Beyoncé adopted a plant-based diet 44 days before her Coachella performance this year. Now, according to Forbes, She is using her visibility to draw others to a more compassionate and sustainable way of eating with a new and innovative vegan meal planner that utilizes AI.
Beyoncé’s journey to veganism began in 2015, under the training of exercise physiologist Marco Borges. Teaming up with Borges this year, Beyoncé and her husband Jay Z created 22 Days Nutrition. Their aim is to provide everyone with the guidance Borges’ previously only provided to celebrities and the wealthy.
Beyoncé offered her own enthusiastic testimony to a plant-based lifestyle. "What I discovered was increased energy, better sleep, weight loss, improved digestion, clarity and an incredibly positive feeling for my actions and the effects it would have on those around me and the environment."
Like other meal planning websites, users can explore meal options and create meal plans and grocery lists. Food coaches and cooking videos are just some of the many tools. It also offers vegan meal delivery, which helps combat food deserts. What sets this new vegan meal planning program apart is the utilization of machine learning. Individual preferences, habits, and what people with similar preferences prefer to eat are taken into account. Then, after the user creates more specific preferences, the meal planner is better able to predict the types of meals the user will enjoy.
Memberships are $14/month or users can save 40% by signing up for a year. It is integrated with Instacart, Peapod and soon, Amazon Fresh. At 22 Days Nutrition, AI works with users and adapts its recommendations to fit their needs as they change over time. Although this type of collaboration is new, we can expect it to become standard within the next decade.
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Reality Changing Observations:
Q1. What meal planning methods have you tried?
Q2. Are you interested in trying 22 Days Nutrition? Why or why not?
Q3. What does the addition of machine learning do to set this meal planning program apart? How could it be improved upon?