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Episode summary: Machine learning currently faces a number of obstacles which prevent it from advancing as quickly as it might. How might these obstacles be overcome and what impact would this have on the machine learning across different industries in the coming decade? In this episode we talk to Dr. Hanie Sedghi, Research Scientist at the Allen Institute for Artificial Intelligence, about the developments in core machine learning technology that need to be made, and that researchers and scientists are working, on to further the application of machine learning in autonomous vehicles.

Sales enablement refers to any technology solution designed to increase productivity during the sales cycle, usually for enterprise business development. Whether managing many sales reps in a large organization or increasing a single sales executive's conversion rates, the primary goal of sales enablement is to push productivity numbers up and to the right.

While self-driving trucks and self-driving cars make use of much of the same technology to power their AI systems, it would be a mistake to think the expected roll out date of both developments to would be identical. Their similarities can easily mask their significant differences.

Despite the massive venture investments going into healthcare AI applications, there's little evidence of hospitals using machine learning in real-world applications. We decided that this topic is worth covering in depth since any changes to the healthcare system directly impact business leaders in multiple facets such as employee insurance coverage or hospital administration policies.

Episode Summary1: Fraud attacks have become much more sophisticated. Account takeovers are happening more often. Many security attacks involve multiple methods and unexpected attacks can devastate businesses in just a few days, as we saw with Neiman Marcus and Target. False promotion and abuse is seen not only on social media sites but is also targeted at business. To combat these risks, fraud solutions need to be smarter to keep pace with fraudsters to prevent attacks and react quickly when they do happen. This requires a fast-learning solution with the ability to continually evolve - which calls for the application machine learning for fraud detection. In this episode we talk to Kevin Lee from Sift Science and examine the shifts in the info security landscape over the past ten or fifteen year. Lee also highlights what new kinds of fraud are now possible and what machine learning solutions are available.

Artificial intelligence in news media is being used in new ways from speeding up research to accumulating and cross-referencing data and beyond.

Just as car companies are betting big that self-driving vehicles will change our roads, shipping companies are making a similar bet that automation will change how we move goods around the world. For autonomous ships, the open ocean may prove to be more fertile ground for the adoption of full automation than crowded city streets.

Historically, space has been an industry only governments and heavyweight airspace corporations (such as Boeing) could handle. Uses of AI in space technology might be expected to be even more expensive, but the last decade of innovation has made space more accessible - and thanks to AI - data from space is becoming much more useful for businesses and governments.

As a business leader, you know the essential role of telecommunications in running a business. In the digital era, the telecom industry has shifted from basic phone and Internet service to a sector that is going high-tech and constantly evolving into a more mobile, wearable and automated environment.

Episode summary: Unlike the field of self-driving cars, the fields of construction, mining, agriculture, and other classes of “heavy industry” involve a huge variety of equipment and use-cases that go beyond traveling from A to B. The heavy industry leaders of today are no farther behind automakers in their understanding that AI and automation will be essential for the future of their companies. In this episode, guest Dr. Sam Kherat discusses the applications of AI in heavy industry, including: What type of capabilities and functions are automate-able, and at what level. He also shines a light on how AI might affect the future of the industry within the next 2-3 years, and in what ways we can expect large equipment to become more autonomous.