If you’ve been around marketing, you'll have heard the phrase "customer journey." It's what people do when they buy ... or don't buy.

Naturally, marketers want to optimize that trip, and Adobe has developed an AI system that finds out where those journeys break. Theoretically, that will help brands sell more.

Our guest this episode: Steve Hammond, a director at Adobe Experience Cloud.

Can AI help us connect trillions of smart devices? There are currently perhaps 20 billion devices connected to the internet: things like laptops, phones, smartwatches, TVs, smart speakers, smart home devices ...

In a decade, that could be 50 billion … and a lot of it is enterprise IoT.

In this edition of the The AI Show with John Koetsier we chat with Intel and the National Science Foundation, which has funded $30M+ into projects to use AI to figure out how we'll manage ultra-dense wireless networks ... how we'll keep it secure, and how we'll keep everything connected.

Joining me in this episode:

Vida Ilderem, VP, Intel Labs

Thyaga Nandagopal, National Science Foundation

Pu Wang, University of North Carolina at Charlotte

Can AI generate music that’s worth listening to?

In this episode of The AI Show with John Koetsier we explore music created by artificial intelligence. Music is one of our oldest art forms, and we think of art as creative ... we think of people as creative.

What about computers? Or AI?

It might surprise you: I’ve been listening to AI-generated music for much of the past few days.

In this episode we chat with Edward Balassian, the CEO of Aimi.fm. 

If your AI chip requires a life support system, you know you're doing something pretty funky.

In this episode of The AI Show with John Koetsier, I talk to the CEO and CTO of Cortical Labs, who are combining mice neurons with silicon chips, then training their system to play ping pong.

Almost all AI uses silicon chips ... that’s the “artificial” in Artificial intelligence. Brain Chip One uses biological components for potentially faster learning systems.

Is biological computing the future of AI?

And, will it some day be literally correct to say ... "my computer died?"

Does artificial intelligence have a sense of smell? Welcome to The AI Show with John Koetsier

Plenty of AI systems are built to solve simple problems, like sorting Legos of different colors and shapes. Intel is building AI chips with neuromorphic architecture. Intel's goal: solving complex real-world problems.

And, doing that with less training: sometimes even just one training sample.

In this episode, we chat with Mike Davies, the director of the Neuromorphic Computing Lab at Intel.

Will AI replace software developers? Or just make software development much easier and quicker?    

I chat with Antonio Alegria, Head of AI at OutSystems, about a shipping technology in which AI helps software developers write code faster, make fewer errors, and .... believe it or not ... get few repetitive stress injuries.  

We talk about:  

- agile development 

- graph neural networks  

- code X-ray  

- hybrid AI  

- probabilistic vs deterministic models  

- predictive AI  

- development help for novices  

- development help for experts  

... and much more.

Ever been shadow-banned? Ever wondered if an algorithm is changing your perception of reality? We talk about AI's black box problem and much more in this episode of The AI Show.

What happens when you don’t know why a smart system made a specific decision?  

Today’s guest chairs the Ethics Certification Program for AI systems for the IEEE standards association. She’s also the vice-chair on the Transparency of Autonomous Systems working group. She’s on the AI faculty at Singularity University … she’s an author ... and she’s been a judge for the X-Prize.  

Her name is Nell Watson.  

We’ve probably all heard the stories about this ... in one, an image recognition system distinguished between dogs and wolves because all the wolf photos it was trained on also had SNOW in the background. Clearly, that’s a system that will fail in other circumstances …   

But unless you know why an AI system is doing what it’s doing, it’s pretty hard to fix. So today we’re talking about transparency in AI.  

How important is it to know why a smart system made a decision … and, can we engineer know-ability into all our AI systems?

Larry Pizette, Head of Data Science for Amazon’s Machine Learning Solutions Lab., reveals the 3 biggest mistakes companies make when they're building smart systems.

Welcome to the first official episode of The AI Show, brought to you by VentureBeat and hosted by John Koetsier. 

Our topics:

 - how to get started

 - training engineers ... AND executives!

 - kicking off AI projects when you do NOT have a lot of data

 - the top 3 mistakes companies make when implementing AI

 - where AI is now on the continuum from build-it-all-from-the-ground-floor to no-code

 - the most innovative uses of machine learning he's seen (think NFL!)

 - and much more ...

Chatting with Marcio Avillez from CUJO AI, which manages over 500 million devices daily for clients like Comcast, about AI solutions to monitor and protect security, control, and privacy.

Intro to show

The AI Show is a live video broadcast to our community on YouTube, Facebook, Twitter, and LinkedIn. It's also a story on VentureBeat. It's a podcast as well. And it's all of them at once.

There is a revolution happening in AI and ML across business, and across the workforce, that is profound, and it will totally change the way we do work within the next decade, says VentureBeat CEO and editor-in-chief Matt Marshall.

This is the podcast that will document that revolution.