AI Today Podcast

As the markets for Data, Automation, Analytics, and AI continue to evolve, so too does Cognilytica’s coverage of these areas. In today’s podcast we discuss how we are expanding our current Cognilytica Classification of the AI Vendor Ecosystem to include a data infrastructure laye...

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 the AI Today podcast hosts Kathleen Walch and Ron Schmelzer provide an overview...

On today’s AI Today podcast hosts Kathleen Walch and Ron Schmelzer are going to do their annual AI Market Forecast & Trends. They will spend some time reflecting on what they are seeing in the market and where they forecast the AI markets will go in 2022. They will talk about the...

With 2021 quickly fading into the rear view mirror it’s time to do our annual yearly AI recap. On today’s podcast hosts Kathleen Walch and Ron Schmelzer are going to take a look back at 2021 as it relates to AI and share some of the hottest news from the past year, including acqu...

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 have brought us to two previous AI Winters? Are we still overpromising what AI ...

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 get the United States AI-ready by 2025. On this episode of the AI Today podcast h...

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 United States must take to responsibly use AI for national security and defense, defe...

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 this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer dig...

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 Schmelzer continue the discussion around common reasons why AI projects fail. In ...

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 understanding is a major reasons why AI projects fail. In this episode of the AI Today pod...

Countries across the world are understanding that they can take advantage of the tremendous transformation presented by AI and cognitive technologies and position themselves for global competitiveness in the future. As a result, countries are coming up with their own unique AI st...

On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Felipe Flores, host of Data Futurology Podcast. On his podca...