This podcast episode discusses the importance of understanding analytics and data visualization in AI projects. It explains key terms such as descriptive, diagnostic, predictive, and projective analytics and highlights the tools and methods used for each. Understanding these concepts is crucial to the success of AI projects.

AI systems have the potential to provide great value, but also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough. You need to know how to build, use, and interact with these systems ethically and responsibly. Additionally you need to understand that Trustworthy AI is a spectrum that addresses various aspects relating to societal, systemic, and technical areas. Continue reading AI Today Podcast: Trustworthy AI Series: AI System Transparency at Cognilytica.

Jeff Eason, project manager specializing in AI and ML projects, discusses lessons learned from AI project management at Salt Lake County Health Department, including challenges of data quality, governance, and privacy. The importance of data access and management in AI projects is emphasized, along with the value of learning from failures. Real business problems solved with AI, ROI of AI projects, and future integration of AI into daily lives are also discussed.

The hosts discuss different series and interviews. They explore diffusion models and image generation in AI, including infilling, style transfer, and super resolution. They compare diffusion models to large language models. They also discuss generative AI techniques for image generation such as image to image transformation and super resolution.

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Data, Dataset, Big Data, DIKUW Pyramid, explain how these terms relate to AI and why it’s important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary AI Glossary Series – DevOps, Machine Learning Operations (ML Ops) AI Glossary Series – Automated Machine Learning (AutoML) AI Glossary Series – Data Preparation, Data Cleaning, Data Splitting, Data Multiplication, Data Transformation AI Glossary Series – Data Augmentation, Data Labeling, Bounding box, Sensor fusion AI Glossary Series – Data, Dataset, Big Data, DIKUW Pyramid Continue reading AI Today Podcast: AI Glossary Series – Data Warehouse, Data Lake, Extract Transform Load (ETL) at Cognilytica.

The podcast discusses the importance of responsible AI and highlights the need to consider laws, protect privacy, and ensure safety. It emphasizes the importance of open evaluation and reevaluation of AI systems and explores practical steps for implementing responsible AI. The hosts also introduce the Trustworthy AI Series and promote a free intro to trustworthy AI course.

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Data, Dataset, Big Data, DIKUW Pyramid, explain how these terms relate to AI and why it’s important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary AI Glossary Series – DevOps, Machine Learning Operations (ML Ops) AI Glossary Series – Automated Machine Learning (AutoML) AI Glossary Series – Data Preparation, Data Cleaning, Data Splitting, Data Multiplication, Data Transformation AI Glossary Series – Data Augmentation, Data Labeling, Bounding box, Sensor fusion AI Glossary Series – Data, Dataset, Big Data, DIKUW Pyramid Continue reading AI Today Podcast: AI Glossary Series – Structured Data, Unstructured Data, Semi-structured Data at Cognilytica.

It’s hard to have a conversation about AI these days without the topics of Generative AI and Large Language Models (LLMs) coming up. But what do these technologies mean at an organizational level? And how do you apply this technology for your organization? In this podcast episode hosts Kathleen Walch and Ron Schmelzer take a deeper look at what generative AI, Transformer Models, and LLMs are. Continue reading AI Today Podcast: Generative AI Series: Generative AI & Large Language Models (LLMs) – How Do They Work? at Cognilytica.

In this podcast, the hosts discuss the importance of understanding the V's of big data in AI. They explain the challenges of handling large amounts of data, dealing with data variety, and processing rapidly changing data. They also introduce the concept of data veracity and discuss how the V's of big data impact AI projects.

The podcast discusses the importance of building and interacting with AI systems ethically and responsibly. It highlights the risks of AI technology and the need for control. The impact on the workforce and the importance of new job categories are also explored. The lack of existing frameworks for ethical AI is addressed and a comprehensive trustworthy AI framework is introduced. Additionally, a free intro to trustworthy AI course is discussed, along with encouraging listener engagement.