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/

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/

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.

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;

In this Data Point, Andy bumps into some familiar faces on the way to the PASS 2019 Welcome Reception where Grant Fritchey kicks off the festivities.

Fun fact: I used to work with Grant Fritchey back in the 90s at a large investment bank on Wall Street.

Small World.

Video version available at: https://www.facebook.com/DataDrivenTV/videos/790212794754980/

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

 

pass2019welcome

Here’s a great collection of Jupyter notebooks that explore all the new features of SQL Server 2019.

Here are some of the ones that caught my attention.

SQL Server 2019 Querying 1 TRILLION rows

  • OneTrillionRowsWarm.ipynb – This notebook shows how SQL Server 2019 reads 9 BILLION rows/second using a 1 trillion row table using a warm cache,
  • OneTrillionRowsCold.ipynb – This notebook shows how SQL Server 2019 performs IO at ~24GB/s using a 1 trillion row table with a cold cache.

Big Data, Machine Learning & Data Virtualization

  • SQL Server Big Data Clusters – Part of our Ground to Cloud workshop. In this lab, you will use notebooks to experiment with SQL Server Big Data Clusters (BDC), and learn how you can use it to implement large-scale data processing and machine learning.
  • Data Virtualization using PolyBase – The notebooks in this SQL Server 2019 workshop cover how to use SQL Server as a hub for data virtualization for sources like OracleSAP HANAAzure CosmosDBSQL Server and Azure SQL Database.
  • Spark with Big Data Clusters – The notebooks in this folder cover the following scenarios:
    • Data Loading – Transforming CSV to Parquet
    • Data Transfer – Spark to SQL using Spark JDBC connector
    • Data Transfer – Spark to SQL using MSSQL Spark connector
    • Configure – Configure a spark session using a notebook
    • Install – Install 3rd party packages
    • Restful-Access – Access Spark in BDC via restful Livy APIs
  • Machine Learning
    • Powerplant Output Prediction – This sample uses the automated machine learning capabilities of the third party H2O package running in Spark in a SQL Server 2019 Big Data Cluster to build a machine learning model that predicts powerplant output.
    • TensorFlow on GPUs in SQL Server 2019 big data cluster – The notebooks in this directory illustrate fitting TensorFlow image classification models using GPU acceleration.

Socratica explores Abstract Algebra.

What is Abstract Algebra?

Abstract Algebra is very different than the algebra most people study in high school. This math subject focuses on abstract structures with names like groups, rings, fields and modules. These structures have applications in many areas of mathematics, and are being used more and more in the sciences, too