With Azure ML Pipelines, all the steps involved in the data scientist’s lifecycle can be stitched together in a single pipeline improving inner-loop agility, collaboration, and reuse of data and code, while maintaining high reliability.

This video explores Azure Machine Learning Pipelines, the end-to-end job orchestrator optimized for machine learning workloads.

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Professor Andrea Morello, Professor of Quantum Engineering at University of New South Wales, takes us on a journey through the inner workings of a quantum computer.

He gives an accessible introduction to the physical principles that underpin quantum information, and highlights the differences and similarities between classical and quantum processors.

Professor Andrea Morello, Professor of Quantum Engineering at University of New South Wales, takes us on a journey through the inner workings of a quantum computer. He gives an accessible introduction to the physical principles that underpin quantum information, and highlights the differences and similarities between classical and quantum processors.

Microsoft Research features a talk by Wei Wen on Efficient and Scalable Deep Learning (slides)

In deep learning, researchers keep gaining higher performance by using larger models. However, there are two obstacles blocking the community to build larger models: (1) training larger models is more time-consuming, which slows down model design exploration, and (2) inference of larger models is also slow, which disables their deployment to computation constrained applications. In this talk, I will introduce some of our efforts to remove those obstacles. On the training side, we propose TernGrad to reduce communication bottleneck to scale up distributed deep learning; on the inference side, we propose structurally sparse neural networks to remove redundant neural components for faster inference. At the end, I will very briefly introduce (1) my recent efforts to accelerate AutoML, and (2) future work to utilize my research to overcome scaling issues in Natural Language Processing.

See more on this talk at Microsoft Research:
https://www.microsoft.com/en-us/research/video/efficient-and-scalable-deep-learning/

CNBC got a first look inside Lyft’s level 5 lab, where it builds self-driving cars that are being tested on roads now.

Self-driving rides are also available to select Lyft passengers in Arizona and Las Vegas, where Lyft opened its app to autonomous vehicle companies Waymo and Aptiv.

Lyft says it’s completed more than 75,000 self-driving rides.

Watch the video to see how the program works.

Andy walks around the PASS Summit 2019 expo floor and bumps into his favorite editor to brainstorm some new book ideas.

This is part of our on going coverage of PASS 2019 Summit.

Let us know in the comments how we’re doing and what you’d like to see.

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Microsoft Research posted this video about Project Silica, a research project that was highlighted earlier this week at Ignite 2019.

Data that needs to be stored long-term is growing exponentially. Existing storage technologies have a limited lifetime, and regular data migration is needed, resulting in high cost. Project Silica designs a long-term storage system specifically for the cloud, using quartz glass.

Read the blog at https://aka.ms/AA6faho
Learn more about the project at https://www.microsoft.com/en-us/research/video/project-silica-storing-data-in-glass/