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Podcast Season 3

A Look Back at Season 2

Welcome back to another season of Utilizing AI! In this first episode of season 3, we are taking a look at some of the most memorable moments of season 2. 

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Podcast Season 2

Taking Artificial Intelligence on the Road with Christophe Couvreur of Cerence

Most people think AI in vehicles means autonomous driving, but there are a lot of other applications for the technology

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Podcast Season 2

Bringing AI to the Executive Suite with Josh Epstein of AtScale

Businesses have long tried to use data to drive decisions, but over the last few years new big data and AI capabilities have appeared

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Podcast Season 2

How AI Can Help Displaced Workers with Saiph Savage

Although we usually focus on the ways AI can displace workers, this technology can also create new jobs and help them

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Podcast Season 2

Offloading ML Processing to Storage Devices with NGD Systems

Today’s storage devices (disks and SSDs) have processors and memory already, and this is the concept of computational storage

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Podcast Season 2

How the ML Community Has Evolved in 2021 with Demetrios Brinkmann and David Aponte

The MLOps community has grown dramatically recently, with security, a data-centric approach, ethical implications, and a growing and diverse community rising in 2021

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Podcast Season 2

The Global Imbalance of AI Investment with Sofia Trejo

Look at a list of the top companies in the world, and most are focused in the United States, China, and Europe, and this causes an imbalance of investment in AI

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Podcast Season 2

AI Is Going to Be Everywhere and in Everything With David Klee

AI is everywhere these days, powering applications from the enterprise to industrial, medical, education, and mobility

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Podcast Season 2

MLOps Is About Quality Not Technology with Steph Locke

MLOps is similar to DevOps but focused on ML, and focuses on improving quality of delivery for artificial intelligence applications

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Podcast Season 2

Overcoming the Obstacles of AI Application Development with Snorkel AI

Developers of AI applications face many obstacles, but the chief challenge is simply that these are different from traditional software development projects