As the markets for Data, Automation, Analytics, and AIcontinue to evolve, so too does Cognilytica's coverage of these areas. In today's podcast we discuss how we are expanding our current Cognilytica

In order for many machine learning algorithms to be trained, especially supervised learning algorithms, they need to be fed relevant data along with the desired meaning of the data. In this episode of

On todays AI Today podcast hosts Kathleen Walch and Ron Schmelzer are going to do their annualAI Market Forecast & Trends. They will spend some time reflecting on what they are seeing in the market

With 2021 quickly fading into the rear view mirror its time to do our annual yearly AI recap. On todays podcast hosts Kathleen Walch and Ron Schmelzer are going to take a look back at 2021 as it rel

AI is not new - in fact the term was coined in 1956. Why then, if it's been around for decades, and we are now on our third major wave of AI interest and hype, do we keep making the same mistakes that

Earlier in 2021, The National Security Commission on AI (NSCAI) published their final report that presents the NSCAI's strategy for winning the artificial intelligence era and provides a strategy to g

For anyone following AI, it should come as no surprise that countries around the world are taking a vested interest in AI. In 2021 the NSCAI published their final report explaining the steps the Unite

It's important for organizations to understand all that's involved that goes into the model. A common reason that AI projects fail is that the team does not understand the model and data lifecycle. In

AI is not the solution to all problems. And, not every vendor solution solves your problem, regardless of what they may tell you. In this episode of the AI Today podcast hosts Kathleen Walch and Ron S

Far too often, organizations move forward with AI projects without having a clear understanding of how their AI and ML models are going to be used in the real world. This lack of real world understand