Podcasts

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How AI Reflects Reality and Why Intentions Come Second to Impact | Slo Mo with Mo Gawdat

Christopher Nguyen and host Mo Gawdat on How the interconnected of machines made the internet and is making the future. How can a developer write a code that creates an independently intelligent entity? So much of life and the world is predictable and, therefore, algorithmically replicable. Are creativity, consciousness, emotions, and art in the cards for intelligent machines? Being thoughtful of how machines are deployed is an existential priority. A profound thought: Intention must come second to possible impact.

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Human-First Artificial Intelligence w/ ​​Christopher Nguyen | Going Deep with Aaron Watson

Human-first AI: How companies should approach AI in the context of life-critical, industrial applications. In this episode, Christopher Nguyen and host Aaron Watson discuss AI’s shortcomings, the mission of Aitomatic, and how diverse experiences keep life engaging.

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Where and how did data fail and humans succeed in AI? | Giant Robots Smashing Into Other Giant Robots with Chad Pytel

Where and how did data fail and humans succeed in ?

Tune in to the latest episode of Giant Robots Smashing into Other Giant Robots, where Chad Pytel talks with our CEO Christopher Nguyen about why we still need people; and working in knowledge-first AI instead of knowledge-2nd, or no knowledge at all.

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Human-first vs. Data-first Approaches to Machine Learning | AI and the Future of Work with Dan Turchin

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. What if, instead of relying on automated data collection, we codify expertise in the heads of a small number of experienced technicians? Listen and learn why Human-first (vs. Data-first) AI may disrupt traditional approaches to ML, how automation problems in physical-first vs. digital-first industries require different solutions...

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What is AI Engineering?

Industrial AI involves incorporating AI capabilities into physical systems, which are often highly reliable systems that operate in challenging environments. Safety and reliability are therefore paramount in Industrial AI applications, and use cases can involve scenarios with limited or noisy training data, or limited internet connections and power supplies. Here's our take on AI Engineering—the emerging discipline concerned with the qualitative and quantitative design, construction, and operation of systems with AI capabilities.

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Designing machine learning models for both consumer and industrial applications

Aitomatic's CEO Christopher Nguyen and The Data Exchange host Ben Lorica on implementing analytics and machine learning products and systems within a large company, ML for IoT and Industrial AI applications such as predictive maintenance, forecasting, etc. Learn the benefits of combining knowledge-based systems and machine learning models. Take a listen and don't forget to share this episode with your friends.

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