Scaling Enterprise ML in 2020: Still Hard with Sushil Thomas

EPISODE 429

November 19, 2020

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About this Episode

Today we're joined by Sushil Thomas, VP of Engineering for Machine Learning at Cloudera. Over the summer, I had the pleasure of hosting Sushil and a handful of business leaders across industries at the Cloudera Virtual Roundtable. In this conversation with Sushil, we recap the roundtable, exploring some of the topics discussed and insights gained from those conversations. Sushil gives us a look at how COVID19 has impacted business throughout the year, and how the pandemic is shaping enterprise decision making moving forward. We also discuss some of the key trends he's seeing as organizations try to scale their machine learning and AI efforts, including understanding best practices, and learning how to hybridize the engineering side of ML with the scientific exploration of the tasks. Finally, we explore if organizational models like hub vs centralized are still organization-specific or if that's changed in recent years, as well as how to get and retain good ML talent with giant companies like Google and Microsoft looming large.

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Thanks to our sponsor Cloudera

Cloudera's Hybrid Data Platform offers a single, unified platform to power data and machine learning workflows across any private, public, multi, or hybrid-cloud deployment. CDP Machine Learning helps organizations build, deploy, and scale ML and AI applications through a repeatable, industrialized approach that streamlines the process of getting analytic workloads into production and intelligently manages machine learning use cases across the business, at scale. CDP Machine Learning lets enterprise data science teams collaborate across the full data lifecycle–with immediate access to enterprise data pipelines, scalable compute resources, and their preferred tools–without compromising the agility, security, and governance needs of the business.

To learn more about what the company is up to and how they can help, visit Cloudera’s Machine Learning resource center at cloudera.com/ml!