Curious to know more about the team at PPO? “People at PPO” is a blog series that highlights the work our team does every day. In each post, we interview one of our team members to get an inside view of PPO and to learn about their experience working here. Join us as we tell their stories and discover how their work impacts the technology we build.
In this post, we spoke with Brad Oldenburg, VP of Data Architecture at PPO. We asked him questions about artificial intelligence (AI) and how it’s used in the food industry. Here’s what he had to say:
J: Hi Brad, thanks for taking the time to talk about AI and machine learning.
Brad: No problem!
J: Let’s start with what do you do at PPO?
Brad: I lead the software and data teams at PPO. What that means is I take a lot of disparate information like timelines and projects and team needs to set the direction for the software team. I use my software background for best practices for testing and design. In the end, I spend less time in the trenches doing hands-on development work, and more time as a mentor and guide.
It can be difficult because most of the leadership team came up from the trenches. Many people think that leaders can solve every problem when in reality we can’t. We don’t have enough time in the day. Sometimes it can be frustrating because when you’re working in the trenches you’re used to being a problem solver. I can’t always be problem-solving, which has been one of the biggest learnings being in a leadership role. I’m lucky to have some really great problem solvers on the software team. They help make my job easier.
J: You bring up some great points about your experience as a leader. Before joining the team, could you talk about your experience with software?
Brad: I come from a software background. In my previous life, I coded with live video for the broadcasting industry. Having that background set me up to work at PPO. I learned to work on projects with large teams. I also learned about the entire product life cycle. I saw every stage from the simulation of the system to shipping the final product to the customer.
There are parallels between broadcast and high-performance processing. Both work on a real-time operation where 100% uptime and high speed are important. That means that you have to focus on both reliability and functionality. And that’s something I’ve brought with me from my past to PPO.
J: You mentioned how broadcasting and AI have many similarities. How is using technology in the food industry the same or different in other industries?
Brad: In the food industry, we can see automation trailing behind compared to other industries. For example, the automotive industry introduced automation 20 years ago.
But there is a difference between assembling cars and preparing meat. Cars are well-defined objects. The car axle in one car is going to be the same as the next. On the other hand, meat varies. No two pork loins are going to be identical. Their size and growing conditions are going to differ. Because car parts are uniform, the automotive industry could adopt automation early on without the tech advancements we have today.
The food industry has the advantage that it can learn from the automotive industry. We can use everything automotive developed and learned over the years. And with AI, there is the potential to implement these technologies at a quicker pace.
J: Going back to your experience, how have you seen AI evolve and change over the years?
Brad: It’s interesting to see its growth. When I was in school, we talked about AI in terms of genetic algorithms, expert systems, and the like; modern neural nets were still in the distance. They weren’t able to capture all the data we can today. Within the last 10-15 years, the advances have been incredible. The hardware and software we use now are more enabled. Simple things like the camera sensors we use didn’t exist 10 years ago. PPO uses near-infrared (NIR) cameras, which aren’t simple technologies. NIR cameras use different sensors and are more complicated than vision cameras. Back then they couldn’t capture data at the high speed we needed them to. Now, that technology is more common and accessible hardware. It’s a lot of fun to implement.
J: So we talked about the past. Now moving onto the future, can you make predictions on what’s going to happen in the future with AI?
Brad: Many smart people tried to over the years and have had varied results. I predict that two things will happen. The first is how can we make AI more creative? What currently separates humans from AI is creativity. But how can we integrate some of that thinking into AI? I see this happening with general AI and digital assistants like Alexa and Siri. In the future, I think they’ll be able to have more complex answers compared to a simple OK. That would be cool.
The second, more immediate and useful application is explainable AI. Today, we’re seeing a lot of unintentional biases in AI’s development. For example, facial recognition is accurate, if you’re a white guy. The AI is learning these behaviors from their creators, which are mostly white males. In the future, I think we’ll learn from these biases. We’ll be including more people of color and others from underrepresented communities to set the standard. There will also be a lot more accountability and introspection to create a more inclusive and ethical AI.
J: How can AI be used in the food industry?
Brad: We’re just on the cusp of discovering what’s possible in the industry. Right now, we can detect foreign materials and assess food quality. In the future, we’ll be able to share information about what’s happening up and down the production line. AI in the plant can collect data like the product’s growing conditions before it arrived in the plant. It can also look at a customer’s steak preferences in the restaurant or in the store. Collecting information beyond the processor is going to have a huge impact. It can influence how they make food for everyone. And that’s impressive.
J: You work with AI regularly, what excites you about it?
Brad: Most AI applications the public sees are in the entertainment space. They see things like adding a filter to face images or a new video player feature. They’re fun, but is it making a significant impact on people’s lives?
What excites me about PPO’s technology is the potential it has to improve the food we eat or reduce food waste. The industry we’re in isn’t the most entertaining. But it’s exciting to create an impact on something that affects everyone on the planet.
J: Speaking of PPO’s technology, where do you see our machine learning and AI in the next 5-10 years?
Brad: I see us building on the technology we have today. Right now, we’re able to give our clients insights and reports on product contamination, quality and composition. That information can be found on-the-line and in real-time.
Similar to what I mentioned earlier, in the future, we’ll be able to gather data beyond the factory. We’ll be able to measure what’s happening on the farm and on your dinner table. If we combine that information, we can make decisions that give our clients the most efficient use of their product.
J: One last question, what’s your favorite food?
Brad: Hmmm…what’s my favorite food? I have a lot of favorite foods, but I’ll give you two fun anecdotes.
The first is that I have a favorite food depending on the time of the year. In particular, I love when summer approaches. I love all the fresh fruits that are in season. So for three months, you’ll catch me eating peaches, berries and cherries. But if I had to pick one summer fruit I couldn’t live without, it would be cherries. They remind me of the time I spent in New Zealand. I would always eat cherries during their growing season.
And here’s the second story. Those who know me know I’m a huge meat-lover. One of my favorite events that normally happens in town is Ribfest. I love going to try the different kinds of rib and drink various craft beers. My wife knows I love Ribfest. So for our wedding gift, she surprised me with an opportunity to be a judge at the event! I had such a wonderful time as a judge. I met the mayor and ended up on the local news talking about it to a reporter. It was such a great experience.
J: I love the cherry and ribs story. Thanks for taking the time to talk to us!
Brad: Awesome, thank you!
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