Experimenting, testing, and refining your prompts are essential. The journey to crafting the perfect prompt often involves trying various strategies to discover what works best for your specific needs. A best practice is to constantly experiment, practice, and try new things using an approach called “hack and track”. This is where you use a spreadsheet or other method to track what prompts work well as you experiment. Continue reading Prompt Engineering Best Practices: Hack and Track [AI Today Podcast] at Cognilytica.

Plugins for Large Language Models (LLMs) are additional tools or extensions that enhance the LLM’s capabilities beyond its base functions. In this episode hosts Kathleen Walch and Ron Schmelzer discuss this topic in greater detail. Can I use plugins with ChatGPT? Plugins can access external databases, perform specific computations, or interact with other software and APIs to fetch real-time data, execute code, and more. Continue reading Prompt Engineering Best Practices: Using Plugins [AI Today Podcast] at Cognilytica.

As folks continue to use LLMs, best practices are emerging to help users get the most out of LLMs. OpenAI’s ChatGPT allows users to tailor responses to match their tone and desired output goals. Many have reported that using custom instructions results in much more accurate, precise, consistent, and predictable results. But why would you want to do this and why does it matter? Continue reading Prompt Engineering Best Practices: Using Custom Instructions [AI Today Podcast] at Cognilytica.

Companies of all sizes in every industry are looking to see how Artificial Intelligence (AI), machine learning (ML), and cognitive technology projects can provide them a competitive edge. They want to provide efficiencies and improve ROI in today’s competitive landscape. As a result, this creates tremendous opportunity in the field of AI for professionals who are CPMAI certified and follow the CPMAI methodology. Continue reading Applying CPMAI Methodology in the real world: Interview with George Fountain, Booz Allen Hamilton (BAH) [AI Today Podcast] at Cognilytica.

To improve the reliability and performance of LLMs, sometimes you need to break large tasks/prompts into sub-tasks. Prompt chaining is when a task is split into sub-tasks with the idea to create a chain of prompt operations. Prompt chaining is useful if the LLM is struggling to complete your larger complex task in one step.  Continue reading Prompt Engineering Best Practices: What is Prompt Chaining? [AI Today Podcast] at Cognilytica.

LLMs are basically big “text predictors” that try to generate outputs based on what it expects is the most likely desired output based on what the user provides as the text-based input, the prompt. Prompts are natural language instructions for an LLM provided by a human so that it will deliver the desired results you’re looking for. Continue reading Prompt Engineering Best Practices: Using a Prompt Pattern [AI Today Podcast] at Cognilytica.

AI is helping to re-imagine experiences of all sorts, including air travel. At the 2024 SXSW Conference and Festivals Bernadette Berger, who is Director of Innovation at Alaska Airlines presents on “The Sky’s the Limit: How AI will Re-imagine Airports”. In this episode of the AI Today podcast hosts and AI thought leaders Kathleen Walch and Ron Schmelzer have the opportunity to interview Bernadette. Continue reading How AI will Re-imagine Air Travel: Interview with Bernadette Berger, Alaska Airlines [AI Today Podcast] at Cognilytica.

AI is having an impact on every industry, including healthcare. AI’s impact in the practice of medicine is helping to reshape the practice of medicine both now, and in the future. In this episode of the AI Today podcast we interview Dr. Jag Singh. He is a Professor of Medicine at Harvard Medical School, focusing on the application of AI in the practice of medicine. Continue reading AI’s impact in the practice of medicine: Interview with Dr. Jag Singh, Mass General Brigham [AI Today Podcast] at Cognilytica.

During the SXSW 2024 event, Wei Li presented on AI Everywhere with Software and Hardware. In this episode of the AI Today podcast we interview Wei Li. He is VP/GM of the AI Software Engineering Team at Intel. He shares with what insights from that talk and what he means by AI being everywhere in both hardware and software. Continue reading AI Everywhere with Software and Hardware: Interview with Wei Li, Intel [AI Today Podcast] at Cognilytica.

