458 episodes

Cognilytica's AI Today podcast focuses on relevant information about what's going on today in the world of artificial intelligence. Hosts Kathleen Walch and Ron Schmelzer discuss pressing topics around artificial intelligence with easy to digest content, interview guests and experts on the subject, and cut through the hype and noise to identify what is really happening with adoption and implementation of AI.

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

    • Technology
    • 4.4 • 134 Ratings

Cognilytica's AI Today podcast focuses on relevant information about what's going on today in the world of artificial intelligence. Hosts Kathleen Walch and Ron Schmelzer discuss pressing topics around artificial intelligence with easy to digest content, interview guests and experts on the subject, and cut through the hype and noise to identify what is really happening with adoption and implementation of AI.

    What Iteration Really Means with AI

    What Iteration Really Means with AI

    AI projects aren’t dying because of big problems. Rather it’s the small things that are causing projects to fail. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss what iteration really means for AI projects.








    Continuous Model Iteration







    We always say that AI projects are never set it and forget it. AI project lifecycles are continuous. They require regular evaluation and retraining. Treating AI projects as one-time investments without considering continuous iteration leads to misaligned ROI and eventual project failure. Successful AI projects require ongoing financial and resource allocation to adapt to real-world changes and evolving data. In this episode we discuss why this is so critial.








    CPMAI: Best Practices for AI Projects







    Certainly, AI projects need to be treated like data projects. So, following a best practices step-by-step approach is critical. Adopting iterative and agile methodologies, such as CPMAI, ensures key steps aren't missed. AI projects often fail not because of big issues but due to small, overlooked details. Initial excitement fades as the realities of AI project implementation set in. If you don't plan iteration properly, it will lead to AI project failures. Mainly because organizations neglect long-term costs and maintenance.








    Show Notes:










    Free Intro to CPMAI course







    CPMAI Certification







    Subscribe to Cognilytica newsletter on LinkedIn

    • 8 min
    Why "Move Fast and Break Things" Doesn't Work for AI

    Why "Move Fast and Break Things" Doesn't Work for AI

    Move Fast and Break Things worked for high flying Silicon Valley startup megatech companies but it doesn’t work for AI projects. Between 70%-80% of AI projects are failing to meet their objectives. With stats like this, it's clear that breaking things isn't leading to success in AI. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer dig into this topic.








    Iterating to Success vs. Breaking Things







    AI projects often fail because organizations are tempted to abandon them when immediate success isn't achieved. Instead of moving fast, organizations need to focus on iterative sprints that bring AI projects closer to their goals. The key is to "think big, start small, and iterate often." This allows for incremental progress and small wins. In this episode we explain what iteration looks like for AI projects.








    The Real-World AI Disconnect







    Certainly, on this podcast we talk a lot about proof-of-concept versus pilots. AI projects frequently fail when small POCs are pushed into real-world applications too quickly. The disconnect between controlled environments and real-world complexities often leads to project failures. And we have seen this far too often.








    Additionally, in this episode we discuss that AI projects must account for real-world data and conditions to succeed. We highlight the importance of aligning development environments with actual use cases. We explain why a cautious, step-wise approach to AI projects, even for simple tasks like document classification using NLP, ensures that AI solutions are tested and refined in real-world scenarios. A popular and proven approach is the Cognitive Project Management for AI (CPMAI). It emphasizes the importance of iterative progress and realistic expectations.








    Show Notes:










    Free Intro to CPMAI course







    CPMAI Certification







    Subscribe to Cognilytica newsletter on LinkedIn







    The Necessary (and often Missing) “U” in the DIKUW Pyramid [AI Today Podcast]

    • 22 min
    The Necessary (and often Missing) “U” in the DIKUW Pyramid

    The Necessary (and often Missing) “U” in the DIKUW Pyramid

    One of the most vexing problems in even today’s highly capable intelligence systems is for systems to actually understand what they are generating as output. Repeating a pattern, even a sophisticated pattern, while showing good knowledge of the pattern, doesn’t really help if the system doesn’t really understand what it is generating.  In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss this DIKUW pyramid and why the "U" understanding level is a critical, but often left out, layer of the pyramid.








    What does the DIK(U)W pyramid represent?







    Data is the heart of AI. So it makes sense that data is at the base of the pyramid. In order to get value from data, which is what the DIKUW pyramid is meant to explain, you can’t just jump from knowledge of patterns to wisdom. If you truly want to get machines to become more intelligent, you need to bridge that gap with at least some understanding of those patterns. Below is a visual presentation of the DIKUW pyramid.
















    In this episode we explain what each level is, and how you move up to the next level. Machine learning, which is what many of our current AI applications are today, is at the "K" knowledge level. However, we need more than machine learning - we need machine reasoning. Machine reason is the concept of giving machines the power to make connections between facts, observations, and all the magical things that we can train machines to do with machine learning. And, we explain why we aren't yet here. Indeed, we're rapidly facing the reality that we're going to soon hit the wall on the current edge of capabilities with machine learning-focused AI. This is where the understanding layer comes into play.








    The current wave of interest and investment in AI doesn't show any signs of slowing or stopping any time soon, but it's inevitable it will slow at some point for one simple reason: we still don't understand intelligence and how it works.








