AI Podcast Interviews Articles and Reports
Our podcast interviews feature the best and brightest executives and researchers in artificial intelligence today, and each episode highlights current and near-term AI use-cases of value for business leaders. Explore our full list of AI podcast episodes below:
We spoke with Jonathan Ross, CEO and founder of Groq, an AI hardware company, about software defined compute. This interview is part of a series we did in collaboration with Kisaco Research for the AI Hardware Summit happening in Mountain View, California on September 17 and 18.
We spoke to Moe Tanabian, General Manager of Intelligent Devices at Microsoft, who is speaking at the AI Edge 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.
Since the advent of online banking services, customers have had several different ways of communicating with their banks. Banks need to monitor all of these incoming customer requests and respond to them in the most efficient way possible. Further, each of the various channels of communication represents a valuable way to segment customers to not only improve how they perceive a bank’s brand but also to market banking products to them better.
Although there are established use-cases for AI applications in the business world, the claims that AI vendors make about returns from their software are often exaggerated. What is also not apparent amongst the AI hype is that adopting AI and machine learning is far more challenging than it might seem.
This week we speak with David Carmona, General Manager of AI at Microsoft. Carmona discusses how redefining a business process is a very different kind of AI adoption project than working on something that is horizontal.
Our research indicates that AI applications for risk-related banking functions are more numerous than applications for other business areas. Fraud and Cybersecurity, Compliance, Loans and Lending, and Risk Management collectively made up 56% of the AI vendor products in the banking industry, as shown in the graph below:
We interviewed Jay Budzik, CTO at Zest AI, about the business value of machine learning for auto lending. We speak with Budzik about how underwriting, lending, and credit scoring is evolving as a result of advances in machine learning - both in terms of new data sources, and more advanced algorithms.
Artificial intelligence is transforming a variety of banking functions and allowing tech startups to compete with some of the largest banks for market share of key services, including lending and wealth management. Business news and media sites have been heralding the downfall of the banking industry as we know it because fintech companies are going to feel comfortable leveraging AI long before banks.