Gil Elbaz believes everyone should have access to information and has dedicated his life to building companies that make information easier to get.
He was the co-founder of Applied Semantics, which he sold to Google in 2003. He then worked at Google for four years.
From 2008 to 2013, Elbaz was a trustee at his alma mater, the California Institute of Technology. In 2008 he founded Factual, a data company that provides location services. He is also a board member of the XPrize Foundation, the founder and chairman of Common Crawl, a mobile board member at IAB and a founding partner at TenOneTen Ventures.
Crain’s Los Angeles spoke with Elbaz about his career.
Searching for answers
I didn’t have any concept of how my life would evolve, but as a kid I was addicted to data. I would ask my parents to leave me in the reference section of a library. I just loved to pour over facts. It was about the freedom to answer questions myself. And in the end I built a career on data.
I keep with me a short essay I wrote when I was seven or eight years old about wanting to build a machine that answered questions. I thought about data from a very early age but I don’t think I had any idea it would become what it is now.
College and first steps
Caltech has a very strong science and math curriculum. I was very focused on math and expected to go into engineering after school. It was a great way to get the fundamentals down.
When I graduated, it was pre-web. There were very few people starting companies out of college. The normal thing to do was work in the industry until you cut your teeth and had more background.
I was inspired by a lot of things to start a company of my own. I was inspired by a close friend who was one of the co-founders of LinkedIn and seeing people around me building companies that were oriented in data and how hard people were working to reinvent things. In the case of LinkedIn seeing people connect around work topics.
I worked at MicroUnity for a year. MicroUnity was an ambitious startup that was trying to compete with Intel and Microsoft and I was inspired by that level of ambition. They were building their own microprocessor. Perhaps that ambition was too large, but it was very exciting to be in Silicon Valley.
Starting a company
I was so focused on data that it was always my number one priority to do something impactful in that area. It was very natural to pursue my passion and my expertise and that can distract someone from fear of the unknown. I was doing something that I loved.
I did set myself up financially. I worked hard in Silicon Valley for seven years. And I saved money. I moved back to a house in L.A. with four roommates. I figured out how I could work on what started as a project and became a company. I was in charge of my own destiny.
It helped that we were able to hire good people so cheaply. I was funding the company for the first six or nine months from my lifesavings and we were running the company out of my house. We got talented people to work for very little. I can’t explain what drew these terrific people toward us. Perhaps it was the intensity and the passion for doing what we were doing which was organizing the world of information by turning it into a database.
Applied Semantics built a unique technology. One of the projects we launched was AdSense. Eventually the market got very excited about AdSense and Google decided it wanted to acquire Applied Semantics for its AdSense product. Google had the same vision we did. That acquisition was completed in 2003 and Applied Semantics became Google Santa Monica.
The next four years after that at Google were a tremendous learning experience where I got to work with some of the most talented people.
It was in my blood to want to build something new. I really enjoyed and gained a lot from being at Google but I feel most in my element in the Wild West when there’s nothing there and no structure and no team and when I work on building something from nothing.
I founded Factual in 2008. I left Google to start Factual because I started to see how important data itself was as an ingredient of innovation. I like the idea that companies large and small can build small products, great apps for example, but they need great data in order to do it.
We’re leveling the playing field by democratizing access to high quality data. The data we decided was most relevant is location data. If you’re building a mobile app and you want that app to understand what’s near me or who’s near me or relevant contextual information, you need the power of location data. Factual provides data to many business and many different apps, almost all of the leading apps.
This is just the tip of the iceberg when it come to location intelligence. You will want your app to not just understand where you are but what you want. It will predict what you want and help you in your daily life.
We’re starting to see products that know that you are going to be on your way to the airport and they know that you skipped lunch and they can see the traffic and can determine if you have time to stop at In-N-Out Burger. With enough data, you can analyze traffic, whether your flight is delayed or the line at In-N-Out. There’s a future where you have an assistant in your pocket.
Editor's note: On April 4, 2018 this article was changed to correct the spelling of alma matter.