    Show Notes:










    Free Intro to CPMAI course







    CPMAI Certification







    Subscribe to Cognilytica newsletter on LinkedIn







    Why Critical Thinking is Crucial for AI [AI Today Podcast]







    Is Critical Thinking A Superpower In The AI Era?







    Soft Skills for AI: Why Collaboration is Key for AI Success [AI Today Podcast]







    Cyc Project

    • 13 min
    Soft Skills for AI: Enhancing Collaboration Skills

    Soft Skills for AI: Enhancing Collaboration Skills

    Soft skills are increasingly becoming important for AI, and in particular Generative AI. Collaboration can accelerate learning, creativity, and innovation. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss the critical skill of collaboration.








    Why Collaboration skills are needed for AI







    In this episode we discuss why collaboration skills are important to improve your interaction with AI systems. By collaborating with others you can improve your prompts and prompt skills. You can also learn what applications are a good fit for AI. Additionally, you're able to get more diverse perspectives on how to leverage AI systems by talking to different people at your organization in different groups and different roles. Also, you can learn from people from different industries.








    How AI is helping us become better Collaborators







    On the flip side, AI can also make us better collaborators. Generative AI can generate a vast array of ideas and solutions, serving as a creative partner in brainstorming sessions. It can also help facilitate remote collaboration. With the rise of remote work, generative AI can enhance virtual collaboration tools, making remote meetings more interactive and productive.








    Show Notes:










    Free Intro to CPMAI course







    CPMAI Certification







    Subscribe to Cognilytica newsletter on LinkedIn







    Why Critical Thinking is Crucial for AI [AI Today Podcast]







    Is Critical Thinking A Superpower In The AI Era?

    • 10 min
    AI in Local Government: Interview with Roxy Ndebumadu

    AI in Local Government: Interview with Roxy Ndebumadu

    AI is being adopted by many organizations and they are seeing dramatic improvement, increased productivity, and cost savings. However, government at all levels, including local governments, are also seeing dramatic improvements when adopting AI. On this episode of AI Today we interview Roxy Ndebumadu. She is the District 4 Councilmember at Bowie, MD City Council.








    AI at the local government level







    Roxy's unique background allows her to bring a technology and AI perspective to local government. In this episode Roxy shares her experiences using AI in her election campaign. She also discusses the transformative role that AI can play in enhancing community services and operations from education to road repairs.








    Additionally, Roxy shares strategies local governments can adopt to effectively up skill their employees on AI technologies and ensure they are prepared for future advancements. She also shares how local governments can look to partner and collaborate with tech companies and educational institutions to foster a robust AI ecosystem at the local level This episode is a must-listen for anyone interested in the intersection of technology, AI, and local government.








    Show Notes:










    Free Intro to CPMAI course







    CPMAI Certification







    Subscribe to Cognilytica newsletter on LinkedIn







    AI Accountability & Colorado’s Trailblazing AI Consumer Law: Interview with Rep Manny Rutinel [AI Today Podcast]

    • 17 min
    Unlocking the power of Communication with AI

    Unlocking the power of Communication with AI

    Effective communication is vital for enhancing both human-to-machine and human-to-human interactions with AI. Clear communication ensures more accurate and optimal outputs from AI systems. Additionally, AI tools can improve our communication skills by helping us better articulate and present our ideas and creative needs. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer continue with the soft skills series and discuss the soft skill of communication.








    How do I communicate with AI?







    Being an effective communicator is essential when it comes to working with AI systems, particularly generative AI. In this episode we discuss why clear communication skills are essential for improving interactions with genAI systems. Any why being specific and communicating well-defined inputs lead to more accurate AI responses. Providing detailed prompts, using prompt patterns, and specifying detailed parameters like target audience, key points, tone, style, and visual details, ensures the AI produces the desired results. This is why this soft skill is critical.








    How AI is helping us be better communicators







    In this episode we also discuss how AI is helping humans become better communicators. AI-powered language translation is helping humans communicate with others who don't speak the same language. Additionally, AI writing and grammar assistants are helping improve writing quality by providing real-time edits for grammar, style, and tone, making communication clearer and more polished.








    Show Notes:










    Free Intro to CPMAI course







    CPMAI Certification







    Subscribe to Cognilytica newsletter on LinkedIn







    Why Critical Thinking is Crucial for AI [AI Today Podcast]







    The Understated Soft Skill Of Communication With AI







    Is Critical Thinking A Superpower In The AI Era?

    • 7 min

Customer Reviews

4.4 out of 5
134 Ratings

134 Ratings

Idea sampler ,

Timely, Provocative and Valuable

I am impressed by the breadth of the carefully curated content featured. Thanks for putting out such high quality perspective!

SEMpro ,

Always Current, Always Relevant

I’ve been a listener and follower for several years now. “AI Today” is consistently relevant because it focuses on the practical application and implementation issues those of us on AI learning journeys encounter everyday.

Oleg Luzhnov ,

Amazing podcast

I love the “AI Today” podcast. Great balance of content, duration, depth and simplicity of presentation. “AI Glossary” is my favorite series, every time I get to know something new, even being initially familiar with most of the terms.

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