The AI in Business Podcast

In October, we're focusing on how non-technical employees can still gain an edge in the era of AI even if they've never learned any code. I can't think of a better guest off the bat than our quest this week: Wijay Wijayakumaran, Chief Architect of Machine Learning and AI at IBM Australia. Wijay emphasizes how much stock he places in the critical importance of subject-matter experts and business leaders with domain knowledge. He also runs through possible career opportunities that non-technical employees can look for in the era of AI and questions they can ask to get more involved with AI projects at their organization.

This is the final episode of our series on the ROI of AI. This week is the monthly analyst call, in which Emerj CEO Daniel Faggella breaks down some of the key themes from this month's interviews. In particular, Daniel puts a large emphasis on connecting the dots between near-term and long-term ROI. A lot of these themes and core questions are discussed and answered for clients of our AI Product Development Roadmap services.

This week, we spoke with David Carmona, the GM of Artificial Intelligence at Microsoft, about his approach to AI ROI with the enterprise clients of Microsoft. The biggest takeaway from this episode comes right at the beginning. David talks about how to think about artificial intelligence ROI in the long-term and the near-term. That is to say, how are we going to see a relatively near-term return with AI that might be able to improve our condition while keeping in mind the longer-term disruption in our industry?

It's clear that there's a revolution in how artificial intelligence is done with neural networks as opposed to the old school systems of the '80s and the '90s. It's clear that hardware is beginning to evolve, and it's also quite clear that the way that we power these hardware systems is going to have to change. GPUs and AI hardware are tremendously power-intensive, and this week we speak with Robert Gendron of Vicor Corporation, a company focused on powering AI systems. Vicor is in partnership with Kisaco Research, which is putting on the 2019 AI Hardware Summit September 17 and 18 in Mountain View, California. Robert speaks about why the way that they are powered needs to be different than traditional manufacturing equipment. He also discusses how the powering of these systems need to work if businesses want to reduce energy costs and be as efficient as they can when it comes to AI.

This week, we have a bonus episode. We spoke with Jonathan Ross, CEO and Founder of Groq, an AI hardware company, about software-defined computing. Groq is in partnership with the AI Hardware Summit happening in Mountain View, California on September 17 and 18. Software-defined computing is a way of thinking about how computing can be optimized for machine learning functions. Ross talks about some of the pros and cons of GPUs and where software-defined computing might make its way into future machine learning applications.

This week, we speak with Dr. Charles Martin of Calculation Consulting. He's a bit of a mentor of mine when it comes to AI knowledge. Charles speaks to us about the pitfalls in getting to ROI, particularly the cultural elements within enterprises that make it so hard to get a return from AI projects. Charles and I tend to go off in a variety of directions when we talk—he's an animated guy—so be prepared for that. But I think this is an awfully fun episode of the podcast. For more on the fundamentals of getting started with AI in business, learn more about our newest report: Getting Started with AI: Proven Best Practices of Adoption.

We have a bonus episode this week. We spoke to Moe Tanabian, General Manager of Intelligent Devices at Microsoft, who is speaking at the AI Hardware Summit in Mountain View, California on September 17 and 18. Tanabian discusses how to think about and reframe business problems to make them more accessible for AI, as well as AI at the edge, which involves doing AI processing on individual devices rather than in the cloud. The edge could open up new potential for business problems to be solved with AI. Tanabian also provides representative use cases of intelligent devices.

This month, we focus on the ROI of AI, and our guest this week is Sankar Narayanan, Chief Practice Officer at Fractal Analytics, a global AI & Analytics firm headquartered in New York City. In this episode, Narayanan discusses how to measure the ROI of AI in ways that aren't just financial return. In addition, he provides examples from his hands-on experience implementing AI to provide business leaders with ways of thinking about success when it comes to AI projects. For more on measuring the ROI of AI, learn about our newest report Getting Started With AI: Proven Best Practices of AI Adoption.

This is the final episode in the month-long series on getting started with AI. In this episode, Emerj CEO Daniel Faggella breaks down the key insights from all four of this month's interviews, distilling them into core best-practices for getting started with artificial intelligence in business. In addition, Daniel discusses insights from our newest report: Getting Started with AI: Proven Best-Practices for AI Adoption

This week we interview Jan Kautz, Vice President of Learning and Perception Research at NVIDIA. Kautz talks about what people underestimate when they start an AI initiative. In addition, he emphasizes the critical value of data storage. Kautz dives into the importance of getting started with an AI project when you already have a barometer of success. Essentially, he talks about why it's important to select a first AI project in an area where you already have a way of measuring success. Learn more about AI adoption in our full report, Getting Started With AI: Proven Best Practices for AI Adoption.