Florian Douetteau
29 statements across 6 episodes · 9 bullish · 2 bearish · 1 people on the record · first statement Apr 13, 2016 by Florian Douetteau · across every show →
On the record as a speaker too: Florian Douetteau's record, appearances and statements → this page counts the times other people say the name.
Everything said about Florian Douetteau, oldest first
Apr 13, 2016
Douetteau: Effective data teams must bridge visual interfaces and programming
“In my perspective, well, whatever happens today, you must be able to make the two mindsets coexist, meaning when you work with computers today, you have people which are more into the coding kind of mode, meaning a textual interaction with computers, and peopl…”
Apr 13, 2016
Douetteau: Winning companies will excel at putting predictive models into production
“So it might be that in the following decade, about, where everything will be about having intelligent connected devices, a company that will win will be companies that will be very good at putting predictive models in production, putting intelligence in produc…”
Apr 13, 2016
Apr 13, 2016
Douetteau: Algorithmic optimization accounts for only 20% of a data project
“When you do have the data, and you do have the real business problem you want to solve, it's like you already did, like, half of the job, and so maybe you spend, like, more, 30 more percent actually working on the domain-specific or problem-specific features y…”
Sep 17, 2018 negative
Douetteau: Airflow and JupyterLab don't go far enough for enterprise data science
“Those two projects are, like, very interesting, but to some extent don't go far enough, because what you really want, at the end of the day, is the ability to capture, within the platform, everything related to, ah, to your data science project.”
Sep 17, 2018
Sep 17, 2018 negative
Sep 17, 2018 positive
Douetteau: Enterprise data science fails without combining business insights with technical expertise
“Data science is actually a mix of business and tech, and the challenge is actually to make business people and tech people get on board in data science together and work collaboratively on project, because you cannot really deliver data science without having …”
Sep 17, 2018 neutral
Apr 27, 2021 positive
Apr 27, 2021 positive
Jul 5, 2023
Simple ML models on real data easily outperform traditional business rules
“In many businesses applying models that are actually not so complicated, but like, still being, you know, with real life data and with a large amount of data, you outperform your previous business rule by a significant margin.”
Jul 5, 2023 neutral
Companies will adopt AI governance and self-assessments ahead of formal regulation
“I think that many companies will have to adopt this kind of systems a little bit ahead of time in order to manage some of the internal expectation in terms of control of AI or expectation on their customers, but also in order to be more ready when the complian…”
Jul 5, 2023
Technical founders should not attempt to become sales or communications experts
“When you come from a technical technical background, you won't become like a service person or a communication person. They want, and maybe it's actually not an objective to become. So you have to stay a little bit what you are, because ultimately you have to …”
Jul 5, 2023 bullish
Most companies will run hundreds of AI automation systems within ten years
“I think that in the next five to 10 years, it will be actually Universally mainstream, as in most companies, a very vast majority of companies will have hundreds, if not thousands of automated systems that automate ordering and some form of cash management and…”
Jul 5, 2023 positive
Future enterprise software will seamlessly combine visual, text, and code interfaces
“I think that there would be, there is a future of, let's say, Enterprise software where you've got system of exist mix of visual and text and potentially coding representation of things where you can navigate between code and clicking and talking to your compu…”
Mar 20, 2024 positive
Mar 20, 2024
Dataiku CEO: Deploying enterprise GenAI is currently trial-and-error 'dark science'
“Because if we're, again, a bit honest, it's not that easy to make generative AI application work in practice. We are playing a little bit dark science there, where you get your LLM, your fine tune, your rag, your stuff around. And you decide, like, okay, good,…”
Mar 20, 2024 neutral
Dec 12, 2024 positive
Dec 12, 2024 neutral
Douetteau: Silicon Valley groupthink would have killed Dataiku's platform strategy
“A thing that it required then some will or independence of mind, which was easier for us because I'm not sure if I have had the will or the mind power to Keep this line of thinking if I had been in the Bay Area. Because around me, everyone would have had a dif…”
Dec 12, 2024
Douetteau: Building a mature tech company takes 20 years
“I think it's at least 20. I mean, I think it's almost, it's probably very comparable to the number of years in order to get a kid in or even out of college, in and out of college, and maybe being being financially independent, you know? That's kind of like the…”
Dec 12, 2024 bullish
Douetteau: Enterprises must build proprietary AI agents to differentiate
“Then enterprise, in order to differentiate and be, transform themselves, will also need to build their own agents. On everything which is about stitching together the data from one vendor to the other, or the overall process, or the thing they actually built, …”
Dec 12, 2024
Douetteau: AI model quality won't be the key bottleneck in 2-5 years
“I, for instance, don't think that the problem two years or five years from now of agents will be relevance, per se, as in the quality of the models. The problem will be very boring stuff, such as, is it the right data, or have we actually updated the data for …”
Dec 12, 2024
Douetteau: Analytics metrics in data-driven enterprises get reused for up to ten years
“If an enterprise is Becoming data-driven or AI-driven, it means that every piece of analytics is actually bearing lots of value long term because you're rebuilding lots of intelligence in your company based on this. Even if it's a simple metric that you're bui…”
Dec 12, 2024
Dec 12, 2024 neutral
Dec 12, 2024
Douetteau: Adding data scientists does not bridge the enterprise business-data gap
“It should not be solved by adding more data scientists, because anyway, there's not enough data scientists, and if they don't understand the business, there's no point. It should be solved by finding a way for people from the business that are very much into d…”