.NET Rocks!

AI Panel from DevIntersection Europe!

Episode #1483 Tuesday, October 10, 2017

What's up with Artificial Intelligence - and why should we care? While at DevIntersection in Stockholm, Carl and Richard hosted a panel discussion with Seth Juarez, Jessica Engstrom and Tess Ferrandez to explore the current AI craze. Each of the panelists discuss the technologies they've been working with for years that now fall into the banner of AI - whether that be machine learning, speech and visual recognition, even chatbots today are part of the AI story. As much branding as product, AI seems to be coming true, have you looked at the latest?

Guests:

Tess Ferrandez

Tess is a developer evangelist at Microsoft and her job is to inspire developers and help them use the Microsoft products to their full potential. Right now the focus is on Windows Phone, Kinect, HTML5 and web apps, and she has a long history as a ASP.net developer and debugger. She runs a popular blog about debugging and development at http://blogs.msdn.com/Tess and you can reach her through the twitter handle @tessferrandez.

Jessica Engstrom

Being a geek shows in all parts of her life, whether it be organizing hackathons, running a user group and a podcast with her husband, game nights (retro or VR/MR) with friends, just catching the latest superhero movie or speaking internationally at conferences. Her favorite topics are UX/UI, Mixed reality and other futuristic tech. She’s a Windows Development MVP. Together with her husband she runs a company called ”Azm dev” which is focused on HoloLens, Windows development, UX and teaching the same.

Seth Juarez

Seth Juarez holds a Master’s Degree in Computer Science where his field of research was Artificial Intelligence, specifically in the realm of Machine Learning. Seth is an Evangelist for Microsoft and devotes the majority of his time making videos for Channel 9. When he is not working in that area, Seth devotes his time to an open source Machine Learning Library, specifically for .NET, intended to simplify the use of popular machine learning models, as well as complex statistics and linear algebra.

Links:

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