In this Data Point, Andy chats with SentryOne CEO Bob Potter while roaming the expo floor at PASS 2019 Summit.

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.

Live video version of this Data Point is at https://www.facebook.com/DataDrivenTV/videos/2362966150499722/

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In this Data Point, Andy takes you behind the scenes of the PASS 2019 Summit on his way to his presentation.

The livestream of the session Andy’s walking to is at http://franksworld.com/2019/11/06/ssis-devops-and-azure-containers/

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.

Live video version of this Data Point is at https://www.facebook.com/DataDrivenTV/videos/2418536671736052/

Watch all our live videos at https://www.facebook.com/DataDrivenTV

Like us on Facebook to be notified of when we go live.

Press the play button below to listen here or visit the show page at DataDriven.tv.

Nearly a year ago, China’s top AI scientists gathered in Suzhou for the annual Wu Wenjun AI Science and Technology Award ceremony.

Despite that fact that they had every reason to feel good about China’s accomplishments in AI, the mood was rather gloomy.

More than two years after the release of the New Generation Artificial Intelligence Development Plan (AIDP), China’s top AI experts worry that Beijing’s AI push will not live up to the hype.

The concern is not just that China might be in for an “AI winter”—a cyclic downturn in AI funding and interest due to overly zealous expectations. It’s also that for all China’s strides in AI, from multi-billion dollar unicorns to a glitzy state plan, it still lacks a solid, independent base in the field’s foundational technologies.

Separating a song into separate vocals and instruments has always been a headache for producers, DJs, and anyone else who wants to play around with isolated audio.

While there are lots of ways to do it, the process is often be time-consuming and the results are lacking.

However, a new open source AI tool makes this tricky task faster and easier.

The software is called Spleeter and was developed by music streaming service Deezer for research purposes. Yesterday the company released it as an open source package, putting the code up on Github for anyone to download and use.

Amazon’s Alexa Science researchers published a paper providing a theoretical basis for neural-network optimization.

While showing that it is computationally intractable to find a perfect solution, the paper does provide a formulation, the Approximate Architecture Search Problem (a-ASP), that can be solved with genetic algorithms.

In a recent blog post describing the work, research engineer Adrian de Wynter cast the problem of choosing a neural-network architecture as an exercise in function approximation;