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AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion

Latest episodes

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Nov 26, 2021 • 0sec

AI Today Podcast: Data Science through a Human Lens – Interview with Felipe Flores, host of Data Futurology Podcast

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 podcast he talks about Data Science through a human lens and discusses the human side of data with leaders from across the globe. Continue reading AI Today Podcast: Data Science through a Human Lens – Interview with Felipe Flores, host of Data Futurology Podcast at Cognilytica.
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Nov 24, 2021 • 24min

AI Today Podcast: AI Failure Series – Iteration Time & Proof of Concept vs. Pilots

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 controlled lab setting (why?) rather than a pilot using real world systems. Continue reading AI Today Podcast: AI Failure Series – Iteration Time & Proof of Concept vs. Pilots at Cognilytica.
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Nov 17, 2021 • 24min

AI Today Podcast: AI Education Series: Managing Data for AI

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 Cognilytica Education course “Managing Data for AI”. In this clip we discuss the history of how we stored data in the past and moving from transactional systems to analytics systems. Continue reading AI Today Podcast: AI Education Series: Managing Data for AI at Cognilytica.
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Nov 10, 2021 • 30min

AI Today Podcast: AI Failure Series- Data Quality Issues

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: CPMAI Methodology CPMAI MethodologyIntro to CPMAI webinar AI Today Podcast: AI Failure Series – Data Quantity & Data Understanding Issues AI Today Podcast: AI Failure Series – ROI Misalignment Continue reading AI Today Podcast: AI Failure Series- Data Quality Issues at Cognilytica.
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Nov 4, 2021 • 0sec

AI Today Podcast: From Data Reporter to AI Strategist, Interview with Mara Pometti, Global AI Strategist at IBM

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 and Ron Schmelzer interview Mara Pometti, Global AI Strategist at IBM. Continue reading AI Today Podcast: From Data Reporter to AI Strategist, Interview with Mara Pometti, Global AI Strategist at IBM at Cognilytica.
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Nov 3, 2021 • 0sec

AI Today Podcast: AI Failure Series – Data Quantity & Data Understanding Issues

AI and ML projects revolve around data so it’s important to understand how much data you really need. Understanding how to plan, manage, and operationalize AI & ML Projects is crucial for project success. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer continue the discussion around common reasons why AI projects fail. Continue reading AI Today Podcast: AI Failure Series – Data Quantity & Data Understanding Issues at Cognilytica.
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Oct 27, 2021 • 18min

AI Today Podcast: AI Education Series: Model Evaluation and Testing

This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. When creating ML models it’s important to focus on model evaluation and testing and evaluating AI models vs. the heuristic. This podcast is an excerpt from our Cognilytica Education course “Model Evaluation and Testing”. In this clip we discuss what is overfit and underfit and bias and variance of data. Continue reading AI Today Podcast: AI Education Series: Model Evaluation and Testing at Cognilytica.
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Oct 20, 2021 • 0sec

AI Today Podcast: AI Failure Series – ROI Misalignment

In order for a project to be successful, there needs to be some positive return on the investment (ROI) involved to get this project off the ground and into production. This ROI can be measured by cost savings, but also by people savings, resource savings, and/or time allocation savings. A common reason we see AI projects fail is that the ROI is not justified. Continue reading AI Today Podcast: AI Failure Series – ROI Misalignment at Cognilytica.
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Oct 15, 2021 • 0sec

AI Today Podcast: The State of Ethical AI – Interview with Radical AI Podcast hosts Jessie J. Smith and Dylan Doyle

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 Jessie J. Smith and Dylan Doyle, hosts of the Radical AI podcast. On their podcast they try to probe and advance the field of Artificial Intelligence Ethics so it was only natural to discuss what they see as the most common themes around responsible and ethical use of AI as well as where we currently stand with ethical AI. Continue reading AI Today Podcast: The State of Ethical AI – Interview with Radical AI Podcast hosts Jessie J. Smith and Dylan Doyle at Cognilytica.
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Oct 13, 2021 • 28min

AI Today podcast: AI Failure Series- AI projects are NOT like traditional software development projects

As part of the AI Failure Series, on this podcast, hosts Kathleen Walch and Ron Schmelzer dig into common themes and reasons we have seen why AI projects fail. Why are so many AI projects failing when they don’t need to be? Various sources are quoting AI project failure rates upwards of 70-80%. Continue reading AI Today podcast: AI Failure Series- AI projects are NOT like traditional software development projects at Cognilytica.

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