digiLab Newsletter: Issue 10

Welcome to the latest newsletter. Last week, we had a great time exhibiting at Utilities Week Live, with exciting conversations about applying Machine Learning in order to improve sustainability and reduce costs across gas, electricity, and water networks.

This week, our Fusion Solution Engineer, Ross Allen, attended ITER's first Private Sector Fusion Workshop. And for those who enjoyed Cyd's article about Predicting Magnetic Fusion Performance, we've released his code in a demo notebook, for twinLab users to explore.

To fuel continued growth, we're hiring for multiple roles across Fusion and Nuclear Fission Sales, Solution Engineering, MLOps, and Software Engineering. Find live job descriptions here.

If you know someone who would be interested in applications of probabilistic ML across fusion, materials, and other complex engineering/infrastructure domains, share our signup link!

ITER's Private Sector Fusion Workshop

Ross represented digiLab at the event, and was lucky enough to see ITER's progress up close and in person. He also got a great picture in a hard hat!

Exciting times lie ahead for collaborations between ITER and the private sector, enabling the acceleration of fusion development.

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Exhibiting at Utilities Week Live

We attended the two-day Utilities Week Live conference at the NEC, where a wide variety of large utilities, innovation teams, and smaller innovators were identifying how to improve our networks.

As our Graduate Solution Engineer Joe put it: "Want to optimally place your sensors? We can help! Want to automate system control with confidence? We can help! Want to understand uncertainty in your system? We can help!"

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twinLab Demo Notebook - Predicting Performance for Magnetic Fusion

We've released the code behind Cyd's article which we shared last week, Predicting Performance for Magnetic Fusion with twinLab.

Got a twinLab API key? Try running the demo notebook. Want to run the notebook, but aren't signed up for a trial? Get in touch below.

Explore the Demo

Getting Started with ML using twinLab

Just hit "Try twinLab" on our website, or reply to this email, and we'll set you up with an API key, the documentation, and some example solutions. Alternatively, if you've got a particular data challenge, book a free call with one of our solution engineers.