AI Articles and Analysis about Automation and robotics

The precipitous drop in the price of drones and the intelligent guidance systems that power them has created a broad range of commercial applications (we covered industrial drone applications in a previous article). One use-case that has captured popular attention and large scale investment from a variety of retailers and start ups is autonomous delivery vehicles.

The applications of AI in pharma are building momentum, but we wanted to look beyond the hype and find the underlying trends that matter in business.

It’s no secret that e-tailer Amazon has an army of robots at its warehouses to fulfill orders; currently its robot detail is 45,000 strong. The company also wants to put a fleet of airborne drones into service for fast deliveries. The question that traditional retailers face is whether or not investing in robots to operate inside their stores can actually improve business and help them stay relevant with consumers.

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.

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.

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.

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.

High costs and technical limitations kept the uses of drones relatively limited until recently. After significant excitement starting around 2012, the FAA's 2016 adoption of regulations - combined with the drop in price - has made drones an economically viable option for a broad range of commercial functions.