How a rocket scientist turned entrepreneur created the "ChatGPT for Earth data" using transformers and satellite imagery.

Bruno Sánchez is a rocket scientist with a somewhat deviant trajectory. An astrophysicist by training, he used the tools of his trade - mathematics and science - at the broadest possible scale: the universe. At some point, however, his focus switched to using those same tools for more down to earth goals.

Sánchez had a stint at the World Bank, where as a member of interdisciplinary teams he helped make sense of geospatial data. Then he realized the core of what he was doing was mapping, which prompted him to launch a company called Mapbox, providing online maps on the web.

This experience brought another realization for Sánchez - that we have so much data about Earth that we don't really know how to use it: "We know what are the trees in the world. We know what are the forests in the world. It's just a matter of processing [data] properly", as he put it.

So when he got the opportunity to attempt to put all of that together in the same data center and in one workbench, he went for it. That was the Planetary Computer project at Microsoft, and Sánchez loved it. Then, ChatGPT happened.

Sánchez noted that the T in ChatGPT - the transformer - was an architecture that seemed to work great for modalities such as text, images, and audio, but no one seemed to be using it for earth data. So he decided to give it a try. He built a team, raised funds, created a non-profit, and built an open source model using open data. And this is how Clay was born.

Read the article published on Orchestrate all the Things here: https://linkeddataorchestration.com/2025/06/11/building-ai-for-earth-with-clay-the-intelligence-platform-transforming-geospatial-data-analysis/

In business, they say it takes ten years to become an overnight success. In technology, they say it takes ten years to build a file system. ScyllaDB is in the technology business, offering a distributed NoSQL database that is monstrously fast and scalable. It turns out that it also takes ten years or more to build a successful database.

This is something that Felipe Mendes and Guilherme Nogueira know well. Mendes and Nogueira are Technical Directors at ScyllaDB, working directly on the product as well as consulting clients. Recently, they presented some of the things they've been working on at ScyllaDB's Monster Scale Summit, and they shared their insights in an exclusive fireside chat.

This episode is sponsored by ScyllaDB. Read the article published on ScyllaDB's blog here: https://www.scylladb.com/2025/05/05/from-raw-performance-to-price-performance/

#NoSQL #Database #DatabaseEvolution #RaftProtocol #Cloud #DataConsistency #DatabaseScaling #TechInnovation #Opensource

As enterprise systems shift from deterministic software to probabilistic AI, forward-thinking organizations leverage proactive quality assessment to maximize value, minimize risk and ensure regulatory compliance

In today's rapidly evolving technological landscape, ensuring the quality of both traditional software and AI systems has become more critical than ever. Organizations are increasingly relying on complex digital systems to drive innovation and maintain competitive advantage, yet many struggle to effectively evaluate these systems before, during, and after deployment.

Yiannis Kanellopoulos is on the forefront of software and AI system quality assessment. He is the founder and CEO of code4thought, a startup specializing in assessing large-scale software systems and AI applications.

We connected to explore the challenges and opportunities of quality assessment and share insights both for developers and for people responsible for technology decisions within their organizations.

Read the article published on Orchestrate all the Things here: https://linkeddataorchestration.com/2025/04/09/the-quality-imperative-why-leading-organizations-proactively-evaluate-software-and-ai-systems-and-how-you-can-too/