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AI in Medicine / Applied AI / Robotics / Uncanny Valley March 24, 2022
READ MOREMost of us think that improving quality or capability of an AI system makes it incrementally (or at least monotonically) better for the users. However, just like computer graphics and robotics, there can be an uncanny valley for AI systems. As artificial faces get more realistic, people are happier, but there is an uncanny valley where faces get to a point that is close to realistic but not…quite. Faces look “eerie” or […]
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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 Capabilities / AI in Medicine / AI Model / AI Systems January 6, 2022
READ MORE“As a rule of thumb, you’ll spend a few months getting to 80% and something between a few years and eternity getting the last 20%.” Chris Dixon in “The idea maze for AI startups” It may seem obvious to some—but bears repeating for others—that our AI product needs to satisfy our customers’ needs to be […]
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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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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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As I’ve explained in previous posts, many organizations are rushing to enter the AI fray, hiring teams of data scientists, coders, and project managers in the urgency to get into the game. But what many teams retain in terms of dedication and enthusiasm for AI projects, they often lack in understanding of the art of […]
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The robotics team had a great idea. Why not use self-driving car technology for a task that was essentially easier, and could make money on the way to autonomous nirvana? And, as often happens, they were pitching me for investment. A solid and practical team, I liked these guys for their clever concept: to build self-driving (“robot”) industrial […]
