Charlie Burgoyne is the founder & CEO of Valkyrie Intelligence, a consulting firm with domain expertise in applied science and strategy. Charlie is also a managing partner for Valkyrie Vertex, an AI driven venture fund based in Austin, as well as the Chairman of the Board for Valkyrie Labs, an AI product company.
Before launching my own company, I worked as a physicist for various government labs and agencies. During my early career, I saw that mainstream artificial intelligence was overhyped, its real potential was misunderstood, and its most game-changing applications were untapped. As I got deeper into the research, I became much more interested in the nature of intelligence, how we express it and how we can apply synthetic versions of it. In order to artificially create something, we need to understand its organic state.
In 2017 you founded Valkyrie Intelligence, could you walk us through the genesis story of this start-up?
I saw a large gap between the cutting-edge techniques in research and their application in industry. Many scientists were forced to either prioritize interesting research and projects or support a comfortable life for their families, and I found that ultimatum unsettling. I set out to create a place for scientists to tackle some of the industrial world’s most interesting problems. I founded Valkyrie and brought together some of the brightest minds in the country—mathematicians, statisticians, biologists, chemists, physicists—to solve some of the biggest problems in modern business and society and harness the power of data science for the greater good. The real value of AI in the market right now is in the narrow band applications of the field, where AI is automating singular, often simple tasks. This is where people are developing really interesting algorithms that do not require a synthetic brain; they capitalize on potential patterns that exist and largely lay dormant in data. At Valkyrie, we champion the restructuring of knowledge and optimize it for pattern recognition.
Valkyrie Intelligence has a team of highly trained scientists and strategists to implement advanced analytics. What type of projects do you normally take on?
We love taking on projects where our clients come to us and say, “we know AI has a potential impact on our business, but we don’t know where to start and we don’t know if we have the right data.” We’re able to bring on our team to create a vision and plan for execution that’s aligned with where they want their company to go and what code we need to get there. Clients who understand how their business can transform with technology are great because every organization is different and requires a unique approach. This applies to every industry – we’ve helped banks cut their default rates in half, telecommunications companies redesign their entire business model and investment firms predict which assets to buy.
What is one of the most impactful projects that you have worked on?
It is hard to name just a single project that I have enjoyed the most. Certainly, the work we did for a Formula 1 team last year was a highlight, as was a project in telecommunications that capitalized on cutting edge research. However, I would say the most rewarding work for me is the work we do supporting the Defense and Intelligence space. We have now had several programs oriented around the defense of our nation and providing our warfighters with tools that give them an edge in the battlefield. One part of our vision is to reinvigorate scientists’ fervor to serve their country the best way they know how, through math. I believe that passion for government service has waned over the past few generations and it is so important for us to rekindle that passion for the sake of our nation.
Your company is driven by women, starting with the two principal scientists on your team. This is rare in STEM and specifically in AI. Do you believe this gives your company an edge?
Valkyrie was founded on the belief that a balanced team is a better team, and we have historically hired and supported women. I’m a big believer in hiring the best talent and empowering them to lead and succeed. If you surround yourself with a variety of perspectives and diverse voices, that will strengthen the company and strengthen the work. As our team expands, this is something that we will continue to prioritize.
Valkyrie Virtue is a new philanthropic initiative to uplift nonprofits and women in STEM. Could you share with us some details regarding this new initiative?
Valkyrie brings incredibly bright minds into a shared lab and united vision. I believe it’s our responsibility as leaders to react when our community is in need. Valkyrie’s passion for community enrichment inspired us to launch Valkyrie Virtue, which offers pro-bono data science services to nonprofit organizations, enabling them to access strategic insights and better serve the Austin community. Through Valkyrie Virtue, we recently partnered with a local nonprofit dedicated to addressing homelessness, by offering our data scientists’ talents to identify high-risk areas via AI and recommend the best services to provide. In total, our team donated 836.5 pro-bono hours in 2020, or about $223,175 in services. We also launched an annual Women in STEM scholarship fund to support Austin’s women of color as they enter higher education, since they receive less than one percent of philanthropic efforts. This year, we partnered with the Hispanic Scholarship Consortium to present a $10,000 academic scholarship to a local student currently attending Texas A&M University.
You are also a managing partner of Valkyrie Vertex, an AI driven investment fund. What are some ways that machine learning plays into wealth management?
Vertex is the flagship fund for the Valkyrie group. The fund invests in high performance venture capital funds that are algorithmically identified by evaluating the experience and capabilities of the managing partners of the respective funds. This approach allows Vertex to be well diversified as we are making investments at the fund level instead of direct investments with the individual portfolio companies. Our advantage in this space comes from the fact that we use machine learning to identify patterns of success in fund managers as opposed to focusing on a particular industry, geography or strategy. This approach is very much akin to the strategy that Renaissance Technologies adopted for the public markets, but in this case, we are deploying it in private assets where the differentiation is more profound. Our models have identified funds as well as co-investments for deployment of capital, and our team is ready to go as we close our first round.
When looking into the future where do you see the state of AI in the next 5 or 10 years?
I predict that AI will only become a larger part of business and finance, especially as an increase in data science companies makes automation more accessible for small businesses. Small businesses account for nearly half of the U.S. workforce, and while they may not have the data sets of large corporations, data scientists can still gather insights into key business functions, such as customer relationship management or sales. AI can strengthen many assets of day-to-day operations with game-changing results. For example, industry estimates forecast that AI can increase business leads by 50 percent and boost profitability rates by 38 percent, making it a critical component of any small businesses’ plans to compete with larger competitors in their field. I also expect that finance companies will integrate data and AI/machine learning into every facet of their business to a greater extent. While Big Data and AI have been hot topics for years, many businesses quickly learned that without a holistic and targeted strategy, the mounds of data weren’t useful. The pandemic’s economic impact has pushed many businesses to focus on return-on-investment, leaving little room in tight budgets for ineffective measures. In order to stay competitive, entrenched financial institutions and Fintech startups alike are using data and AI in areas core to their business function and growth: risk management, fraud detection, customer experience and service, employee management, targeted business development and marketing, intelligent product development and AI-driven decision making.
Thank you for the great interview, readers who wish to learn more should visit Valkyrie Intelligence.
- Attention-Based Deep Learning Networks Could Improve Sonar Systems
- Cerebras CS-1 System Integrated Into Lassen Supercomputer
- Deepfaked Voice Enabled $35 Million Bank Heist in 2020
- Facebook: ‘Nanotargeting’ Users Based Solely on Their Perceived Interests
- IBM Announces AI-Driven Software for Environmental Intelligence