Feed aggregator

I posted v1 of this app here and got great feedbacks (SSH port forwarding).

Since then I added a 2nd part I now use a lot too: remote file browsing and markdown preview, without scp or a mount.

When codex/claude prints a path to file, i can now paste it into the menu bar, and the markdown/images just renders.

Comments URL: https://news.ycombinator.com/item?id=49064490

Points: 1

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Article URL: https://portaudio.com/

Comments URL: https://news.ycombinator.com/item?id=49064462

Points: 1

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Article URL: https://newcriterion.com/dispatch/the-art-of-ham-radio/

Comments URL: https://news.ycombinator.com/item?id=49064426

Points: 2

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Article URL: https://pmc.ncbi.nlm.nih.gov/articles/PMC4318286/

Comments URL: https://news.ycombinator.com/item?id=49064422

Points: 2

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Article URL: https://lea.verou.me/blog/2020/05/todays-javascript-from-an-outsiders-perspective/

Comments URL: https://news.ycombinator.com/item?id=49064421

Points: 2

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Article URL: https://www.weather.gov/media/owlie/SGJune6-11(1).pdf

Comments URL: https://news.ycombinator.com/item?id=49064414

Points: 2

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Article URL: https://xinfer.ai/home/md/the-model-writes-the-judge-measures

Comments URL: https://news.ycombinator.com/item?id=49064396

Points: 1

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Article URL: https://www.theguardian.com/us-news/2026/jul/26/new-jersey-surveillance-pricing-ban

Comments URL: https://news.ycombinator.com/item?id=49064392

Points: 6

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Article URL: https://gizmodo.com/a-feature-that-makes-your-phone-data-self-destruct-in-authorities-hands-may-soon-have-its-day-in-court-2000790831

Comments URL: https://news.ycombinator.com/item?id=49063853

Points: 2

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Structured data could be the next big frontier for foundation models.

RelativeDB is an open source query engine built around the Relational Transformer architecture, developed by Stanford’s Tabular and Relational (STAR) Project. These models can adapt to new databases and prediction tasks using relatively little labeled context.

With some of my experiments, the results have been remarkable. On some tasks, RelativeDB can outperform XGBoost with only a small amount of relational context and no manual feature engineering.

So RelativeDB turns relational foundation models into something you can query (like this customer churn query):

``` PREDICT NOT EXISTS(orders.*) OVER (90 DAYS FOLLOWING) FROM customers ```

The engine finds the relevant context across the related tables and returns a prediction. The goal is to make questions like churn, demand forecasting, fraud detection, and recommendations feel more like database queries than bespoke ML projects.

Longer term, I think the optimizer should be able to choose between relational foundation models, fine-tuned models, and conventional approaches such as XGBoost depending on the query (how much graph-like context is needed vs just tabular features). Bridging ML to LLMs in a sane way.

I think there are markets for quantitive finance and utilizing emerging context graphs.

The project is early, and I would especially appreciate feedback on the query language and execution model.

RelativeDB: https://github.com/RelativeDB/RelQL Stanford RT-J: https://star-project.stanford.edu/rt-j/

Comments URL: https://news.ycombinator.com/item?id=49063842

Points: 2

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Article URL: https://medium.com/westenberg/the-indie-hacker-economy-is-a-pyramid-scheme-d06cb5789648

Comments URL: https://news.ycombinator.com/item?id=49063832

Points: 2

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Article URL: https://newsletter.platypuseconomics.com/p/i-championed-prediction-markets-look

Comments URL: https://news.ycombinator.com/item?id=49063789

Points: 2

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Article URL: https://blog.getutm.app/2026/introducing-triton-directx-11-driver-for-qemu/

Comments URL: https://news.ycombinator.com/item?id=49063767

Points: 1

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Hi HN community,

As a busy techie with kids and other family obligations and my recent health diagnosis, I wanted an efficient way to integrate workouts in my daily routine and my research indicated that HIIT/Tabata style routines fit that requirement much better than a dedicated long running/planned workout routine.

I made a simple PWA to help me with that endeavor that I have found useful and hoping some of you may like it as well. No sign ups needed but you can sign in if you'd like to save custom presets and history/progress. You may also enjoy some of the fitness guides/blog posts that I am put together to help someone get started more easily. Built using javascript, vite and firebase.

Feedback is most welcome, both via the app/email or comments here.

Comments URL: https://news.ycombinator.com/item?id=49063766

Points: 1

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Article URL: https://atmos-atelier.de/en/atmos-uhr/

Comments URL: https://news.ycombinator.com/item?id=49063757

Points: 1

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Article URL: https://nikolays.github.io/PGSimCity/

Comments URL: https://news.ycombinator.com/item?id=49063754

Points: 2

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Article URL: https://github.com/orca-gamedev/img2blockbench

Comments URL: https://news.ycombinator.com/item?id=49063753

Points: 1

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Article URL: https://github.com/Schummlerr/steam-dlc-protection-sdk-

Comments URL: https://news.ycombinator.com/item?id=49063747

Points: 1

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Article URL: https://proofsandintuitions.net/2026/06/24/liveness-proofs-in-veil-part-1/

Comments URL: https://news.ycombinator.com/item?id=49063745

Points: 1

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Article URL: https://github.com/jdyar/discrete-assembly-sim

Comments URL: https://news.ycombinator.com/item?id=49063724

Points: 1

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