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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)
Show HN: Python can make 3M+ WebSocket keys per second
Show HN: Python can make 3M+ WebSocket keys per second
Show HN: Using C++23 <stacktrace> to get proper crash logs in C++ programs
Show HN: Using C++23 <stacktrace> to get proper crash logs in C++ programs
Show HN: Using C++23 <stacktrace> to get proper crash logs in C++ programs
Show HN: Project S.A.T.U.R.D.A.Y. – open-source, self hosted, J.A.R.V.I.S.
Welcome to Project S.A.T.U.R.D.A.Y. This is a project that allows anyone to easily build their own self-hosted J.A.R.V.I.S-like voice assistant. In my mind vocal computing is the future of human-computer interaction and by open sourcing this code I hope to expedite us on that path.<p>I have had a blast working on this so far and I'm excited to continue to build with it. It uses whisper.cpp [1], Coqui TTS [2] and OpenAI [3] to do speech-to-text, text-to-text and text-to-speech inference all 100% locally (except for text-to-text). In the future I plan to swap out OpenAI for llama.cpp [4]. It is built on top of WebRTC as the media transmission layer which will allow this technology to be deployed anywhere as it does not rely on any native or 3rd party APIs.<p>The purpose of this project is to be a toolbox for vocal computing. It provides high-level abstractions for dealing with speech-to-text, text-to-text and text-to-speech tasks. The tools remain decoupled from underlying AI models allowing for quick and easy upgrades when new technology is realeased. The main demo for this project is a J.A.R.V.I.S-like assistant however this is meant to be used for a wide variety of use cases.<p>In the coming months I plan to continue to build (hopefully with some of you) on top of this project in order to refine the abstraction level and better understand the kinds of tools required. I hope to build a community of like-minded individuals who want to see J.A.R.V.I.S finally come to life! If you are interested in vocal computing come join the Discord server and build with us! Hope to see you there :)<p>Video demo: <a href="https://youtu.be/xqEQSw2Wq54" rel="nofollow noreferrer">https://youtu.be/xqEQSw2Wq54</a><p>[1] whisper.cpp: <a href="https://github.com/ggerganov/whisper.cpp">https://github.com/ggerganov/whisper.cpp</a><p>[2] Coqui TTS: <a href="https://github.com/coqui-ai/TTS">https://github.com/coqui-ai/TTS</a><p>[3] OpenAI: <a href="https://openai.com/" rel="nofollow noreferrer">https://openai.com/</a><p>[4] llama.cpp: <a href="https://github.com/ggerganov/llama.cpp">https://github.com/ggerganov/llama.cpp</a>
Show HN: Project S.A.T.U.R.D.A.Y. – open-source, self hosted, J.A.R.V.I.S.
Welcome to Project S.A.T.U.R.D.A.Y. This is a project that allows anyone to easily build their own self-hosted J.A.R.V.I.S-like voice assistant. In my mind vocal computing is the future of human-computer interaction and by open sourcing this code I hope to expedite us on that path.<p>I have had a blast working on this so far and I'm excited to continue to build with it. It uses whisper.cpp [1], Coqui TTS [2] and OpenAI [3] to do speech-to-text, text-to-text and text-to-speech inference all 100% locally (except for text-to-text). In the future I plan to swap out OpenAI for llama.cpp [4]. It is built on top of WebRTC as the media transmission layer which will allow this technology to be deployed anywhere as it does not rely on any native or 3rd party APIs.<p>The purpose of this project is to be a toolbox for vocal computing. It provides high-level abstractions for dealing with speech-to-text, text-to-text and text-to-speech tasks. The tools remain decoupled from underlying AI models allowing for quick and easy upgrades when new technology is realeased. The main demo for this project is a J.A.R.V.I.S-like assistant however this is meant to be used for a wide variety of use cases.<p>In the coming months I plan to continue to build (hopefully with some of you) on top of this project in order to refine the abstraction level and better understand the kinds of tools required. I hope to build a community of like-minded individuals who want to see J.A.R.V.I.S finally come to life! If you are interested in vocal computing come join the Discord server and build with us! Hope to see you there :)<p>Video demo: <a href="https://youtu.be/xqEQSw2Wq54" rel="nofollow noreferrer">https://youtu.be/xqEQSw2Wq54</a><p>[1] whisper.cpp: <a href="https://github.com/ggerganov/whisper.cpp">https://github.com/ggerganov/whisper.cpp</a><p>[2] Coqui TTS: <a href="https://github.com/coqui-ai/TTS">https://github.com/coqui-ai/TTS</a><p>[3] OpenAI: <a href="https://openai.com/" rel="nofollow noreferrer">https://openai.com/</a><p>[4] llama.cpp: <a href="https://github.com/ggerganov/llama.cpp">https://github.com/ggerganov/llama.cpp</a>
Show HN: Project S.A.T.U.R.D.A.Y. – open-source, self hosted, J.A.R.V.I.S.
Welcome to Project S.A.T.U.R.D.A.Y. This is a project that allows anyone to easily build their own self-hosted J.A.R.V.I.S-like voice assistant. In my mind vocal computing is the future of human-computer interaction and by open sourcing this code I hope to expedite us on that path.<p>I have had a blast working on this so far and I'm excited to continue to build with it. It uses whisper.cpp [1], Coqui TTS [2] and OpenAI [3] to do speech-to-text, text-to-text and text-to-speech inference all 100% locally (except for text-to-text). In the future I plan to swap out OpenAI for llama.cpp [4]. It is built on top of WebRTC as the media transmission layer which will allow this technology to be deployed anywhere as it does not rely on any native or 3rd party APIs.<p>The purpose of this project is to be a toolbox for vocal computing. It provides high-level abstractions for dealing with speech-to-text, text-to-text and text-to-speech tasks. The tools remain decoupled from underlying AI models allowing for quick and easy upgrades when new technology is realeased. The main demo for this project is a J.A.R.V.I.S-like assistant however this is meant to be used for a wide variety of use cases.<p>In the coming months I plan to continue to build (hopefully with some of you) on top of this project in order to refine the abstraction level and better understand the kinds of tools required. I hope to build a community of like-minded individuals who want to see J.A.R.V.I.S finally come to life! If you are interested in vocal computing come join the Discord server and build with us! Hope to see you there :)<p>Video demo: <a href="https://youtu.be/xqEQSw2Wq54" rel="nofollow noreferrer">https://youtu.be/xqEQSw2Wq54</a><p>[1] whisper.cpp: <a href="https://github.com/ggerganov/whisper.cpp">https://github.com/ggerganov/whisper.cpp</a><p>[2] Coqui TTS: <a href="https://github.com/coqui-ai/TTS">https://github.com/coqui-ai/TTS</a><p>[3] OpenAI: <a href="https://openai.com/" rel="nofollow noreferrer">https://openai.com/</a><p>[4] llama.cpp: <a href="https://github.com/ggerganov/llama.cpp">https://github.com/ggerganov/llama.cpp</a>
Show HN: Script – A text editor for digitally interconnected documents
script is a text editor powering truly digital documents recently launched. Feel free to play with and share your feedback.
Show HN: Script – A text editor for digitally interconnected documents
script is a text editor powering truly digital documents recently launched. Feel free to play with and share your feedback.