May 9, 2019
AI (Artificial Intelligence), ML (Machine Learning) and DL (Deep Learning) are some of the hottest IT buzzwords of our time. If you’re working in tech industry, chances are that you hear or read something about them almost every day. It looks like they are the answer to every question, and the solution to every problem, including wars and global hunger.
AI/ML is used in self-driving cars, but what about self-driving, self-optimising data centers? On the 19th episode of Virtual Stack Podcast, I’m joined by Greg Burk, Senior Staff Architect at VMware, and we discuss about AI, ML, and their use cases in today’s Enterprise IT, especially Self-Driving and Self-Optimizing Data Centers.
Hope you enjoy the show. Feel free to share your feedback via Twitter (@emregirici), LinkedIn or virtualstack.tech.
Show Notes:
- 02:00 - Intro
- 05:10 - What’s AI (Artificial Intelligence), ML (Machine Learning) and DL (Deep Learning)?
- 12:00 - AI/ML is not a new technology, what caused the big increase in popularity in the last 3-4 years?
- 18:00 - Where (use case, vertical, industry) do you expect AI to drive the biggest transformation?
- 26:30 - How do you expect AI/ML primarily serve in the Data Center? For driving the DC autonomously, or only for log crunching and creating insights for the people that are running the DC?
- 35:00 - Is it possible to achieve self-drive and self-optimisation in a HW defined DC, or is SDDC a must?
- 40:00 - What’s VMware’s approach on Self-Driving/Optimizing Data Centers? (a.k.a. Project Magna)
- 52:30 - Closing notes
Links and books: