AI Today Podcast

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 courseCPMAI Training and CertificationAI GlossaryAI 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 TransformationAI Glossary Series – Data Augmentation, Data Labeling, Bounding box, Sensor fusionAI Glossary Series – Data, Dataset, Big Data, DIKUW PyramidContinue 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 courseCPMAI Training and CertificationAI GlossaryAI 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 TransformationAI Glossary Series – Data Augmentation, Data Labeling, Bounding box, Sensor fusionAI Glossary Series – Data, Dataset, Big Data, DIKUW PyramidContinue reading AI Today Podcast: AI Glossary Series – Structured Data, Unstructured Data, Semi-structured Data at Cognilytica.

The hosts dive into the intriguing world of Generative AI and Large Language Models (LLMs). They explain how these technologies generate new data using machine learning techniques. Tokenization and word embeddings are explored for their role in enhancing language understanding. The significance of prompt engineering is highlighted, showing how it can improve model outputs. Plus, the evolution of GPT and ChatGPT is discussed, revealing their rapid adoption and transformative potential in AI. Finally, updates to the CPM AI certification and training program are shared, emphasizing its relevance in the industry.

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.

Kathleen Walch and Ron Schmelzer discuss the definitions of data, dataset, big data, and the DIKUW Pyramid, and how these concepts relate to AI. They emphasize the importance of analyzing data to gain insights and the challenges of big data. They also explain the progression from basic data to wisdom in the DIKUW Pyramid, and the importance of putting data into practice using the CPMAI methodology.

Chuck LaBarre, an expert in applying CPMAI methodology, discusses the benefits of the methodology in real-world scenarios. Topics include enhancing employee well-being, challenges in conversational AI and personalized medicine, trustworthy AI, use of LLMs, and the future of education.

Data is critical to making AI and machine learning work. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Data Augmentation, Data Labeling, Bounding box, Sensor fusion.Data Augmentation are the techniques used to enhance existing data through the use of additional data, manipulations on existing data, or combinations of data in various ways.Continue reading AI Today Podcast: AI Glossary Series – Data Augmentation, Data Labeling, Bounding box, Sensor fusion at Cognilytica.

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: The Layers of Trustworthy AI at Cognilytica.