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In the previous episode we briefly mentioned the Data Mesh. In this one, we look into in detail. We answer four questions:

1. What is a Data Mesh and how is it different from the Data Warehouse, Data Lake or Data Lake-house that we’ve been discussing so far?
2. Why do I say that most enterprises, at this point in time, shouldn’t be investing in the Data Mesh?
3. How can we tell if we’re one of the few enterprises that should indeed be pursuing this idea right now?
4. If we’re not, can we capture any of the benefits of the Data Mesh without actually implementing one?

Is it right for your company...listen in and draw your own conclusions.

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Most companies have a Data Warehouse to some degree already, some have delivered more value than others, but these days the chatter is mostly around Data Lakes instead. What's the difference and which, if either, should today's Enterprises be investing in? Is there a middle ground between the two worth pursuing? Spoiler alert: the answer is yes and we'll be talking about it in this episode.

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What if I told you that you could unravel the mysteries of generative AI, and ChatGPT in particular, through the eyes of a Stochastic Parrot? Join me, your host Michael R Gilbert, as we embark on an exciting journey into the world of generative AI, exploring its capabilities and contemplating the potential dangers hidden within this powerful technology.

Together, we'll dive deep into the concept of word distance, essential for encoding context and understanding language. Our AI parrot example will guide us through a fascinating exploration of probability frequency and how it influences the AI's responses to prompts. We'll also discuss the implications of generative AI, its ability to create new content never seen before, and the challenges that come with it. By the end of this episode, you'll have a better grasp of generative AI's power and potential pitfalls, as well as a newfound appreciation for our stochastic feathered friend.