As organizations continue to adopt AI the idea of innovation and sustainability are becoming important conversations. Intel wants to accelerate AI adoption by lowering barriers to entry for customers. In this episode of the AI Today podcast we interview Nuri Cankaya. He is the VP of AI Marketing at Intel. Nuri sheds light on the myriad challenges faced by companies as they navigate the integration of AI with real-world data. Continue reading Lowering Barriers to Entry for AI: Interview with Nuri Cankaya, Intel [AI Today Podcast] at Cognilytica.

AI is having an impact on just about every industry and healthcare is no exception. In this episode of the AI Today podcast Cognilytica AI thought leaders Kathleen Walch and Ron Schmelzer interview Dr. Jesse Ehrenfeld. He is President of the American Medical Association (AMA). He also recently spoke at the 2024 SXSW Conference and Festivals. Continue reading AI’s Impact on Healthcare: Interview with Dr. Jesse Ehrenfeld, AMA [AI Today Podcast] at Cognilytica.

The people side of AI is changing. Generative AI is reshaping how teams brainstorm, collaborate, and embrace the future. In this episode of the AI Today podcast we interview Ian Beacraft who is CEO at Signal and Cipher, and also CPMAI certified. Is AI helping or hurting society? In recent years the idea of responsible, ethical, and trustworthy AI has gained a lot of attention. Continue reading The People Side of AI: Interview with Ian Beacraft, Signal and Cipher [AI Today podcast] at Cognilytica.

The Explainable AI Layer of the Cognilytica Trustworthy AI Framework addresses the technical methods that go into understanding system behavior and make black boxes less so. In this episode of the AI Today podcast Cognilytica AI experts Ron Schmelzer and Kathleen Walch discuss the interpretable and explainable AI layer. The Explainable AI Layer Separate from the notion of transparency of AI systems is the concept of AI algorithms being able to explain how they arrived at particular decisions. Continue reading Explainable AI Concepts [AI Today Podcast] at Cognilytica.

Who is on the AI Team? Continue reading Who is on the AI Team? [AI Today podcast] at Cognilytica.

Anyone looking to use and/or develop AI systems need ways that maintain trust, provide visibility and transparency, and utilize processes and methods that can provide greater oversight and accountability for potent AI systems that need to address – the layers of trustworthy AI. In this episode of the AI Today podcast Cognilytica thought leaders Kathleen Walch and Ron Schmelzer go over the Governed AI layer of the Cognilytica Trustworthy AI Framework. Continue reading Governed AI Concepts [AI Today Podcast] at Cognilytica.

What are you really spending on in an AI Project? This is a question we often get asked. So, we wanted to spend some time on this podcast to discuss how to determine AI project costs. First, it’s important to remember that it all comes down to scope. Our motto: Think Big. Start Small. Continue reading Determining AI Project Costs [AI Today Podcast] at Cognilytica.

AI system transparency is about how we manage and run our AI systems. Transparency needs to address how you plan to provide visibility or transparency into how AI systems are created or applied. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss the transparent layer of AI as part of Cognilytica’s Trustworthy AI Framework. Continue reading Transparent AI Concepts [AI Today Podcast] at Cognilytica.

The best practice for any high risk, emerging technology project with ill-defined goals is: Think Big. Start Small. Iterate Often. But, what does that really mean? How do you think big? And how do you start small? What does iteration look like? And how does this connect to project scope? In this episode of the AI Today podcast we discuss what it means to think big when it comes to AI. Continue reading Properly Scoping AI Projects [AI Today Podcast] at Cognilytica.

In the context of technology adoption, “crossing the chasm” refers to the pivotal moment when an emerging technology moves beyond the early adopters and innovators phase to reach the early majority of users. This concept, popularized by Geoffrey A. Moore in his book “Crossing the Chasm,” highlights the gap or “chasm” that exists between the initial acceptance of a technology by enthusiasts and visionaries and its broader acceptance by a more pragmatic, mainstream market. Continue reading Has AI Crossed the Chasm? [AI Today Podcast] at Cognilytica.

What is pseudo AI? While AI is all about machines that have the intelligence like people, Pseudo AI or “AI washing” is when a company or product claims that AI is being used for a specific task or feature, but in reality, it’s people doing that task. In the startup world, “faking it until you make it”, is a common practice. Continue reading Pseudo AI: Still a Thing, Still a Problem [AI Today Podcast] at Cognilytica.