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by The digiLab Team

Updated 25 March 2024

digiLab Newsletter: Issue 5

Delivering Workshops for MIT and the Henry Royce Institute, Exploring ML for Fusion, twinLab's autoML Functionality, and our Summer Interns
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Interested in applications of probabilistic ML across fusion and other complex engineering/infrastructure domains? Signup for email updates here!

We've been travelling the globe for the last two weeks, attending the Fusion Industry Association annual policy conference in D.C., and delivering twinLab workshops for MIT, for The Henry Royce Institute / Rolls-Royce, and, nearer to home, for Exeter College.

Introduction to ML for Fusion

There are many potential applications for machine learning, and few are as technically complex as nuclear fusion.

In this first video, plasma physicist and fusion solutions engineer Dr Cyd Cowley explores the applications of machine learning in the development of fusion. These include ongoing applications, as well as potential areas where machine learning could be applied in the future.

Watch the Video

autoML in twinLab - Making Gaussian Processes Easy

Despite its importance, choosing the right kernel to use with a Gaussian Process model can be a difficult task. In addition to the commonly chosen kernel functions, the space of possible kernels become very complicated when including compositional kernels, such as adding or multiplying two kernels together.

In this video, our technical content lead Ana explores the Model Selection feature in twinLab, which automates the process of kernel selection and composition.

Learn More

Announcing our 2024 Summer Interns

We are delighted to introduce the students who will be taking part in digiLab’s 2024 Summer Internship Programme: Joe Rayson, Natalia Wojcik, and Lucas Pigott.

Discover More

Probabilistic ML with twinLab

twinLab is already being used to solve next-generation engineering and sustainability challenges at organisations like the UKAEA, Airbus, and Rolls-Royce. Our vision with twinLab is to help more people and organisations to use probabilistic ML.

Just hit "Try twinLab" at the top-right, 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.

The digiLab Team
We are a 30+ strong team of ML Experts, Software Developers, Solution Engineers, and Product Experts. As a spinout from the University of Exeter, we build on years of cutting-edge academic research. At our core is a commitment to helping engineering and infrastructure companies become data-driven.

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