AI Today Podcast

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...

In order for projects to be successful, the time between concept to execution needs to be reasonably set. Far too often, we see the iteration time of AI projects to be months, if not years, from the initial pilot. Additionally, we see organizations run a proof of concept in a con...

This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. Data is at the heart of AI. It should be no surprise then that proper data management is crucial for AI projects. This podcast is an excerpt from our Cognilyt...

The saying garbage in is garbage out couldn’t be more true when it comes to data being fed into AI and ML models. In this podcast, hosts Kathleen Walch and Ron Schmelzer discuss the importance of data quality and why bad data is a main reason for AI project failure.
Show Notes:
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Organizations are finding that data is only part of their AI strategy. In order to fully utilize their data, they need to be able to make sense of that data and effectively communicate the story their data is telling. In this episode of the AI Today podcast, hosts Kathleen Walch ...