June 10, 2024

A.I. and Machine Learning to Lead the Nutraceuticals Industry Forward

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A.I. and Machine Learning to Lead the Nutraceuticals Industry Forward

 

Back in the day, our relationship with technology was quite different than it is now.

 

Car phones, if you were lucky enough to have one, were devices with curly cords connected to fairly large handsets. There were also no pocket computers (e.g., smart phones), no desktop (or laptop) computers, just yellow lined pads and pens or typewriters, and no on-line shopping.

 

If you weren’t around back then, you might wonder: how did we ever get through our business day?

 

Depending on your age, your own “back in the day” will place you in a different time period, with different memories of how technology, or the lack thereof, improved your business (and personal) life. For example, some of you may laugh at the actual memory of your first car phone, likely a perk that went along with your company car, if you were fortunate to have both.

 

And others of you may have no idea what we’re talking about.

 

The reason we’re tripping down memory lane is because our industry, among most, is about to experience a seismic technology shift that is already well underway. Ready to go through it together?

 

We’re talking about Artificial Intelligence (AI). And if the possibility of life on other planets excites you, just wait till you learn what AI can do right here on Earth.

 

McKinsey & Company neatly summarizes AI as a “machine’s ability to perform some cognitive functions we usually associate with human minds.” (1) This means that machines that can solve problems, use reasoning and learn things—sort of like humans, but without the emotions or feelings—at least for now.

 

There are so many potential applications for AI that could be game changers, but we’re not going to attempt to boil the ocean in this blog. In other words, just like boiling the ocean, trying to get a handle on the entirety of AI, especially in under 1500 words, is not only a massive undertaking, but one that would be futile.

 

So, let’s start with some basics. Now that you have a definition of AI, you’ll want to know what Machine Learning (ML) is and how it can change your life (and our industry) for the better.

 

We like this explanation from DataCamp (2):

 

“Machine Learning, often abbreviated as ML, is a subset of AI that focuses on the development of computer algorithms that improve automatically through experience and by the use of data.  In simpler terms, machine learning enables computers to learn from data and make decisions or predictions without being explicitly programmed to do so. At its core, Machine Learning is all about creating and implementing algorithms that facilitate these decisions and predictions.

 

In your personal life, whether you realize it or not, you’re probably already enjoying the benefits of Machine Learning. For example, iPhones use ML for people to browse, search and potentially organize their photos, using a foundational algorithm that visually recognizes people. A simpler example is if you put the word “dog” into your search in your photo library, your smart phone has learned what a dog is and will pull up your dog pictures—even if it’s not your dog!

 

Applying AI and ML in Industry

 

Here are just three (there are many more!) specific areas of AI and ML that we envision will help modernize the nutraceuticals industry and its businesses:

 

  1. Forecasting—Using AI and ML, companies can analyze sales data, historical market trends, and other outside factors to accurately assess future demand in products. AI and ML can scrutinize not only historical market trends and sales data, but also external factors to predict future demand accurately.

Procter & Gamble is one company that is using ML algorithms to help optimize production schedules and distribution channels by having ML                 analyze point-of-sale data, social media trends and even weather patterns to forecast product demand. (3)

  1. Inventory Management—Walmart is utilizing the power of AI in managing inventory across its extensive network of stores and warehouses resulting in impressive cost savings, improved efficiency and a better-run supply chain. This streamlined approach has allowed Walmart to better administer and maintain its stores’ product inventories which help drive sales and make customers happy when they see stocked shelves (in stores or online). (4)

 

  1. Addressing Sustainability—Nestlé is corralling AI and advanced data science to better understand and act on environmental pressures that threaten their profitable coffee business. Climate change is a land-and-crop bully with the potential to destroy much of the world’s Coffea arabica, commonly known as coffee bean plants. Arabica has a lower tolerance to rising temperatures and is more susceptible to disease than other coffee plants. To help ensure a sustainable future for cultivating coffee, and supporting farmers, Nestlé has mapped out a plan that it hopes will result in regenerative farming of crops with greater resilience to disease and drought. (5, 6)

 

It’s also important to begin to understand what AI is not doing. DataCamp has an interesting blog (7) that among other things, debunks some of              the common misconceptions (and fears) about AI. For example:

 

  1. AI is creating a world of robots. While AI may involve robotics, it’s a broader discipline that also pulls in other technologies, such as learning language algorithms, figuring out search technologies, and applying data analysis.
  2. AI is strictly factual, leaving opinions behind. Not true. In today’s world, it’s hard to find someone without bias, and that includes AI. For example, if you’re using some version of ChatGPT to write your company’s blogs, and you ask questions that will lead that AI algorithm to explain dietary supplement regulation, ChatGPT will likely pull info from a wealth of other articles that have been published about dietary supplement regulation—articles that many in the supplement industry have complained for years are biased and misleading.
  3. AI is coming for all our jobs. Maybe someday, but not at the moment. At least not right now for most of us. That’s because AI doesn’t yet understand speech, context, and tone in the same way that we do. If your job requires self-awareness, managing relationships, reading the room, imagination and other skills that are human-housed, you don’t have to look over your shoulder quite yet.

 

If you think that AI appeared out of nowhere, think again. Remember Rosie the Robot from The Jetsons, a futuristic cartoon that aired in the early 60s but was set in 2062? How about the 1964 World’s Fair that featured an exhibit with animatronics, an early version of AI?

 

Fast forward to today, and it seems like AI is moving more quickly than some would like. Congress is now questioning—and being questioned as to—when and how it plans to involve itself in regulating this behemoth of technology.

 

In March of 2023, more than 1,000 technology leaders and researchers signed an Open Letter (which now has over 3,000 signatures) urging “all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4.” The gist of the letter was this: “Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable.” (8)  FYI, although the letter generated publicity and may have helped temporarily slow down the movement, there was no actual pause. (9)

 

And then there’s Bill Gates, who says that AI “will change the way people work, learn, travel, get health care, and communicate with each other. Entire industries will reorient around it. Businesses will distinguish themselves by how well they use it.” (10)

 

If that’s not an enthusiastic, clarion call for engagement, we don’t know what else is. If you’re not yet paying attention to AI, now’s the time to start.  We’re ready if you are!

 

 

 

  1. McKinsey & Company, “What is Artificial Intelligence,” April 3, 2024
  2. com, Blog: “What is Machine Learning,” July 2023
  3. Polestar, “Decoding the Synergies of AI & ML,” February 13, 2024
  4. Akkio, “Revolutionizing Inventory Management,” November 24, 2023
  5. Nestlé Press Release, “Mapping Arabica!” April 15, 2024
  6. Consumer Goods Technology, “Nestlé Uses AI and Data Science…,” April 16, 2024
  7. com, Blog: “What is AI,” September 2023
  8. Pause Giant AI Experiments: An Open Letter, March 22, 2023
  9. Axios, “The Great AI “Pause” That Wasn’t,” September 22, 2023
  10. GatesNotes Blog, “The Age of AI Has Begun,” March 21, 2023

 

 

 

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