Tom MacWright
@macwright.com
2 months ago priestdaddy might not be your speed but it's one of my favorite books ever en.wikipedia.org/wiki/Priestd...
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priestdaddy might not be your speed but it's one of my favorite books ever en.wikipedia.org/wiki/Priestd...
how do you explain this gap in your open source side projects / sorry that's when i was apalled about the world and annoyed with llms and spending hours using a sewing machine in the evenings
๐ We just published a technical deep dive into MCP servers, based on how we built our own.
We cover:
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Tradeoffs between local & remote MCP servers
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Using the `modelcontextprotocol/sdk` package
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How we enabled LLMs to create DBs and run migrations
pris.ly/mcp-deep-dive
4/ The Earthmover team is proud to play a leading role in the Zarr project as this community grows.
Read about our takeaways from CNG here: earthmover.io/blog/zarr-ta...
3/ As we navigate a future increasingly reliant on massive volumes of EO data, Zarr is poised to become a cornerstone of the cloud-native geospatial ecosystem, unlocking new frontiers for scientific discovery and operational applications.
2/ @zarr.dev โs use cases are broadening beyond level 3+ data to include level 1 and 2 EO applications. Major players like @copernicusecmwf.bsky.social (Sentinel 1/2/3), USGS (Landsat), GEE, and ESRI ArcGIS are all integrating Zarr, making PBs of EO data cloud-ready and analysis-friendly.
1/ Our team just got back from an inspiring week at the @cloudnativegeo.org conference in Snowbird, Utah, and one thing is clear:ย ๐๐๐ซ๐ซ ๐๐๐จ๐ฉ๐ญ๐ข๐จ๐ง ๐ข๐ฌ ๐ฌ๐ฎ๐ซ๐ ๐ข๐ง๐ ๐๐๐ซ๐จ๐ฌ๐ฌ ๐ ๐๐จ๐ฌ๐ฉ๐๐ญ๐ข๐๐ฅ.
4/ The Earthmover team is proud to play a leading role in the Zarr project as this community grows.
Read more about our takeaways from CNG here: earthmover.io/blog/meet-th...
3/ As we navigate a future increasingly reliant on massive volumes of EO data, Zarr is poised to become a cornerstone of the cloud-native geospatial ecosystem, unlocking new frontiers for scientific discovery and operational applications.
2/ @zarr.devโs use cases are broadening beyond level 3+ data to include level 1 and 2 EO applications. Major players like @copernicusecmwf.bsky.social (Sentinel 1/2/3), USGS (Landsat), GEE, and ESRI ArcGIS are all integrating Zarr, making PBs of EO data cloud-ready and analysis-friendly.
i'm not the right person to write an article about how ai training datasets are analogous to henry george's concept of 'land' and the profit generated by proprietary models built on stolen datasets are 'economic rents' but someone has to do it
got my first "make this a thing for llms" issue filed on one of my github repos, start of an era probably
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