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:

The Future of Drug Discovery and AI - The Role of Man and Machine

The Future of Drug Discovery and AI – The Role of Man and Machine

Episode Summary: This week on AI in Industry, we speak with Amir Saffari, Senior Vice President of AI at BenevolentAI, a London-based pharmaceutical company that uses machine learning to find new uses for existing drugs and new treatments for diseases.

AI for Government and NGO Social Good Initiatives - an Interview with the Wadhwani Institute

AI for Government and NGO Social Good Initiatives – an Interview with the Wadhwani Institute

Episode Summary: We usually discuss the impact of artificial intelligence on a business's bottom line, but, in addition to law enforcement, governments and NGOs are also considering AI as a mechanism for improving society.

Artificial Intelligence for Video Search and the YouTube of the Future

Machine Learning for Video Search and Video Education – How it Works

Episode Summary: AI, specifically natural language processing, has made it easier to understand text as a medium in a deeper, more efficient way and at scale. With video, the situation is quite different. AI is already being used to help industries that work in the video medium. However, searching for content within videos is more challenging because video is not just voice and sound, it is also a collection of moving and still images on screen. How could AI work to overcome that challenge?

How Recommendation Engines Actually Work - Strategies and Principles

How Recommendation Engines Actually Work – Strategies and Principles

Episode Summary: When we think of recommendation engines, we might think of Amazon or Netflix, but while consumer goods and entertainment might be the most prominent domains for recommendation engines, there are others. This week, we speak with Madhu Gopinathan of MakeMyTrip, one of the few Indian unicorn companies, about recommendation engines for travel companies.

NLP for Text Summarization and Team Communication

NLP for Text Summarization and Team Communication

Episode Summary: In this episode of the podcast, we interview AIG’s Chief Data Science Officer, Dr. Nishant Chandra, about natural language processing (NLP) for internal and team communication. Dr. Chandra talks about how NLP can help with sharing documents with specific team members whose roles warrant viewing those documents.

How to Determine the Best Artificial Intelligence Application Areas in Your Business

How to Determine the Best Artificial Intelligence Application Areas in Your Business

Episode Summary: This week’s episode of the AI in Industry podcast focuses on two main questions. First, how should business leaders determine the most fruitful, potential applications of AI in their business? Second, how do they choose the right one into which to invest resources?

The Future of Advertising and Machine Learning - Audience Targeting, Reach, and More

The Future of Advertising and Machine Learning – Audience Targeting, Reach, and More

Episode Summary: Facebook and Google’s advertising complex is founded on machine learning, allowing people to self-serve their data needs across a broad audience. India-based InMobi is a company in the advertising technology space that delivers 10 billion ad requests daily.

How Existing Businesses Should Organize Their Data Assets for AI 1

How Existing Businesses Should Organize Their Data Assets for AI

Episode Summary: Companies with wells of data at their disposal may find themselves asking how they can use them in meaningful ways. Generally speaking, a clean set of data is the foundation for AI applications, but business owners may not know how exactly to organize their data in a way that allows them to best leverage AI. How exactly does a business transition from having data with the potential for usefulness to having data that’s going to allow for an accurate, helpful machine learning tool—one that can actually help solve business problems?