George J. Nassef is the CEO and Co-Founder of TripVair Inc., a data service powered by predictive models that aims to improve the travel experience by offering accurate and unique long-range transportation and logistics predictions in time to avoid trip interruptions.
Nassef got his start in 1987 in the transportation industry when he joined American Airlines Data Processing Division, which would eventually spin out as SABRE Holdings via IPO.
Over the next 35 years, Nassef never strayed far from his technology roots, taking on various high-profile CTO roles as well as starting many new businesses. He has also built upon his BS in Computer Engineering from Texas A&M University in the 1980s by gaining separate certifications in Advanced Computer Security and Machine Learning from Stanford Continuing Studies from 2018 to 2020. Nassef is also currently a Master of Liberal Arts in Finance degree candidate at Harvard University Extension School.
We wanted to learn more from Nassef and has passion for technology, leading to the following interview.
Question: Did you always know you were going to have a career in technology? Or was there a defining moment?
Answer: I always knew I wanted to work in technology. My curiosity as a child led me to disassemble and then re-assemble every piece of electronics, I could find just to understand how they worked. My interest wasn’t just limited to early computers. I was encouraged by my family to fix anything which stopped working: cars, radios, alarms, computers, etc.
I can still remember when I was young and my family lived in West Palm Beach, Florida. I begged my parents to let me stay up late and stand outside to watch the nighttime Apollo rocket launches. Even as a kid I was fascinated by what technology could do.
Q: What were your initial responsibilities in the late 1980s at American Airlines’ Data Processing Division and how did those responsibilities change?
A: I went to Texas A&M and majored in engineering while also working full-time in the college data center, which kept me busy. Although I didn’t have time to socialize as much as my peers, working full time with systems gave me an advantage when I started interviewing for jobs my senior year. I decided to take a job with American Airlines, and never looked back.
Since I already had four years of full-time experience doing debugging and server software maintenance, American hired me to join a small team of engineers assigned to a help desk for other engineers to call when they had problems with utility systems or their own programs. My responsibilities widened quickly, and I was able to understand the data flows between the reservations and airline logistics, which gave me a unique overview of the entire operation.
From there, I moved to a very small team of systems programmers critical to keeping the large production mainframes running. This early position gave me a wide view of the way in which all the specialized systems connected and exchanged data.
Q: Two decades ago, you began various entrepreneurial pursuits, did you maintain a hand in the technology side of those businesses and why?
A: Yes, always. My vision of a technology leader fits the model of a Chief Surgeon in a large hospital. I don’t have to do every operation personally, but I try to have an operational understanding of the latest approach, hold expertise in a few fields such that I can teach them, and be able to recognize expertise when hiring.
Q: Why did you decide to go back to school a few years ago?
A: If you want to succeed and continue to innovate in the technology industry, there is no other choice but to keep learning. Yes, one can self-learn with streaming task-oriented instruction, but these methods lack an element of cohesiveness I find when taking a series of courses for a certification or degree. Just as inventors must scrap everything and start over again, I think it’s important to do the same with mental models and training.
Q: What lessons have you learned in a career that has featured a blend of technology and entrepreneurship?
A: Time is not on your side as a good portion of the risk of winning is in the execution, not the idea. Having personally watched so many technologies get superseded by better ones, starting over becomes something that you need to look at as part of the process, not a negative.
Q: Why did you decide to start TripVair?
A: I knew years ago that AI was going to revolutionize the technology industry and decided to apply the latest AI solutions to long-standing problems in transportation. If data is the “new oil”, then small companies that can move quickly can build the first wells and begin pumping.
With TripVair, we were able to train and patent working AI models from billions of historical events to make extremely accurate long-range predictions in travel. Our system is able to interpret patterns across hundreds of variables and arrive at highly accurate forecasts, ranging from long-range flight cancellation predictions to a flight delay up to 14 days in advance.
Q: How do you see your company interacting with the enterprise?
A: Our product is a self-service online data feed that addresses top complaints in air travel. Companies can sign-up in minutes, connect their mobile, web or other application to our data and answer questions.
Armed with this data in sub-second real-time, travel app providers can pass along hints or guidance during booking or pre-travel to clients about what flights make sense for their priorities.
Travel insurance companies can make an informed decision to reduce the rate of a trip insurance package if our prediction is different from, say, and average already figured into a premium.
Q: Give us a glimpse of what you see in the future with AI?
A: The latest generation of hardware and software for AI training brings us closer to many of our favorite science fiction books and movies than ever before. Generative AI acts like a very good librarian but with the ability recite all the contents of the library in ways we understand. As fast as this has arrived, it is still evolutionary. The revolution will be when predictive AI is also ubiquitous.
TripVair uses predictive AI to answer travel logistics questions. The future of AI will be able to predict nearly everything, make revolutionary inventions and recommendations or solve many of the unsolved problems in our universe. I don’t think we’ve ever experienced a similar leap in innovation before.