Ep. 3: Deep Learning DIY - NVIDIA Engineer Bob Bond, Make: Magazine Executive Editor Mike Senese
Dec 11, 2016
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NVIDIA engineer Bob Bond and Make: Magazine Editor Mike Senese discuss using deep learning for DIY projects like recognizing cats in the front yard with a Jetson board and creating a non-lethal cat sprayer. They explore how AI can be utilized in everyday tasks and innovative technology projects, emphasizing the accessibility of advanced technology for hobbyists.
DIY AI enables individuals to solve everyday problems like deterring cats using deep learning and consumer GPUs.
AI technology is increasingly adaptable for unconventional applications, such as developing autonomous systems for pet entertainment with platforms like NVIDIA's Jetson TX1.
Deep dives
Application of DIY AI to Everyday Problems
DIY AI involves everyday applications accessible to individuals without extensive engineering backgrounds. For instance, using deep neural nets to address common issues like deterring neighbor's cats from intruding into the yard. By installing a camera to detect cats, a system was set up to activate a sprinkler, showcasing a practical and innovative use of AI for everyday challenges.
Expansion of AI Applications to Novel Areas
The podcast highlights the increasing accessibility and adaptability of AI technology for unconventional applications. Examples include developing autonomous systems for pet entertainment, like a laser toy for cats, by leveraging powerful prototyping boards like NVIDIA's Jetson TX1. The fusion of AI with diverse scenarios, such as enhancing pet interactions, demonstrates the playful and creative integration of advanced technology into everyday life.
Growing Community Engagement in DIY AI Projects
The discussion delves into the emerging trend of community-driven experimentation with AI technology. Through projects like autonomous racing series for Power Wheels toys, individuals are exploring AI solutions with affordable budgets, akin to DARPA challenges. This collaborative engagement not only fosters innovation but also serves as an entry point for individuals to explore AI applications, encouraging a grassroots movement in developing and sharing novel AI projects.
Deep learning isn't just for research scientists anymore. Hobbyists can use consumer grade GPUs and open-source DNN software to tackle common household tasks from ant control to chasing away stray cats.
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