT functions feature and the extended context windows are really helpful for this.
Instead of having to build a custom NER pipeline, it works very well with GPT out-of-the box.<p>One challenge is keeping the filters consistent and merging of duplicates. Embeddings help with that.<p>What's next:<p>* Integrate additional sources. We can generate web scrapers and data processing steps on the fly that extract and transform data into the same structure.<p>* Add location distance filters.<p>* Expand beyond jobs to monitor personalized data like events or real estate. Imagine using AI to rate local events from multiple sources based on your preferences, considering factors like your interests and distance from home.<p>* Smaller improvements based on your feedback :)
Show HN: JobLens – AI-powered job search for 'Who Is Hiring'
There are existing HN job aggregators, but I thought we could take it a step further.
Inspired by an insightful comment on a previous thread (<a href="https://news.ycombinator.com/item?id=36163021">https://news.ycombinator.com/item?id=36163021</a>), I built a tool that aggregates job postings and intelligently categorizes them based on user-specific preferences:<p>* Country and remote work preferences<p>* Employer type (e.g., startup, corporation, government)<p>* Industry<p>* Technologies used<p>* Role type (developer, architect, product owner, etc.)<p>* Salary range (where available)<p>One of the superpowers of LLMs is reformatting information from any format X to any other format Y.
We leverage this to map all the unstructured job postings into the same unified structure. The new GPT functions feature and the extended context windows are really helpful for this.
Instead of having to build a custom NER pipeline, it works very well with GPT out-of-the box.<p>One challenge is keeping the filters consistent and merging of duplicates. Embeddings help with that.<p>What's next:<p>* Integrate additional sources. We can generate web scrapers and data processing steps on the fly that extract and transform data into the same structure.<p>* Add location distance filters.<p>* Expand beyond jobs to monitor personalized data like events or real estate. Imagine using AI to rate local events from multiple sources based on your preferences, considering factors like your interests and distance from home.<p>* Smaller improvements based on your feedback :)
Show HN: Prototype for ETH Signing for endorsing Wikipedia updates
Wikipedia suffers from vandalism. We built a prototype for making endorsement from cryptographically signed signature using Ethereum wallet (e.g. MetaMask)