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.

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.

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.

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.

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.

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.

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.

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 Sanyam Bhutani, host of Chai Time Data Science podcast. As his podcast talks about Data Science, he shares with us where things really stand in enterprises with data science, some of the biggest trends emerging in data and data science today, and some of the mundane but crucial aspects to data science that people need to be aware of.

Continue reading AI Today Podcast: Data science in the Enterprise: Interview with Sanyam Bhutani, host of Chai Time Data Science podcast at Cognilytica.

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 Alexandra Petrus, host of the Applied AI Pod. On her podcast she talks to anyone who is applying AI today including startup founders, startup engineers, AI community leaders, research scientists, innovation leaders, product builders, passionate AI practitioners.

Continue reading AI Today Podcast: Insights into the AI Startup Scene: Interview with Alexandra Petrus, host of the Applied AI Pod at Cognilytica.

This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. There are many paths to data science and different skills are needed for creating successful data scientists. These skills include curiosity, analytical thinking, performing analysis, taking a strong position and arguing that position, being a data driven problem solver, having an impact-driven mindset, and being good at storytelling.

Continue reading AI Today podcast: AI Education Series: Thinking and Acting Like a Data Scientist at Cognilytica.