Stellar Trends & Insights Report: May 2019

Join us to discover the latest trends across Australian industry and customer experience. In this issue: A more dynamic drive-thru experience, The proliferation of predictive personalisation & Roadmap sets the groundwork for AI research priorities.

A more dynamic drive-thru experience

McDonald’s enters into the AI world with the acquisition of Dynamic Yield

McDonald’s has announced that it will acquire AI company Dynamic Yield for approx. US$300m. The technology will provide a more personalised experience in their Drive Thrus via intelligent digital menu displays that show food based on time of day, current restaurant traffic, weather, and trending menu items and suggest food based on customer’s selections.

The occasionally slow decision making process at a drive-thru will be made easier with more relevant recommendations.

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The proliferation of predictive personalisation

Use cases for machine learning extend across financial services, retail and automotive sectors

Machine Learning, a type of AI, involves training a machine how to learn – performing tasks without explicit instructions, relying on patterns and inference to make decisions. Several companies are benefiting from the technology – American Express in detecting fraud, Yelp in categorising information from pictures hosted on the app (given users spend more time looking at them than anything else), and BMW using your driving preferences to adjust your cabin experience.

Predictive power enabled by machine learning is continuing its rapid expansion across more sectors.

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Roadmap sets the groundwork for AI research priorities

Long-term AI research roadmap in development for the US

Following on from a US government AI strategy launched in early 2019, research group Computing Community Consortium, co-chaired by academics from the University of Southern California and Cornell University, has released a report outlining priorities for artificial intelligence research in the US in the next 20 years. Recommendations include creating an open source platform for AI data to be used across academia, government and business, launching national AI competitions to help solve big challenges, supporting research into self-aware learning (AI learning by example) and creating recruiting programs that attract a talented and diverse range of students to work in the field.

As artificial intelligence takes off in capability and relevance, having a solid foundational roadmap in place will assist its development.

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About The Author

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