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AI Business / AI in Medicine / AI Projects / Applied AI / Artificial Intelligence / Machine Learning / Product Management / ROI January 6, 2022
READ MOREIf you’ve been reading my posts so far, you’ve probably learned solidly that AI models become useful when they leave the lab and become part of a deployed system, where they are integrated into business software and processes. So, say you’ve done that. You built your model. You improved your accuracy and demonstrated that it’s high […]
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AI Business / AI in Medicine / AI Projects / AI Systems / Artificial Intelligence / Machine Learning November 8, 2021
READ MOREWhen I talk with AI entrepreneurs, I often ask, “How good does the AI need to be, to be useful in your application? What actually is the quality bar?”[1]Note that in this article, I use the word “quality” as synonymous with “accuracy”, as opposed to the more general usage of “quality” in software development, which can […]
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Artificial Intelligence / Machine Learning September 19, 2021
READ MOREYou might be detecting a theme in the last few posts: AI isn’t always the answer. Sometimes it’s better to use just humans, sometimes humans in the loop with a non-AI solution. Here are a few other alternatives you should be sure to consider. The many flavors of machine learning At the moment, most enterprise AI […]
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AI Projects / AI Systems / Artificial Intelligence / Machine Learning / ROI September 19, 2021
READ MOREI wrote earlier about the importance of asking yourself some foundational questions about what alternatives your solution is competing with. I also wrote more specifically about competition with human / manual solutions, and about how it’s a good idea to seek the optimal mixture of AI, more traditional tech, and human beings. Sometimes, as it […]
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AI in Medicine / AI Systems / Applied AI / Artificial Intelligence / Intelligence Amplification / Machine Learning August 13, 2021
READ MOREShould companies base AI systems on knowledge or data? The answer may surprise you: the best AI systems today use both. If you’ve come to AI in recent years, you might be surprised to learn that early AI applications were almost exclusively logic-based: models were built from facts and rules, not learned from data. MYCIN […]
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AI Capabilities / AI Systems / Artificial Intelligence / Big Data / Machine Learning August 12, 2021
READ MOREGetting the right data—and getting the data right—is essential for good AI accuracy, whether that data is collected before or during system deployment. Obtaining Data Obtaining data to train your AI system may seem like a straightforward task, but there are some hidden gotchas. Consider a company I’ll call WebLeads. It set out to create the […]
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AI Business / AI in Medicine / Applied AI / Artificial Intelligence July 19, 2021
READ MOREIn my previous post I talked about how to identify the opportunities for AI to solve key operational challenges and deliver on organization goals. As I described there, a good place to start is by understanding the categories of AI and ML use cases. The first half-dozen categories were classification, prediction, optimization, robotics and control, […]
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Applied AI / Artificial Intelligence / Book / Decision Intelligence / Introductory / Product Management June 16, 2021
READ MORETypically, AI innovation teams want to use AI to solve important problems that people or the business really need solved, which could not be solved by other traditional approaches. In practice, we tend to misjudge what the customer needs, under-estimate what alternative approaches can accomplish, and overestimate our AI abilities. This is a standard recipe […]
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Applied AI / Artificial Intelligence / Book / Introductory June 6, 2021
READ MOREIf you’re a CEO, a CTO, product manager, a member of a start-up or an investor in a project that includes AI, you need real answers and practical solutions to some hard questions and problems: How well do we understand our customers and the value we bring to them? How good does the AI system […]
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Applied AI / Artificial Intelligence / Book / Introductory June 6, 2021
READ MOREArtificial Intelligence (AI)—including Machine Learning (ML)—stands at this same precipice today as it transitions into the mass market. Yet because we are only beginning this process, there is a missing body of knowledge—you might say an unwritten book on the shelf. This is the knowledge that’s essential to developing AI applications with low risk, high value, and high adoption, across the thousands of use cases in which the technology can provide massive value to humanity worldwide.
