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Dennis Mortensen | Fixing the World One Startup at a Time
Episode 114th September 2021 • Absolute AI • Innodata
00:00:00 00:42:03

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Welcome to the very first episode of the Absolute AI podcast, where, each week  you will have the opportunity to hear the humans behind artificial intelligence talking about cutting edge innovation and the unique challenges posed by this new technological frontier. The very special guest for this premier episode is Dennis Mortensen, CEO and Founder of, a sophisticated AI platform that solves the problem of scheduling meetings. A serial entrepreneur who built and successfully exited 4 companies as a Founder and CEO, Dennis is also a recognized leader, author, and university instructor in the field of Data Analytics and AI. Today, he delves into this vast amount of experience to pass on wisdom and advice for all to hear.


Dennis begins the interview by sharing the origins of his interest in computer science, his experience of becoming an entrepreneur, and starting He goes on to discuss the technical challenges that he and his team faced at the start, their work in flipping the onus for accuracy onto the client, and the concepts of educating the market and explainable AI. He finishes up by detailing how they set up their system to distinguish between important and superfluous information, and offering his perspective on the future of work. Possessing an innate ability to render the complexities of his work entirely accessible, Dennis shares his experience, knowledge, advice, and thoroughly enjoyable sense of humor with listeners here today – a fitting springboard to this fascinating new podcast.


Episode Highlights:


·   The origins of Dennis’ interest in computer science

·   Becoming an entrepreneur

·   Starting

·   The technical challenges he and his team faced

·   Flipping the onus for accuracy onto the client

·   Pitfalls of educating the market

·   Explainable AI

·   Setting up their AI system in a way to distinguish between important and superfluous information

·   Future of Work

·   Dennis’ vision of the future


Soundbites from the Expert:


The origins of Dennis’ interest in computer science


“One day on the telly, they showed an old movie called Wargames, you might not remember it, but that really touched me.”


Becoming an entrepreneur


“The only reason that I briefly thought I would make a small entrepreneurial run was that the company that I worked for in college went bankrupt.”


“What I'm trying to do instead is just walk around, look at my life, and take note if there are things that don't work the way they should, or to the point where I actually get annoyed or disappointed.”




“Any startup is usually one of two challenges…either a tech/science challenge of some sort, or a market challenge.”


The technical challenges he and his team faced


“There's no way I can ever come up with any model that will be able to kind of predict anything if I don't even know what the end of this list looked like.”


“It's not as black as white as as this, but there's probably two types of AI sort of types of predictions that you could make. There’s low accuracy predictions for where whatever prediction you make, it is of value. Then there’s high accuracy predictions, where if you don't reach a certain kind of threshold, anything which you make, it's really not of value.”


Pitfalls of educating the market


“I'm just saying that if you're in a position where you need to kind of reframe it and rewire the full population of your uses, that is scary. You should try to avoid that at all cost.”


Setting up their AI system in a way to distinguish between important and superfluous information


“So we had this kind of deterministic decision engine, that, upon feeding it with the information, could figure out what is the next step. And we then designed that and that was deterministic, from beginning to end.”


Future of Work                                                                                                                                           


“I do think you will extend your team with a pool of intelligent agents, and it'll be on you to figure out who to hire, how to train them, how best to deploy them, on failure how to best terminate them and find new agents.”

“Think of it more like professional sports, where you have a skill set and you deploy that with different teams for different seasons, to win different trophies. And you might even play for multiple teams at the same time, and that will not be abnormal.”

“It's not just the companies that have to change, it's the support system of the whole society that would have to shift to this new way of living and working.”