Digital Dirt Update: Using AI/ML to Advance Soil Carbon Sequestration

By Scott Hinson– Pecan Street’s Digital Dirt initiative was designed to accelerate the development of cost-effective ways to predict how land management practices can increase soil organic carbon, a promising climate solution. The next generation of high-tech sensors will surely be part of the solution, but they a still far from being something most producers can use to obtain accurate results. We see significant near-term potential for simulation models to fill this gap.

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Pecan Street’s JupyterHub Can Help Rapidly Scale and Iterate Your Research

By Cavan Merski, data analyst, Pecan Street – To allow better access and more sophisticated analysis of this data, we launched our own Jupyterhub, a multi-user server for Jupyter Notebooks designed to support large-scale analysis by using GPU and memory based on a server rather than a local machine. It also allows multiple users – like groups of students or researchers – to share the same document at the same time.

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Next Level Energy Research Requires Mountains of Data

By Steve Mock – Beyond any one analysis, there’s a bigger reason why we collect so much data. Emerging tools like artificial intelligence and machine learning have the potential to revolutionize how we generate, move, store and use critical resources like electricity and water. But to reach their potential, these tools require mountains of data.

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