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"A Practical Guide to Neural Network Quantization" Marios Fournarakis Deep Learning Researcher Qualcomm "Data techniques that enable tiny computer vision in the real world" Jelmer Neeven Deep learning scientist and software engineer ... Demoing the world's fastest inference engine for Arm Cortex-M Cedric Nugteren Deep learning software engineer Plumerai ...
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tinyML Talks Tomer Malach: AI/ML SoC for Ultra-Low-Power Mobile and IoT devices
tinyML Talks: SRAM based In-Memory Computing for Energy-Efficient AI Inference
tinyML Talks: A Practical Guide to Neural Network Quantization
tinyML Talks - Sek Chai: Adaptive AI for a Smarter Edge
tinyML Talks local India Amit Mate: AI/ML solutions for low-power Edge platforms - challenges and...
tinyML Talks Shenzhen: Data techniques that enable tiny computer vision in the real world
tinyML Talks Weiwen Jiang: Using AI to design energy-efficient AI accelerators for the edge
tinyML Talks: Demoing the world’s fastest inference engine for Arm Cortex-M
tinyML Talks: Train-by-weight (TBW): Accelerated Deep Learning by Data Dimensionality Reduction
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Last Updated: June 7, 2026
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