Show HN: Kurvengefahr – browser CAD/CAM for pen plotters
6 by tibordp | 1 comments on Hacker News.
A few years ago I made a pen plotter attachment for Prusa MK4 ( https://ift.tt/jpZ1G95... ) and at the time I didn't have a good way to turn artwork into G-code for it, and I put the project on ice for a while. I recently wanted to dabble in line art again and made a small browser app to make it easier. As agentic AI tools of 2026 are quite addictive, it rather quickly grew into something quite a bit more - an integrated browser CAD/CAM for pen plotters that covers everything from importing existing artwork, creating artwork from scratch, preparing for plotting and hardware integration. It includes some off-beat features like a Logo interpreter for turtle art and Graves RNN for handwriting synthesis and in addition to 3D printer pretending to be pen plotters it now also supports actual pen plotters based on EBB (AxiDraw) and GRBL firmwares through Web Serial. If you own an AxiDraw or a GRBL plotter, I'd very much appreciate it you gave it a try and give feedback. As I don't own those, I did all the testing with a hardware mock on STM32, so I am not sure how well it works attached to an actual plotter. Source code and docs are on GitHub:
https://ift.tt/B8rkbNG
Minggu, 12 Juli 2026
Free agent Diggs: No WR2 in NFL better than me
Free agent Stefon Diggs says he is better than any No. 2 wide receiver currently on an NFL roster.
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Sabtu, 11 Juli 2026
A's All-Star 1B Kurtz put on IL with thumb sprain
Athletics slugger Nick Kurtz, who was set to start at first base for the American League at next week's All-Star Game, went on the 10-day injured list Saturday with a right thumb sprain.
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Jumat, 10 Juli 2026
New top story on Hacker News: Show HN: Reviving my 2001 college band with AI
Show HN: Reviving my 2001 college band with AI
24 by jacobgraf | 12 comments on Hacker News.
25 years ago, I joined a band called Fading Maize at Ripon College in Wisconsin. We did what we could with what we had. We recorded 3 albums over the next 3 years and played at as many bars and coffee shops as we could. We built a website with Microsoft Frontpage. Then we went our separate ways, got married, had kids, focused on other things. Earlier this year I had the idea to approach the lead singer who wrote all of the lyrics and melodies to the stuff we played back then, and wanted to "reimagine" everything in 2026 using AI. That's the project I want to share here! The site has a before/after player where you can flip between the original dorm-room recording and the 2026 version mid-song without losing your place, so you can hear exactly what changed. The original 2001 website is preserved and browsable at https://ift.tt/L7UMZmg , rough edges intact. Working on this, the thing that sparked in my own mind is that it was an experiment in a certain way to use AI. The songs, lyrics, and arrangements are the original human work (in this case from 2001-2003). We wrote the lyrics, we created the melodies, we played the parts, it just didn't sound as good as we heard it in our own heads. The stuff AI creates is awesome, but it means less if it's just the AI cranking everything out from the ground up. In our case, the AI was only there to help us get the results we originally wanted back in 2001 when we were cooking ramen in our dorm rooms and couldn't afford anything fancy Being fully transparent about our use of AI, sticking tightly to our original lyrics and melodies, but making full use of AI to give us the studio, session players, and production budget we never had seemed like the right balance of concerns. I'm super proud of how it turned out and the transparency we've used along the way. Happy to discuss the audio pipeline, the site (Next.js), or what it's like to A/B your 20-year-old self! p.s. Oh and check this out! I remember this day. Our site was getting absolutely hammered! https://www.youtube.com/watch?v=KPJWlnN9tSE&t=43
24 by jacobgraf | 12 comments on Hacker News.
25 years ago, I joined a band called Fading Maize at Ripon College in Wisconsin. We did what we could with what we had. We recorded 3 albums over the next 3 years and played at as many bars and coffee shops as we could. We built a website with Microsoft Frontpage. Then we went our separate ways, got married, had kids, focused on other things. Earlier this year I had the idea to approach the lead singer who wrote all of the lyrics and melodies to the stuff we played back then, and wanted to "reimagine" everything in 2026 using AI. That's the project I want to share here! The site has a before/after player where you can flip between the original dorm-room recording and the 2026 version mid-song without losing your place, so you can hear exactly what changed. The original 2001 website is preserved and browsable at https://ift.tt/L7UMZmg , rough edges intact. Working on this, the thing that sparked in my own mind is that it was an experiment in a certain way to use AI. The songs, lyrics, and arrangements are the original human work (in this case from 2001-2003). We wrote the lyrics, we created the melodies, we played the parts, it just didn't sound as good as we heard it in our own heads. The stuff AI creates is awesome, but it means less if it's just the AI cranking everything out from the ground up. In our case, the AI was only there to help us get the results we originally wanted back in 2001 when we were cooking ramen in our dorm rooms and couldn't afford anything fancy Being fully transparent about our use of AI, sticking tightly to our original lyrics and melodies, but making full use of AI to give us the studio, session players, and production budget we never had seemed like the right balance of concerns. I'm super proud of how it turned out and the transparency we've used along the way. Happy to discuss the audio pipeline, the site (Next.js), or what it's like to A/B your 20-year-old self! p.s. Oh and check this out! I remember this day. Our site was getting absolutely hammered! https://www.youtube.com/watch?v=KPJWlnN9tSE&t=43
Live NHL free agency tracker: Contract details for...
