AI Use Case Series: AI in Travel and Hospitality [AI Today Podcast]

AI is significantly transforming the travel industry by enhancing customer experiences, optimizing operations, and personalizing services. In this episode hosts Kathleen Walch and Ron Schmelzer discuss various ways that AI is applied in travel and hospitality. AI Improving the Travel Experience We are seeing AI be applied to improve the entire experience. Through hyperpersonalization, AI

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Ethical AI and Project Management: Interview with Vince Lynch, CEO of IV.AI [AI Today Podcast]

This episode is the audio recording of the discussion moderated by Kathleen Walch at PMI’s Global Summit 2024 event. This event took place in LA on September 20th. On this panel we get insights from Vince Lynch who is CEO of IV.AI. The discussion starts off with Vince sharing some of the biggest challenges he’s

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Are We Still Repeating the Same Mistakes with AI? [AI Today Podcast]

Artificial intelligence has been on the horizon for over seventy years. In fact, the term AI was officially coined in 1956. So, why does it seem so close but also so unattainable? In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss the question: Are we still repeating the same mistakes with

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Why “Move Fast and Break Things” Doesn’t Work for AI [AI Today Podcast]

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

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

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

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Prompt Engineering Best Practices: Hack and Track [AI Today Podcast]

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

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Lowering Barriers to Entry for AI: Interview with Nuri Cankaya, Intel [AI Today Podcast]

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

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Has AI Crossed the Chasm? [AI Today Podcast]

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

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Growing Key AI and Data Skills with CPMAI: Interview with Selvie Thevathasan [AI Today Podcast]

In an era where Artificial Intelligence is revolutionizing various industries, professionals equipped with the right skills and certifications are in high demand. The Certified Project Management for AI (CPMAI) certification is a game-changer for those seeking to excel in planning, managing, and executing AI and ML projects. And for those looking to grow critical AI

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AI Glossary Series: Retrieval Augmented Generation (RAG) [AI Today Podcast]

It’s hard to have a conversation about AI these days without the topics of Generative AI and Large Language Models (LLMs) coming up. And, Large Language Models (LLMs) have been proving useful for a variety of things such as helping write text, write code, generate images, and help augment human workers. However, as people are using

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Revisiting the Seven Patterns of AI in 2024 [AI Today Podcast]

How many categories of AI are there? Artificial Intelligence and machine learning is maturing considerably. You can now find AI projects in every industry. At Cognilytica, we spend a considerable amount of time on use cases and how different industries are using AI. As we analyze hundreds of different use cases, interact with many customers, deliver

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AI Today Podcast: The Critical AI and Data Skills Needed for AI Project Managers

AI projects are really data-centric projects. After all, data is the heart of AI. So it should come as no surprise that project managers who are managing AI projects need to move beyond just general project management skills. These provide a good foundation for managing schedules, resources, and the people needed to meet organizational goals.

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No, Agile and the “Scientific Method” are not Sufficient to Run AI Projects

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%. At Cognilytica, we have seen thousands of AI projects ourselves and the most of the reasons for these failures can be traced to 10 key reasons. One of those reasons is

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Operationalizing AI

When AI practitioners talk about taking their machine learning models and deploying them into real-world environments, they don’t call it deployment. Instead the term that’s used in the industry is “operationalizing”. This might be confusing for traditional IT operations managers and applications developers. Why don’t we deploy or put into production AI models? What does

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From Machine Learning to Machine Reasoning

This post was featured in our Cognilytica Newsletter, with additional details. Didn’t get the newsletter? Sign up here The conversation around Artificial Intelligence usually revolves around technology-focused topics: machine learning, conversational interfaces, autonomous agents, and other aspects of data science, math, and implementation. However, the history and evolution of AI is also inextricably linked with

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Are people overly infatuated with Deep Learning, and can it really deliver?

This post was featured in our Cognilytica Newsletter, with additional details. Didn’t get the newsletter? Sign up here One of the factors often credited for this latest boom in artificial intelligence (AI) investment, research, and related cognitive technologies, is the emergence of Deep Learning AI algorithms, and the corresponding large volumes of big data and

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