Sushil Thomas's guest appearances

Sushil Thomas

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Designing Enterprise Platforms

Andrew Peterson

Meredith Broussard

Ilias Diakonikolas

Scott Clark

Celeste Kidd

Dennis Mortensen

Rob Walker

Sanmi Koyejo

Chelsea Finn

Dario Amodei

Jianxiong Xiao

Kate Darling

Jason Holmberg

Lotte Bransen

Christopher Berner

OwlTail

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. The complete show notes for this episode can be found at https://twimlai.com/go/429.

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. The complete show notes for this episode can be found at <a href="https://twimlai.com/go/429" rel="nofollow" target="_blank">https://twimlai.com/go/429</a>.

Scaling Enterprise ML in 2020: Still Hard! with Sushil Thomas - #429

In this edition of the Early Adopter Research Podcast, Dan Woods spoke with Sushil Thomas, co-founder and CEO of Arcadia Data, while both were at Strata NYC. Woods has written about how Arcadia Data's platform is attempting to save the data lake (link: https://www.arcadiadata.com/blog/the-best-ways-to-get-value-from-data-lakes/; link: https://www.forbes.com/sites/danwoods/2018/08/02/the-path-to-repeatable-ai-success-why-data-fabrics-are-the-next-step/#4a8f1a17313f) by making it more actionable and useful for companies -- and not just a place to store all one's data. He and Thomas discussed Arcadia Data's new release of search-based BI and how that will allow analysts to bypass IT to get the IT data they need.Other topics covered in this episode include:&lt;) The flexibility of the Arcadia Data search-based BI interface&lt;) Using AI to improve how search-based BI operates&lt;) The problems of accessing data and harnessing big data&lt;) Arcadia Data's data native approach&lt;) The best ways to operationalize your data

In this edition of the Early Adopter Research Podcast, Dan Woods spoke with Sushil Thomas, co-founder and CEO of Arcadia Data, while both were at Strata NYC. Woods has written about how Arcadia Data's platform is attempting to save the data lake (link: <a href="https://www.arcadiadata.com/blog/the-best-ways-to-get-value-from-data-lakes/;" rel="nofollow" target="_blank">https://www.arcadiadata.com/blog/the-best-ways-to-get-value-from-data-lakes/;</a> link: <a href="https://www.forbes.com/sites/danwoods/2018/08/02/the-path-to-repeatable-ai-success-why-data-fabrics-are-the-next-step/#4a8f1a17313f" rel="nofollow" target="_blank">https://www.forbes.com/sites/danwoods/2018/08/02/the-path-to-repeatable-ai-success-why-data-fabrics-are-the-next-step/#4a8f1a17313f</a>) by making it more actionable and useful for companies -- and not just a place to store all one's data. He and Thomas discussed Arcadia Data's new release of search-based BI and how that will allow analysts to bypass IT to get the IT data they need. Other topics covered in this episode include: &lt;) The flexibility of the Arcadia Data search-based BI interface &lt;) Using AI to improve how search-based BI operates &lt;) The problems of accessing data and harnessing big data &lt;) Arcadia Data's data native approach &lt;) The best ways to operationalize your data

EAR Podcast - Data Native Analytics - ArcadiaData - Sushil Thomas 2018 - 09 - 12