As a content creator, I appreciate tools that quickly and easily make me able to generate content. Throw AI and computer vision into the mix, then I’m all in.

Here’s a cool tool that will radically transform animation.

Pose Animator basically animates users’ poses and movements from either a camera feed or a static image, and can run on browsers in real-time using TensorFlow.js. The generated animation characters can be customized by downloading and making changes on the provided sample skeleton SVG.

Julia Jaskólska, who draws for social media management company Buffer, recently used Pose Animator to animate one of her character illustrations dancing to the 2014 hit song Uptown Funk by Bruno Mars. “I’d never guess it could be so easy! Thanks @yemount for making our weekend!” tweeted Jaskólska.

In the first part of this two-part video segment, Rohit Nayak explains what Private Endpoint for Azure SQL Database is and how it relates to the overall connectivity story for Azure SQL.

You can learn more about Private Link in Azure SQL Database here https://docs.microsoft.com/en-us/azure/sql-database/sql-database-private-endpoint-overview?WT.mc_id=dataexposed-c9-niner , and Private Link generally for Azure here https://docs.microsoft.com/en-us/azure/private-link/private-endpoint-overview?WT.mc_id=dataexposed-c9-niner.

At the beginning, Rohit mentions a playlist with other videos you should review to get more background on the topic. You can see the playlist here: https://www.youtube.com/playlist?list=PL3EZ3A8mHh0xtbf4Cr2yR4-xsUtELwPjw?WT.mc_id=dataexposed-c9-niner

Time Index

  • [00:46] Connectivity architecture for public endpoint
  • [01:46] Private Link overview
  • [03:55] Why Private Link?
  • [05:08] How does Private Endpoint work?
  • [06:55] Client connectivity scenarios to Private Endpoint
  • [09:05] Summary and what’s next

Astrophysicists have developed an AI to help scientists automatically detect and describe galaxies observed by telescopes surveying the distant sky.

The program, known as Morpheus, was built over a two-year period by a computer scientist and an astrophysicist at the University of California, Santa Cruz.

Morpheus employs a range of computer vision algorithms, including a neural network, that segments objects in the image from the empty background of space, and analyses each detected galaxy pixel-by-pixel to classify its type, whether it’s disk, spheroidal, or irregular shaped. The goal is to trawl through petabytes of images, picking out faraway systems, far faster than humans can.

From navigating to a new place to picking out new music, AI backed algorithms have laid the foundation for much of modern life.

In this article, get a higher-level view of Google’s TensorFlow deep learning framework, with the ultimate goal of helping you to understand and build your own deep learning algorithms from scratch.

Over the past couple of decades, deep learning has evolved rapidly, leading to massive disruption in a range of industries and organizations. The term was coined in 1943 when Warren McCulloch and Walter Pitts created a computer model based on neural networks of a human brain, creating the first artificial neural networks (or ANNs). Deep learning now denotes a branch of machine learning that deploys data-centric algorithms in real-time.