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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 Capabilities / AI Systems / Applied AI / Artificial Intelligence March 24, 2022
READ MOREAI failures and how to avoid them are a recurring theme of these posts. In a recent article called 4 things VCs get wrong about AI, Aible CEO Arijit Sengupta provides one reason: AI is not SaaS, and we cannot directly apply lessons learned from SaaS successes to AI Projects. I do like Arijit’s contrast with SaaS metrics. His strongest point addresses what you can’t learn from AI pilots. In […]
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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 […]
