Eye on AI - July 31st, 2020
Welcome to Aigora's "Eye on AI" series, where we round up exciting news at the intersection of consumer science and artificial intelligence!
Hi everyone! This week, we’ll be looking at two forms of AI linked to the food industry that have recently seen rapid advancement in Amazon’s Alexa and smell-based AI.
Alexa and Audio-Based AI Continue to Expand within Chain Restaurants
Let’s begin by looking at news of a new application of Amazon’s Alexa in Sonic restaurants. In 2017, when TGI Fridays became the first restaurant chain to offer Amazon’s Alexa pay, no one had any inkling how much influence Alexa and other audio-based AI would have in chain restaurants. It seemed unnatural for such technology to be used in a fast-food world dominated by brick and mortar. The times, as they say, have indeed changed. News this week that Sonic will now be now using Amazon’s ‘Alexa Skill’ to help customers to find locations and menu items is only the latest in an onslaught of restaurant news about AI-driven partnerships.
“Alexa for Apps is a natural fit for [Sonic’s] mobile strategy as we are always on the lookout for new ways that technology can help us serve our millions of devoted fans better,” Kim Lewis, vice president of digital strategies for Sonic said in a statement. “Hungry consumers make choices quickly and asking Alexa on their mobile device to find nearby Sonic locations and discover new menu items removes friction from the process. In the future, we plan to build on our new custom skill, adding great features to make it even easier for our guests and fans.”
Since their first partnership with TGI Fridays in 2017, Amazon has integrated with restaurant chains across the globe. Amazon’s Dave Limp even made the Nation’s Restaurant News Power List in 2020 for connecting restaurants like Chipotle, Wingstop, Domino’s and Denny’s with Amazon devices.
The latest restaurant push by Amazon comes at a time when the restaurant industry’s hand is being forced to look for new ways to connect with customers in contactless ways, and is one reason why big tech has seen heavy growth since the pandemic hit. Just this week, clean juice announced it would be launching a new app with lunchbox, helping them to offer more ways for customers to get healthy certified-organic products into their hands. Similar tech-inspired food news has been popping up almost daily. As the world continues to go digital in a push for more contactless deliverables, expect to see more restaurant AI news as other audio-based AI players continue vying for market share.
New AI Attempts to Mimic Human Olfaction
Voice-driven AI is hardly the only food-driven AI that has been on the rise. AI smell, a technology we’ve been following closely with this series, has also seen heavy growth. News this week that researchers at UC Riverside have found a new breakthrough method for allowing a computer to learn chemical features that activate known human odorant receptors is unique in that it’s among the first applications of AI we’ve seen that may actually mimic human olfaction.
“The researchers first developed a method for a computer to learn chemical features that activate known human odorant receptors,” writes reporter Iqbal Pittalwala. “They then screened roughly half a million compounds for new ligands — molecules that bind to receptors — for 34 odorant receptors. Next, they focused on whether the algorithm that could estimate odorant receptor activity could also predict diverse perceptual qualities of odorants…. [the researchers] showed the activity of ORs successfully predicted 146 different percepts of chemicals.”
This new digital approach, which has the ability to find ligands and new flavors and fragrances, could lend to many applications in the food, flavor, and fragrance industries. It could potentially intelligently design volatile chemicals that smell desirable for use and predict ligands for the 34 human odorant receptors –– in layman’s terms, it could accurately predict how chemicals and chemical combinations will actually smell to humans before being tested on humans.
While this technology is still young and patent-pending, there’s still a long way to go before it can be applied to mass use. If it proves accurate, it could be a game changer.
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