The Truth About AI

Status Go Podcast: Episode 1

“Of all of the leaders out there in all of our industries a full 85% don’t get beyond the self authoring stage.” – Ron West

Episode 42: The Truth About AI

Jeff Ton‘s recent Forbes Article, A Skeptic’s Guide to Assessing Artificial Intelligence, was written to cut through some of the hype around Artificial Intelligence and help IT Leaders get a better understanding of the difference between Artificial Intelligence (AI) and Machine Learning (ML).

Joining us on this episode are Ananth Gopalakrishnan and Harsha Gopianandan, Co-Founders of SeyVu (recently acquired by InterVision) authorities in the field of AI and ML, and contributors to the Forbes article. Ananth and Harsha sit down with Jeff to dive a little deeper into demystifying AI: what constitutes true AI, how AI is changing business models, detecting AI washing and much, much more.

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Time Stamped Table of Contents

1:41 The difference between AI and ML

4:45 Training a model

6:55 More data or clean data?

9:00 Use Cases

11:57 Changing the business model

14:12 Detecting AI washing

18:47 Determining if a company is taking the right approach with data

20:02 Defining Deep Learning

21:30 Action Items

Ananth is the co-founder / COO of SeyVu, a machine learning / AI startup. He has been driving deployment of complex and innovative data science solutions across several industries. Ananth has over 20 years’ experience in the semi-conductor industry. Over the past decade, Ananth was responsible for running an innovation lab centered around data driven capabilities in graphics computing. Under his leadership, the team streamlined development of pioneering solutions in design, test, integration and proliferation of semi-conductor products. He’s a proven leader and has managed large cross-functional global teams.

Harsha is the founder / CEO of SeyVu, a machine learning / AI startup. Before SeyVu, Harsha held several leadership roles at leading semiconductor companies like Micron and Intel, managing large global and cross-functional teams. He has 20 years of data science experience with a focus on building predictive models to derive actionable insights that drive tangible business value. In his previous roles, Harsha was responsible for designing and prototyping machine learning algorithms for product optimization. He has extensive experience exploring and analyzing data, which form the foundation for good data science.