I dropped out of my PhD programme and entered the start-up world when I was 20. I led an R&D team at Exalead, a search engine tech company, until it was bought out. Then I acted as CTO at IsCool, a European leader in social gaming, while freelancing as a lead data scientist at various companies. I went through some successful transitions and some really painful downsizings. But, for all the ups and downs, It brought me to a place where I founded Dataiku. As a maths guy, doing data science now is like getting back to my first love.
Watching Dataiku grow and evolve has been my highlight. Sure, the big wins are exciting - we just announced a $101 million Series C round - but more than that, it’s thrilling to see the team grow, the product improve, and our customers’ successes in action. We have over 200 cross-industry customers now from around the world, supported by a talented team that’s taking on cutting-edge machine learning technology and ethical issues surrounding prevalent AI. Starting Dataiku was the best career move I made and guiding it through its evolution is a joy.
Data is obviously critical for successful ML and predictive analytics, but at the end of the day, it is old. Quantum and neural computing are redefining everything we know about software and hardware. I’d tell my younger self to study these fields and learn as much as possible.From my perspective, 2018 was a big year of humility in the AI technology world. In spite of great progress and success in the space, it's become evident that AI won't solve most of the very human issues that contribute to the growing chasm between people. But I think it is still possible (and imperative) that we try not to create new problems with the AI tech we’re developing in 2019. We can combat social isolation, discrimination and more, but only if we’re intentional about it and make it a priority.
Today, there is a pretty sizeable gap in terms of AI in business domains. Smart cars aren’t sci-fi anymore, computers can win GO, and there's a talking AI assistant in each of our homes. But AI for the enterprise looks comparably pretty primitive. My expectation for 2019 is that we start filling this gap and pushing businesses to incorporate data-driven insights into their organisational framework and maybe get them a bit more cutting-edge, too.
We have a fantastic team of people focused on finding talent across data science, AI and engineering disciplines. At Dataiku, we try to keep a good balance between finding fun and meaning in our job, while being a bit obstinate about precise technological excellence. We’re also growing very fast and are focused on maintaining our unique culture, which I think helps - we like working here and we think it shows during recruitment.
Recent analytical evolutions and events in data abuse made people at all levels more self-conscious about data. I'm more optimistic that a sense of responsibility around the ethical use of AI in the enterprise can grow at the same pace as the evolution of technology.Data and analytics technology/service provider