It is becoming clear that generative AI exposed to the public must be an adversarial system. From jailbreaks to prompt injection to inherent bias in the models themselves, there is no model on the market today that can be put into customer-facing production, as is, with no supervision. None. Not GPT-5, not Gemini, not WatsonX,…
Summary In today's episode, I explain how to prepare your business for AI agents that will soon shop on your behalf as self-driving apps. Here's what this means for you. By making your website a first-class experience for screen readers today, you both future-proof it for AI agent commerce and unlock up to 10% more…
At this year’s IBM THINK, I had the pleasure of joining fellow IBM Champions Jason Juliano, Steven Perva, and Craig Mullins along with IBMs Luke Schantz, JJ Asghar, Elizabeth Joseph, and the legendary Gabriela de Quieroz for a wide-ranging discussion on AI, data, bias, quantum computing, genomics, and more. Give a watch/listen! Can’t see anything?…
I recently had the opportunity to sit down with Lauren Frazier from IBM to discuss how we go about building trusted AI systems in a fireside chat livestream. We covered a ton of ground. Can’t see anything? Watch it on YouTube here. What is Fair? Fairness is a difficult subject to tackle, because people have…
Summary In today's episode, I sit down with Lauren Frazier from IBM to unpack what it really takes to build responsible and trustworthy AI systems that serve businesses and society fairly. Here's what this means for you. You'll walk away with a practical framework for evaluating whether your organization's AI operates fairly, holds itself accountable,…
Today, let’s take a look at a new offering from IBM, the new AutoAI Time Series Forecasting module. Before we begin, let’s define a few things. What is Time Series Forecasting? Time series forecasting is predicting one or more data variables over some future time, based on previous data. Why is Time Series Forecasting Valuable?…
This week, I had the pleasure of sitting down with IBM Project Debater system lead Yoav Katz for an in-depth chat about how Project Debater has evolved since its debut at IBM THINK 2019 and how it’s being used for the GRAMMY Debates with Watson. What is IBM Project Debater For those unfamiliar, Project Debater…
When it comes to learning data science, one of the challenges we face is just how seemingly daunting the field is to learn. There are so many techniques, tactics, and strategies that it’s difficult to know where to start. Learning something new always begins with an understanding of the basics. From martial arts to dance…
Summary In today's episode, I explore whether you can trust public datasets and pre-trained models from vendors like Amazon and Google to be free of bias in your machine learning work. Here's what this means for you. You gain a risk-based framework for deciding when to build your own model versus when you can rely…
Summary In today's episode, I walk through how to scrape fanfiction data from Archive of Our Own and use IBM Watson AutoAI to predict what drives story popularity. Here's what this means for you. You'll see how exploratory data analysis turns messy scraped data into a testable content marketing hypothesis. You'll also learn these concepts:…
