Christopher Nguyen, serial entrepreneur and CEO of Aitomatic, realized big data isn't the only answer when training AI models. In fact, when doing preventive or predictive maintenance on industrial equipment, only small data is available. He and his team asked what if instead of relying on automated data collection we codify expertise in the heads of a small number of experienced technicians. And thus human-first AI was born. Aitomatic was launched in 2021 to productize the new field. It builds on Christopher's legacy of innovation having spent time in academia, at Google, and other startups including Arimo before its acquisition by Panasonic.
Listen and learn...
1. Why human-first vs. data-first AI may disrupt traditional approaches to machine learning. 2. How automation problems in physical-first vs. digital-first industries require different solutions. 3. How to build machine learning models when there isn t enough data. 4. Why the world is in short supply of human expertise. 5. How people feel about having their jobs automated away. 6. Why the topic of ethical AI is controversial. 7. The science behind neuromorphic computing.
References in today's episode...
AitomaticChristopher on TwitterGordon Wilson, CEO of Rain Neuromorphics, on AI and the Future of Work Thanks to Tess Hau from Tess Ventures for the introduction to Christopher!
Christopher Nguyen, serial entrepreneur and CEO of Aitomatic, realized big data isn't the only answer when training AI models. In fact, when doing preventive or predictive maintenance on industrial equipment, only small data is available. He and his team asked what if instead of relying on automated data collection we codify expertise in the heads of a small number of experienced technicians. And thus human-first AI was born. Aitomatic was launched in 2021 to productize the new field. It builds on Christopher's legacy of innovation having spent time in academia, at Google, and other startups including Arimo before its acquisition by Panasonic.
Listen and learn...
1. Why human-first vs. data-first AI may disrupt traditional approaches to machine learning. 2. How automation problems in physical-first vs. digital-first industries require different solutions. 3. How to build machine learning models when there isn t enough data. 4. Why the world is in short supply of human expertise. 5. How people feel about having their jobs automated away. 6. Why the topic of ethical AI is controversial. 7. The science behind neuromorphic computing.
References in today's episode...
AitomaticChristopher on TwitterGordon Wilson, CEO of Rain Neuromorphics, on AI and the Future of Work Thanks to Tess Hau from Tess Ventures for the introduction to Christopher!
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