The more specific a piece of data, the less useful it is in forecasting. This is a maxim of predictive analytics. Predicting audience behaviors based on the year they were born is useful. Predicting audience behaviors based on individuals’ exact birthdays is not useful. Which is why, in OpenAI’s newest paper on hallucination in generative…
Summary In today's episode, I examine the dangers of connecting generative AI tools to your file systems. Here's what this means for you. You safeguard your most important documents by establishing strict access boundaries. You'll also learn these concepts: how to implement isolated sandboxes, why you should use file copies for testing, and how to…
When it comes to reporting with data, especially quantitative data, in generative AI, you have to answer a critical question: Are we using the data for the report, or in the report? This seemingly pedantic question is vitally important. Will the data be used in the report itself, or will the data be used to…
Dharmesh: Today: BYOD (Bring Your Own Device) Tomorrow: BYOA (Bring Your Own Agents) More and more people will be building their own agents to increase their personal productivity. And, they will take that “team” with them to their next job. I can also imagine a day where companies will gravitate towards hiring people that have…
Summary In today's episode, I explain how to use AI to transform a raw list of URLs into a human-readable format that includes summaries and titles. Here's what this means for you. You can automate the tedious task of manual browsing to create enriched datasets with ease. You'll also learn these concepts: why the ChatGPT…
Summary In today's episode, I discuss the strategies for protecting intellectual property when using generative AI. Here's what this means for you. You can integrate cutting-edge AI into your workflow without risking the exposure of sensitive company data. You'll also learn these concepts: how to audit terms of service, why free AI tools pose significant…
Summary In today's episode, I walk through the AI-ready data quality audit, covering the three levels of data quality assessment, the 6C Data Quality Audit Framework, and why AI systems fail without high-quality data. Here's what this means for you. You'll gain a practical diagnostic approach to catch small data issues before they compound into…
