This video posted by Microsoft has an interesting look at the challenges holding companies back from digital transformation in the cloud era.

What if we could store data in such a way that we never had to worry about quality loss or degradation? Microsoft Partner Deputy Lab Director Ant Rowstron shares his thoughts on redesigning the datacenter for a cloud-centric world. An ordinary piece of glass could have an extraordinary impact on the ways in which we store data and preserve collective memories. Using silica glass presents an energy efficient, sustainable and nearly indestructible method of data storage that could change the way we preserve our history, movies and music and more.

Discover more about this story at Microsoft Innovation: http://msft.social/b1iM95

Julie Lerman shares some insight and great tips for working with Entity Framework in Docker. You will see thing tips for working with the SQL Server Docker image, using environment variables for passports, using the Docker tools for Visual Studio and so much more!

Useful Links

Wall Street Journal explores the future of satellite internet.

The most reliable streaming providers have typically used cable to deliver content. But that’s all changing with the launch of new and better satellites that could one day give us 5G, low latency data. The Wall Street Journal speaks with the chief of the International Bureau at the FCC to discover how those changes are happening almost overnight.

Here’s an interesting article on how to represent a categorical feature, with 100’s of levels, in a model in R.

In this post, we will discuss using an embedding matrix as an alternative to using one-hot encoded categorical features for in modeling. We usually find references to embedding matrices in natural language processing applications but they may also be used on tabular data. An embedding matrix replaces the spares one-hot encoded matrix with an array of vectors where each vector represents some level of the feature. Using an embedding matrix can greatly reduce the memory needed to handle the categorical features.

AI may get all the headlines, but it is impossible to create good algorithms without data, lots and lots of data.

Here’s a thought provoking piece on the three critical components of AI.

Guess which one is the most important?

AI is leaping all around us everywhere we look, both in areas that border on science fiction, like self-driving cars to the more ordinary tasks like what show should I watch on Netflix/Amazon. AI is continuing to have an enormous influence on almost every walk of life, from businesses to civilization.

Siraj Raval explores generative modeling technology.

This innovation is changing the face of the Internet as you read this. It’s now possible to design automated systems that can write novels, act as talking heads in videos, and compose music.

In this episode, Siraj explains how generative modeling works by demoing 3 examples that you can try yourself in your web browser.