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News for “distribut”
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Moozonian News
quip.network• Apr 2, 2026• 1 min read
Show HN: Open-source distributed quantum compute networkHey HN. I'm Colton (YC S21, ex-Acorns), one of the founders of Postquant Labs. My cofounder Richard is a cryptographer out of Draper Labs and DARPA. We're building Quip.Network, the first distributed quantum compute network. We just opened our testnet and wanted to share it here.The basic problem: quantum hardware is here and already competitive on certain optimization problems, but for most people, there's no way to access it. The machines cost millions and the hardware and research are gated by the companies who own them.Also, quantum providers regularly have machines sitting idle because demand isn't consistent, and that's a problem because many architectures need to be cooled near absolute zero and can't just be turned off. There's currently no equivalent of spinning up an on-demand cloud instance for quantum compute.So we're building one. Quip.Network is a spot clearinghouse and marketplace where quantum providers contribute excess capacity, developers deploy their best solvers to
Moozonian News
github.com• Mar 31, 2026• 1 min read
Show HN: Dux, distributed DuckDB-backed dataframes on the BeamHey all! I wrote Explorer[1] a good few years ago now with the dream of fast dataframes with a dplyr-like API in a really powerful, ergonomic language (Elixir). It's proved pretty successful. Explorer is used in production at my company, and it's my go-to for quick data analysis.But maintaining it became a true albatross. Polars is an amazing project, but the development process is fast and a lot is very focused on the Python lib. We found that trying to maintain Explorer against Polars was a maintenance nightmare and eventually hit points where we had to give up features and found it extremely difficult to update to the latest.We also tried distributing Explorer and only got so far. A reasonable alternative to Spark was always what I wanted, and I could (tantalisingly, frustratingly) see the pieces there in dataframes and the BEAM, but couldn't make it happen.We also always knew that the right direction was to be 'lazy by default', accumulating ops and only executing when the datafram