Dan McCreary: Jellyfish, Flatworms, and the AI-Ready Enterprise – Episode 1

Dan McCreary Dan McCreary has years of experience selling AI solutions to executives. He uses a metaphorical story to show the importance of making your enterprise as intelligent and nimble as possible. His story of the the evolutionary heritage of jellyfish and flatworms seemed to me like a great way to kick off this new podcast. We talked about: the importance of helping an executive audience visualize the benefits of any technical solution, in particular the role of storytelling that will help your message stick the jellyfish and flatworm metaphor that he uses to help executives visualize their competitive environment how a knowledge graph lets companies build internal maps of their company and environment how a knowledge graph can enable micro-personalization how adding precision to a model improves your ability to predict customer behavior his simple description of embeddings: a way that we find when two things are similar his take on the benefits of labeled property graphs over knowledge graphs the idea of "reference frames" articulated by Jeff Hawkins and how knowledge graphs come closest to modeling them how three main ways of representing data - neural networks, knowledge graphs, and reference frames - are all based on graph network models the importance of freeing data from spreadsheets to enable the full productivity benefits of AI his insight that knowledge representation is the hardest part of AI Dan's bio Dan McCreary is a solution architect focusing on AI and generative AI architectural patterns. In the past, he worked at Bell Labs with the creators of the UNIX operating system, with Steve Jobs at NeXT Computer, and founded his own consulting firm with over 75 employees. His background includes topics such as scale-out enterprise knowledge graphs, high-performance computing, and NoSQL databases. He is the co-author of the book "Making Sense of NoSQL" and is a frequent blogger on AI strategy. He has been closely following the growth of knowledge graphs and generative AI. He is a huge fan of GPT-4. Connect with Dan online: LinkedIn Video Here’s the video version of our conversation: https://youtu.be/SwK73iQ7_j8 Podcast intro transcript This is the Content and AI podcast, episode number 1. As I was getting ready to launch this new show, Dan McCreary shared on LinkedIn a story that he uses to help executives understand why they need a smarter approach to their data and knowledge management. I always appreciate a good origin story - especially when I'm in the process of starting something new - so his comparison of the evolutionary heritage of jellyfish and flatworms resonated with me. I hope you like the story, too, as well as Dan's take on knowledge representation, which he thinks is the hardest part of AI. Interview transcript Larry: Hey everyone. Welcome to episode number one of the Content and AI podcast. I'm delighted to start off the series with Dan McCreary. Dan is an AI consultant based in Minneapolis, Minnesota in the US. Welcome to the show Dan, tell the folks a little bit more about what you're up to these days. Dan: Thank you very much for having me. I have been working on the field of knowledge representation for most of my career. My background is - early on I did chip design for Bell Labs. I worked in the super computing industry, worked for Steve Jobs for a couple of years, and then I've been doing a lot of starting my own companies and consulting. And then I just recently left a Fortune five healthcare company where I ran a generative AI center of excellence there. Larry: Nice. Yeah, so you've been doing this stuff for a little while and that's why I wanted to start off. I've been thinking of launching this podcast for a couple months now, and I saw this article that you wrote that said, "Aha, there's my trigger here. Let's go." You wrote this brilliant piece that you've been kind of shopping around because just for everybody's background, Dan has been explaining to executives for decades about how to get the most out of computers and computer stuff. And his latest thing - as an AI consultant - is helping people understand where to make smart investments in AI. And so he's been looking for ways to explain that he came up with this brilliant metaphor of the jellyfish and the flatworm. Tell us about that, Dan. Dan: Well, first of all, anybody who's in technology and has an intimate understanding of how bits move across networks and then goes into a room full of executives who maybe have a finance background or a healthcare background but can't visualize the difference between two databases, you can get very quickly frustrated trying to guide them. And one of the things that I've always learned is that if your audience can't visualize what you're trying to explain, they won't make the right decisions. AI today, say your executives are pondering a million or a 10 million or $100 million investment, they have to be convinced that it's the right thing. And what's interesting is they'll often have you in a one-hour consulting meeting and then they're going to go away. And the question is what will they remember? They're not going to remember data and facts and bites and bits and all this stuff, but they will remember a story if that story attaches to their emotional memory. Dan: We think of emotions attaching memory to our brain. And so the idea here is to develop a compelling set of stories that when you're not in the room, they can talk about it and they can say, "Hey, are we a jellyfish or are we a flatworm?" And then they'll make the right decisions if you give them the right metaphors, right? So that's the whole thing about being a good thought leader is having really good stories. By the way, they have to be accurate. You can't just make things up. They have to be able to talk to their friends and say, "Hey, do you understand Dan's jellyfish flatworm story?" And they have to say, "Yes, that makes sense," but well, let me just tell you the story real quick. Okay. So in the evolution of animals on planet earth, about 600 million years ago, we had two animals. Dan: One, the jellyfish and the jellyfish live in a very simplified open ocean environment and they have to have a very simple set of rules. And they just hope that by following those rules go towards light, go down in the dark if there's prey around very simple rules to hope that fish wander into their tentacles. On the ocean floor, though, the world was very different where these flatworms were crawling around and they had to know how to move towards their prey or they were often considered the first hunters and also avoid their predators. So they had to remember things and they had to remember maps of where the good places to go and where the bad places code. And they had to have complex rules so that if they turn around, they're going to move away from their predators. So motion is complicated. It really tells you about you have to have a map of the world around you. Dan: That's the flatworm. And most scientists say that the flat one was probably the very first animal to have a central nervous system. And most of other animals that move around their environment evolved from that. So I use that as a metaphor for asking companies to understand, are you floating in a competitive environment that's simple? Do you sell one product to one consumer and you have no competitors? Right? And there are a few companies that do that, right? They're specialized manufacturers, they make one part, they sell it to another manufacturer, they get the same contract every year. They're very good at what they do. They're so specialized, they don't have competition. They have a simple world. They don't need to have a huge massive IT department to simulate their competitive landscape. But in the real world, you have many products. You often sell to many different types of consumers, and every one of your products may have a hundred different competitors. Dan: That's a complex world. That's not like a simple jellyfish that floats in the open ocean. That's a flatworm company, a company that has to start to take an understanding of the world around them and build internal maps. And by the way, there are companies that do have IT systems. You've got an IT system that runs your website, it has a log of who's coming to your website. There's a search field you can store who's searching for what on your website. You have your customer relationship management system, you have your sales system, you have your commission system, you have your product management system, you have your inventory system. You got all these systems, and they're all little silos. And what we've learned is that if you want to have intelligent agents that help knowledge workers make decisions, putting a hundred data silos in the cloud is not going to help you build intelligent agents that are helping your knowledge workers get their jobs done. Dan: What we need is to be like the flatworm where we centralize knowledge in a brain, our central nervous system as it were. And the manifestation of that is a knowledge graph where you can model the complexity of the real world in all of its detail to make good decisions and make good predictions about, hey, if I introduce this product, this is going to be a change in revenue. If I see this change happening in these products, here's my prediction of why it's happening. All of those things, if you have all your data spread across these silos, you're not going to be able to have intelligent agents. So the way I say this is that if you want to be a flatworm company, you need to centralize your knowledge in a knowledge graph and you need to use all of the power of modeling the outside world to precisely predict your customer's behavior. Does that make sense? Larry: That makes perfect sense. And what I love about one thing,