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How Change Management Can Prepare Leaders for AI [Podcast Takeaways] Change can be scary. It’s a well-known adage, one whose longevity can be attributed to its accuracy—but it’s not an excuse. AI and its industry applications grow by the day.
How To Solve Problems With AI [theCUBE Interview] What is trustworthy AI? How are companies using AI? What are some of the top concerns about AI and privacy today? Pandata CEO and AI Strategist, Cal Al-Dhubaib, recently joined Jonathan Seckler
Why Does AI Matter Now? 3 Factors Driving Recent Interest [Collision Takeaways] While the earliest forms of AI date back to the 1950s, the last decade has seen a marked increase in the popularity of artificial intelligence. And as AI
What Is Compute in AI? 3 Key Challenges In its simplest form, compute describes the manipulation of information; it’s used to organize and process data. Machines that use compute to perform tasks have three primary components: logic, memory, and interconnect.
Reliable KPIs for AI: How To Measure Success This post is part of a series designed to help AI-interested regulated industry leaders overcome challenges to successful AI design. For more information, download Top Challenges to Designing AI in Regulated Industries
How Do I Monitor for Bias in AI? This post is part of a series that features answers to top AI questions, directly from our data scientists. Other posts in this series include: Data scientists, major organizations, and media outlets
Is AI Really Surveillance? [Insight From Collision Conference] When you hear the word “surveillance” what comes to mind? You might be thinking about hidden cameras, tracking website history, public health monitoring, or a military operation. It’s often construed as invasive
How To Develop an AI Strategy That Yields Positive ROI This post is part of a series designed to help AI-interested regulated industry leaders overcome challenges to successful AI design. For more information, download Top Challenges to Designing AI in
What Can I Expect From the Future of Machine Learning? Machine learning has come a long way since the 1952 introduction of the first computer learning program. In 1980, data scientists created Explanation Based Learning, where a computer could create
Who Is Responsible for AI’s Mistakes? This post is part of a series that features answers to top AI questions, straight from our data scientists. To receive similar content to your inbox, subscribe to our monthly email digest. Strategizing, designing,
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