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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 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 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 Projects / AI Systems / Diversity / Intelligence Amplification / Teams July 30, 2021
READ MOREHere is my advice to CEOs about AI. Much of what you already know as a leader can be translated into the introduction of an AI “team member”. You know: How to build and manage teams The value of diverse teams for improved decision making and productivity The need for continuous and thoughtful team redesign, […]
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AI Business / AI Companies / AI Projects / AI Systems / Applied AI / Artificial Intelligence / ROI July 30, 2021
READ MOREI see it all the time. A brilliant and passionate team contacts me for advice or investment. They’ve conceptualized an amazing fully automated AI system that will (eventually) solve a customer’s problem. And it’s really hard to do and it’s going to be very expensive in terms of time and money but, the team is […]
