ABOUT THIS EPISODE
How do you build intelligent systems that people trust? Then, how do you keep that trust when things go wrong? Because when things do, it’s not the tech that loses face but the brand people relied on.
This episode was taped before a live audience on stage at the HumanX Conference in San Francisco.
We Meet:
Radha Basu, Founder & CEO of iMerit
Shuman Ghosemajumder, Co-founder & CEO of Reken
Andrea Thomaz, Co-founder & CEO of Diligent Robotics
Credits:
This episode of SHIFT was produced by Jennifer Strong with help from Emma Cillekens. It was mixed by Garret Lang, with original music from him and Jacob Gorski. Art by Meg Marco.
English
United States
IN THIS EPISODE
TRANSCRIPT 🔗
Are you the producer of this podcast?
Add a podcast transcript
Need Audio-to-Text?
Transcribe with Listen411 in Just 60 Seconds
OTHER EPISODES IN THIS PODCAST
From Las Vegas, where AI and security conferences are putting agentic risk front and center, we explore the identity crisis inside enterprise AI, and what it means to have machines managing machines.
We Meet: SailPoint President Matt Mills
Credits:
This episode of SHIFT was produced by Jennife…
What if you could build solutions that unlock entirely new realities for millions of people? Aiming for something so big and so audacious that it seems almost impossible to imagine is often referred to as a moonshot. And what might it mean if a big part of what’s standing in the way of your moonsho…
What’s an astronaut’s time worth? Answering that question is not a perfect science, but at more than $100,000 an hour (not counting salary - that's just to keep one alive) on the International Space Station, it’s safe to say it’s more than you want to pay for bagging up trash.
This week, we take a…
For as far as we’ve come with AI and robotics, there’s still a huge gap when it comes to combining the two. AI excels in the digital space, and in the physical world, robots are often pre-programmed. That’s where physical AI comes in. It’s critical for things that can’t tolerate the kinds of mistak…
Water shows up at every stage of the AI supply chain: to manufacture chips, to generate the power that runs them, and then more water to cool the chips in data centers. It's believed that AI's water needs by 2030 could roughly match the drinking needs of the entire United States, and less than 5% o…
Disclaimer: The podcast and artwork embedded on this page are from Jennifer Strong, which is the property of its owner and not affiliated with or endorsed by Listen Notes, Inc.
EDIT
Thank you for helping to keep the podcast database up to date.
