Today we close out our 2019 NeurIPS series with Mohamed Sidahmed, Machine Learning and Artificial Intelligence R&D Manager at Shell.
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Mohamed and his team submitted a few papers at the conference this year. We briefly touch on their paper Accelerating Least Squares Imaging Using Deep Learning Techniques, which details how researchers can computationally efficiently reconstruct imaging using a deep learning framework approach. We then transition into a discussion on the paper FaciesNet: Machine Learning Applications for Facies Classification in Well Logs, which Mohamed describes as “A novel way of designing a new architecture for how we use sequence modeling and recurrent networks to be able to break out of the benchmark for classifying the different types of rock.” Enjoy!
Thanks to our sponsor!
Thanks to our friends at Shell for their support of the podcast and their sponsorship of the NeurIPS 2019 series.
Shell has been an early adopter of a wide variety of AI technologies to support use cases across retail, trading, new energies, refineries, exploration, and many more, and is doing some really interesting things, but don’t take it from me.
Microsoft CEO Satya Nadella recently noted that “What’s happening at Shell is pretty amazing. They have a very deliberate strategy of using AI, right across their operation… from the drilling operations to safety.”
Last year the company established the Shell.ai Residency Programme, a 2 year, full-time program that allows data scientists and AI engineers to gain experience working on a variety of AI projects across all Shell businesses. If this interests you, I’d encourage you to hit pause and head over to shell.ai to learn more.
Mentioned in the Interview
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“More On That Later” by Lee Rosevere licensed under CC By 4.0