Shubha Nabar is a senior director of data science for Salesforce Einstein. Prior to working for Salesforce, she was a data scientist at LinkedIn and Microsoft.  In the podcast she discusses Salesforce Einstein and the problem space that they are trying to solve, explores the differences between enterprise and consumer for machine learning, and then talks about the Optimus Prime Scala library that they use in Salesforce.

Why listen to this podcast:
* The volume of data, and hardware advances have made it possible to do machine learning to do them a lot faster.
* AI is a science of building intelligent software, encompassing many aspects of intelligence that we tend to think of as human.
* If you can’t measure something, you can’t fix it.
* You have to think about what you can automate, rather than having a human to try and engineer out all those features.
* Get feedback on design.

Nora Jones, a senior software engineer on Netflix’ Chaos Team, talks with Wesley Reisz about what Chaos Engineering means today. She covers what it takes to build a practice, how to establish a strategy, defines cost of impact, and covers key technical considerations when leveraging chaos engineering.

Why listen to this podcast:

- Chaos engineering is a discipline where you formulate hypotheses, perform experiments, and evaluate the results afterwards.
- Injecting a bit of failure over time is going to make your system more resilient in the end.
- Start with Tier 2 or non-critical services first, and build up success stories to grow chaos further.
- As systems become more and more distributed, there becomes a higher need for chaos engineering.
- If you’re running your first experiment, get your service owners in a war room and get them to monitor the results of the test as it is running.

More on this: Quick scan our curated show notes on InfoQ http://bit.ly/2vJoimw

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InfoQ Podcast

Shubha Nabar Discusses Einstein, the Machine Learning System in Salesforce

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