Summary In today's episode, I debunk the claim that generative AI will implode from ingesting its own data and explain why the math actually points in the opposite direction. Here's what this means for you. You can stop worrying about model collapse and instead understand how synthetic data is likely to make future AI tools…
In today’s episode, you’ll explore the intriguing paradox of why marketers, despite having access to vast amounts of data, often struggle to extract meaningful insights. You’ll discover the crucial role that well-defined questions play in guiding data analysis and learn why simply having data isn’t enough. I’ll share a practical framework that helps you transform…
In today’s episode, we’re tackling a truth that can be unsettling for many marketers: sometimes, your data is just plain wrong. You’ll learn why discrepancies in your analytics are more common than you might think and why that’s not necessarily a reason to panic. I’ll explain the difference between “reliably wrong” and “unreliably wrong” data…
Almost Timely News: 🗞️ Building a Synthetic Dataset with Generative AI (2024-04-28) :: View in Browser 👉 Did you miss my webinar this past week on generative AI for agencies? Go catch the free replay! Content Authenticity Statement 100% of this week’s newsletter was generated by me, the human. Learn why this kind of disclosure…
Summary In today's episode, I walk through how generative AI applies to analytics, which tools work best for different tasks, and the not-so-secret trick to using AI effectively with your data. Here's what this means for you. You discover that these AI tools are language prediction machines, not math calculators, so pairing them with actual…
Summary In today's episode, I share highlights from a live Q&A on generative AI transparency and the practical tools associations can use to handle structured data. Here's what this means for you. You'll walk away with a framework for building trust around AI use and a method for turning AI into a coding assistant for…
In today’s episode, I answer the question, “What is the difference between great data and good data or great data and data?” I explain how data is like the ingredients for cooking. Good data enables quality results, but bad data ruins everything. To find out more about the key role data quality plays in AI,…
Summary In today's episode, I break down the difference between great data, good data, and bad data, and why data quality matters more than tools or talent in AI applications. Here's what this means for you. You will see why feeding AI high-quality data is the single biggest factor in producing reliable, valuable results, no…
Summary In today's episode, I break down two architectural approaches for building large language models that handle tax and accounting data, including the trade-offs of each. Here's what this means for you. You get a clear framework for deciding whether to fine-tune a model or build an interpreter that connects to an up-to-date data source.…
