Pizza and ML/AI go together like pepperoni and mushrooms!

ML and AI have many practical uses now. As time passes and the coding becomes better with each iteration, more uses are being put into use. These also are becoming more creative. Recently, one of the applications has been utilized by a pizza giant.

In the limited time I enjoy television, there began to be played Domino's commercials. There are played across the nation every day. They'll have the usual specials and new toppings, however, this struck me as special and usual. This commercial asked the enjoying their pizza to take a picture using the Domino's app and upload it. The person gets points for this a limited amount of time. This may be a  Domino's pizza, a competitor's pizza, or home-made.

On the surface, the marketing focus is apparent. This is a great deal for the customer as they received Domino's points for eating any pizza. This also increases the awareness for Domino's pizza as the name is noted more, due to the commercials and buzz it creates. While this is fantastic, a deeper dive notes another use of this, other than being altruistic. As the customer/consumer uploads the pizza picture, Donio's has the opportunity to log, when possible due to the image, what competitor's pizzas their clients and potential clients are eating. This picture is processed to categorize which business (Domino's, Little Caesar's, Hungry Howies, etc.) made the pizza or if this was home-made.

The algorithm detects the object and identifies the pizza. The ML/AI application not only categorizes this, however, also as part of the process creates a database from the individual person and aggregates this allowing for further baseline and predictive analysis. This genuinely is a great idea, helping both parties.

Yes, AI is able to assist with reducing food waste!

There is a massive issue with food waste. In the US, this issue has been noted, researched, and published at length. Froma physical aspect, all the public has to do is look at the excess food left on the plates in restaurants, as the clientele leaves. This piles up in the dumpster. An area not so easy to study and document involves consumer waste in the home. To measure this waste and extrapolate these would be difficult at best with reasonable certainty.

This amount of food waste is however rather large and across the standard of living tiers. This is not limited to the middle class, however, is done by across the board. This issue is not isolated to restaurants or consumers.

As alarming as the known figures are, there is mitigation available. The individual entity has the opportunity to reduce the waste, based on analyzing the food thrown out using ML & AI. To combat this, the British company Winnow has developed and created a smart bin which was coded to use AI on some level.

To ensure the accuracy of this application, the business began testing this in 100 professional kitchens, and others in the UK and Ireland. An encouraging differential with the study is with IKEA. The management was able to reduce its food waste by 50%. This is a great step in the advancing utilization for ML & AI to better our lives in the long run.

Resource
Katanich, D. (2019, March 31). What can artificial intelligence do about food waste? Retrieved from https://www.euronews.com/2019/03/31/what-can-artificial-intelligence-do-about-our-food-waste/

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