We sat down with Daniel Bruce from Levatas to discuss how his career path has evolved, what made him get into AI, his biggest achievement so far, and more.
What has your career path been like since you started?
In the approximately 20 years that I’ve been working in this field, I feel incredibly privileged to witness a literal technical revolution. I know many generations have felt this way, but I truly believe we’re living in one of the most transformative generations ever.
So, my career so far has and continues to be characterized by rapid change. I’ve had the privilege of working for many leading industry brands and helping those companies navigate the break-neck pace of change is challenging but also really meaningful. It’s been incredibly rewarding so far, but it feels like running an all-out sprint without a break. When you love sprinting, it’s a lot of fun!
What made you get into AI, and specifically, your industry/field?
I’ve been passionate about AI for as long as I can remember. Specifically, since early in my education and career, I’ve been fascinated with applications of AI to unstructured data, a field called “machine perception”. This field focuses on giving machines the ability to draw insights from unstructured data (like text, speech or images) and replicate human capabilities that we take for granted (like vision, speech, smell, etc…).
These are capabilities that come naturally to us as humans, but are incredibly difficult to replicate in computers. Many other fields of AI are focused on a sort of converse of this (taking tasks that humans are relatively bad at, like analyzing big tables of data for patterns). Machine perception is fascinating to me though because it focuses on replicating deep, but very intuitive tasks that come easy to us but are really hard for computers.
What’s more, these tasks are absolutely critical to allowing machines (for example, robots) to exist safely and usefully in a real-world environment where most data comes in an unstructured form. That makes this field incredibly fascinating, but also critical for so many industry applications. That’s just a fun space to be in.
What advice do you wish someone had told you when you were starting out?
If I had a time machine, there’s so many things I would wanna tell myself 20 years ago, so it’s hard to narrow this down! Certainly, one thing I’d want to tell myself is to always view education, not as a destination but a journey. I think this is true in general, but in tech and especially in AI, the pace of change in the industry is breathtaking (literally).
So it is critical to embrace and love constantly learning. Whether that’s learning a new language, a new framework, a new piece of hardware, or whatever the case may be, learning is a constant and critical part of staying relevant. I wish I knew and embraced that day one. I’ve learned that now, but sometimes the hard way!
What’s your current role like? What excites you the most about it and what are the biggest challenges?
In my current role, my focus is finding the right overlap between industry needs and gaps in current technical/product capabilities and then working with a great team to build solutions for those problems.
The biggest challenge and what excites me the most is the same thing: having to learn to adapt to change quickly. Literally on a weekly/monthly basis, I sit down and ask “What’s changed since the last time I asked this question? And how do we need to adjust our strategy accordingly?” That’s challenging, but when you see beyond the challenge, there’s a whole world of opportunity.
What’s your biggest achievement so far?
My whole career, I’ve been extremely privileged to work in the trenches with amazing people. So for every big achievement I can think of, I see faces of a dozen people much more responsible for that than me. With that in mind, I’d have to say the thing I’m personally most proud of is building a team of those great people through the years.
Finding and keeping great people is a challenge, especially in this industry where there’s such stiff competition for great talent. So building great teams of people I’m proud to work with, that continue to challenge me every day - that’s been the highlight of my career.
What impact does your company have on the adoption of AI in your industry/field?
The thing we take the most pride in as a company is our ability to help companies operationalize AI solutions. As proud as I am of Levatas, there are much bigger companies in the space doing fantastic research. There are great consultancies helping companies identify where AI can help save money, improve operations, etc… And that’s very valuable.
But there’s a real scarcity of companies getting real-world AI solutions into production, because AI is messy. It requires such a delicate balance of business and technical priorities, and finding ways to synthesize the things that humans are uniquely good at (like adapting to unknowns, and making ethical judgments) with what AI does best. So helping companies get AI into messy, real-world settings and delivering real value - that’s where we’re having the biggest impact today, and that’s what we want our legacy to be.
How have changes in the industry impacted your job?
More ways than I could list, but again, the constant pace of change in this industry is frenetic, and (to my knowledge) unprecedented in scope. The interesting thing is that this impacts not just smaller companies like Levatas, but also the big players in the space. It comes with its own challenges obviously, but in a way, it’s an advantage being smaller and more nimble.
Change is the only constant, and it’s like the proverbial “sword of Damocles” hanging above us every day. It’s incredibly empowering to feel that your company or your product has your finger on the pulse of what the industry wants, and we certainly have those periods.
But change is always there to mix things up, so we often remind ourselves and our customers, you innovate or you die. That dynamic isn’t just a factor, it is THE factor that has driven my personal and Levatas’ corporate priorities for years. It’s challenging but I’d never want to trade it.
Want more from Daniel Bruce? Tune in to AI Bytes Podcast: Where AI Meets Business.
