Carlos F. Gaitan Ospina is the Founder and CEO of Benchmark Labs, which provides IoT-based weather forecasting solutions for the agriculture, energy, and insurance sectors worldwide using proprietary machine-learning software.
Chad talks with Carlos about creating the company, the hardware they're producing and what it is doing, and where the machine learning comes into play.
Benchmark Labs (https://www.benchmarklabs.com/)
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Transcript:
CHAD: This is the Giant Robots Smashing Into Other Giant Robots Podcast, where we explore the design, development, and business of great products. I'm your host, Chad Pytel. And with me today is Carlos Gaitan, the Founder and CEO of Benchmark Labs, which provides IoT-based weather forecasting solutions for the agriculture, energy, and insurance sectors worldwide using proprietary machine-learning software. Carlos, thank you very much for joining me.
CARLOS: Thank you for the invitation, Chad. It's a pleasure to join you here.
CHAD: You work in a variety of different industries with weather forecasting solutions using machine learning. I'm really curious, at a high level, how did you get to where you created Benchmark Labs today?
CARLOS: Oh, thank you, Chad. That's a great question. I think that in many ways, it's a combination of life experiences and lots of user feedback. As a background, my mum worked for 28 years in the National Federation of Coffee Growers in my native Columbia. And we experience basically the effects of weather, La Niña, El Niño, local conditions, pests on the coffee growers. I remember growing up looking at the price in The New York Stock Exchange if the pound of coffee was going to be more than $1 or not [laughs] and so on.
So, you know, we had a very severe drought in Colombia, and Colombia was heavily dependent in hydropower at that time. And I remember that we even had to study with candlelight and move to a spring savings time for the first time in the country. The country is in the equator, so you can imagine moving the clock was unheard of. So since then, I was always passionate about hydrology, the water cycle, why this happened, how weather can affect the economy at that level that people have to change their working habits.
I did civil engineering hydrology, then studied these new applications of machine learning technologies, hydroinformatics, did my studies there in Columbia, my bachelor's, my master's. Then I was fortunate to go to The University of British Columbia to study my Ph.D. in Atmospheric Sciences. And then, after I finished, I moved to The United States to work at the Geophysical Fluid Dynamics Laboratory in Princeton with close collaboration with the NOAA, the USGS.
And that gave that perspective also of understanding how weather climate models were done at the Department of Commerce level but also to understand the users on how they interact with weather data or climate data and what were the needs that they were expecting from the National Weather Service and the Department of Commerce and NOAA that not necessarily were fulfilled with the current information.
So then I moved to the private sector, joined a hardware company, and met my co-founder of Benchmark Labs there then moved to California to work on consultancy of climate change assessments. But since the time at the Department of Commerce, it became very clear that what farmers and what users wanted was weather information that was more actionable, that was tailored to their specific