Get up to speed on all the latest veteran additions teams are making beginning on June 30.
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Kamis, 09 Juli 2026
New top story on Hacker News: Show HN: I mapped 8.5M research papers into an interactive atlas
Show HN: I mapped 8.5M research papers into an interactive atlas
9 by leonickson | 0 comments on Hacker News.
When I read papers, I have to jump between multiple tabs to find the dataset, code, videos, peer reviews, and so on. I tried to fix this with this project. It started as a project just for papers on arXiv, but after its initial success on Twitter (got like 1.9k views: the most I have gotten for a post), I have now expanded it to include other openly available papers from PubMed Central, bioRxiv, medRxiv, and eLife. These papers have been linked with their genes, proteins, diseases, drugs, clinical trials, 3D protein structures, code, and cited and similar papers. This project now has four parts: First, a map. I embedded nearly 8.5M papers (with SPECTER2), ran UMAP for 2D representation, and rendered them as a scatterplot. The dots can be clicked to see brief information about the papers, like an LLM TLDR, key findings, peer reviews, linked entities, and more. The clusters are also labeled, though you might have to zoom in. Second, I built a detailed paper page for each paper. They give you the paper's full text, images, videos, peer reviews (from OpenReview), GitHub links, Hugging Face dataset/model links, clinical trials, genes, diseases, 3D protein structures, cited papers, and similar papers. You can also copy the whole page, including the full paper text and image URLs, as markdown for your LLM. Third, I have released an extension so you can read all this information in your sidebar by clicking "open in Tomesphere" that shows up in arXiv, PMC, bioRxiv, Google Scholar, or medRxiv. I have tried to provide as much information as possible in the extension, though for things like viewing all the images or a 3D protein structure, you might still have to go to the paper page using the link provided in the extension. Fourth, all this data is available for your LLM via MCP. The MCP does have a 50-query free limit (this jumps 10x with signup). Note: this project is still in beta, so papers might have some mismatched information. I am rolling out feedback forms soon to improve the data quality. Thank you so much for taking the time to read this.
9 by leonickson | 0 comments on Hacker News.
When I read papers, I have to jump between multiple tabs to find the dataset, code, videos, peer reviews, and so on. I tried to fix this with this project. It started as a project just for papers on arXiv, but after its initial success on Twitter (got like 1.9k views: the most I have gotten for a post), I have now expanded it to include other openly available papers from PubMed Central, bioRxiv, medRxiv, and eLife. These papers have been linked with their genes, proteins, diseases, drugs, clinical trials, 3D protein structures, code, and cited and similar papers. This project now has four parts: First, a map. I embedded nearly 8.5M papers (with SPECTER2), ran UMAP for 2D representation, and rendered them as a scatterplot. The dots can be clicked to see brief information about the papers, like an LLM TLDR, key findings, peer reviews, linked entities, and more. The clusters are also labeled, though you might have to zoom in. Second, I built a detailed paper page for each paper. They give you the paper's full text, images, videos, peer reviews (from OpenReview), GitHub links, Hugging Face dataset/model links, clinical trials, genes, diseases, 3D protein structures, cited papers, and similar papers. You can also copy the whole page, including the full paper text and image URLs, as markdown for your LLM. Third, I have released an extension so you can read all this information in your sidebar by clicking "open in Tomesphere" that shows up in arXiv, PMC, bioRxiv, Google Scholar, or medRxiv. I have tried to provide as much information as possible in the extension, though for things like viewing all the images or a 3D protein structure, you might still have to go to the paper page using the link provided in the extension. Fourth, all this data is available for your LLM via MCP. The MCP does have a 50-query free limit (this jumps 10x with signup). Note: this project is still in beta, so papers might have some mismatched information. I am rolling out feedback forms soon to improve the data quality. Thank you so much for taking the time to read this.
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