AI Articles and Analysis in Consumer goods

AI is being likened to a "Fourth Industrial Revolution" because of it's potential for creating profound change in people’s lives, much like the invention of steam engines (First Industrial Revolution), electricity and mass production (Second Industrial Revolution), and the rise of the digital age (Third Industrial Revolution) had in the past.

Episode summary: In this week's interview on the AI in Industry podcast, we speak with Amir Konigsberg, the CEO of Twiggle, about the future of product search - and how eCommerce and retail brands can use natural language processing (NLP) to improve their user experience.

This year has been marked by an increase in artificial intelligence interest from new business sectors. Just one years ago, we hardly had any visitors or subscribers from the food services sector - and this year we have a strong interest from food processing and food services leaders, which has come as a surprise.

After a presentation at the Shop!Association’s national conference late last year, I had plenty of time to chat with retail business people about their own ideas about AI’s uses, and the trends that matter most. This prompted me to gather my thoughts and combine the ideas of retailers with the AI-in-retail research we’ve done, and put together a piece to help retail vendors make sense of the next 2-3 years of AI’s influence in retail.

The International Federation of Robotics reports that the U.S. service robot industry, which includes both industrial and domestic sectors, is a $5.2 billion market. It also estimates that home robots or domestic robots will contribute $11 billion in revenue by 2020.

Episode summary: This week, AI in Industry features Dr. David Franke, Chief Scientist at Vast. David talks about how AI can work with scarce transaction data to derive meaningful analytics for big purchases, such as cars and houses. He elaborates on how the AI can glean information from user interaction and marketplace data to provide customers with the relevant product fit, deals and recommendations on big purchases. He also discusses the future trends and business benefits for early adopters of AI for purchase recommendations of high-cost items. 

Expert systems and machine learning are two ends of a spectrum working to solve similar problems quite differently. One one hand you have if-then scenarios and a logical approach, and on the other you have vast neural networks and a big data approach. Some companies exist to try and bridge the gap between the if-then rule systems and the massive piles of data. They hope to find a middle ground of sorts, one that mitigates their individual disadvantages. One such company is Montreal’s fuzzy.ai.

The U.S. Energy Information Agency (EIA) defines renewable energy as an energy source that naturally regenerates, such as solar or wind. In contrast, fossil fuels are considered finite. The EIA reports that in 2016, 10 percent of all energy consumed in the U.S. was derived from renewable energy sources. This is equivalent to roughly “10.2 quadrillion British thermal units (Btu) —1 quadrillion is the number 1 followed by 15 zeros”.