SwimStreams and More: The Best New Swim.ai Podcasts
by Swim.ai Team, on Oct 2, 2019 6:55:00 AM
Podcasts are one of our favorite ways to stay up to date with the latest innovations and hear deep dives from technology innovators. If you want technical context, industry trends, and analysis of recent news, then there’s nothing better than a good podcast. This year, Swim.ai even started our own SwimStreams podcast, hosted by cloud thought leader and innovator Krishnan Subramanian.
Top 5 Recent Swim.ai Podcasts
If you haven’t already had a chance to listen, here are four FIVE! insightful podcasts which feature discussion about our new DataFabric product, our open source swimOS platform and how it all fits into the technology landscape:
- SwimStreams Podcast Ep. 3 - “The World Needs a Distributed Operating System” featuring Chris Sachs, co-founder & Chief Architect, Swim.ai
“In this episode we chat with Chris Sachs, Co-Founder and Chief Architect of Swim.ai on how the modern web has evolved from a web of stateless documents served up by REST API. For today's web with streaming data you need a distributed operating system with a different protocol to access the data. Chris makes a case for why Distributed Operating System is essential and how REST cannot meet the demands of today's web.”
- The Internet of Things Podcast Ep. 236 - "Yes, I want Amazon Alexa eyeglasses" featuring Simon Crosby, CTO, Swim.ai
"Our guest this week is Simon Crosby, the CTO of Swim.ai, a company that provides machine learning at the edge for a variety of use cases. Crosby explains how Swim.ai works and then digs into the challenges the company has faced in trying to find a business model that works. His example of parsing through 60 terabytes of data a day from traffic lights only to sell the resulting insights for a quarter per intersection is pretty tough. He does offer hope in the form of new tech developments that we also talk about on the show."
- Big Data Beard Podcast - “Analyze, Act THEN Store: How Swim.ai is changing data processing” featuring Simon Crosby, CTO, Swim.ai
“Data processing today is based on a “Store then Analyze” architecture born in the big-data era. Cory and Brett sit down with Swim.ai CTO Simon Crosby to hear about their recently launched DataFabric software is changing how organizations can stream, analyze and store data. Announced on September 18th, DataFabric software lets businesses interconnect all data-generating assets and provides real-time data classification, reduction, analysis and prediction. Simon talks about how this technology allows for an Analyze, Act and then Store architecture rather than the traditional Store then Analyze architectures that are most common. Simon also talks about Swim.ai’s partnership with Microsoft Azure and its integration into the Azure suite of Data Analytics and AI tools.”
- Data Engineering Podcast Ep. 98 - “Navigating Boundless Data Streams With The SwimOS Kernel” featuring Simon Crosby, CTO, Swim.ai
“The conventional approach to analytics involves collecting large amounts of data that can be cleaned, followed by a separate step for analysis and interpretation. Unfortunately this strategy is not viable for handling real-time, real-world use cases such as traffic management or supply chain logistics. In this episode Simon Crosby, CTO of Swim.ai Inc., explains how the SwimOS kernel and the enterprise data fabric built on top of it enable brand new use cases for instant insights. This was an eye opening conversation about how stateful computation of data streams from edge devices can reduce cost and complexity as compared to batch oriented workflows.”
- SwimStreams Ep. 4 - “Discussing Serverless, DataFabric and What Comes Next” featuring Simon Crosby, CTO, Swim.ai
“In this episode of the SwimStreams Podcast, we talk to Simon Crosby, CTO of Swim.ai, on Serverless, how SwimOS fits into Serverless and how Swim can enable modern data architectures with cloud, IoT and Edge.”
Let us know what you're building using the open source swimOS platform. You can get started with swimOS here and make sure to STAR us on GitHub.