Putting AI on Diet: TinyML and Efficient Deep Learning Published 2021-04-16 Download video MP4 360p Recommendations 40:22 In-memory Computing with Memristors and Memtransistors - Daniele Ielmini 13:35 The Horizon Problem | The Universe's biggest UNSOLVED mystery 3:30:04 SpaceX Performs Second Attempt of B10/S28 Wet Dress Rehearsal 1:18:40 S2024 #06 - Vectorized Query Execution Using SIMD (CMU Advanced Database Systems) 57:14 Resource-Efficient Deep Learning Execution - Deepak Narayanan | Stanford MLSys #50 1:17:06 Great Decisions Lecture 3 - China's Belt and Road Initiative - Dr. Zenel Garcia 9:18:36 (SCRUB) SpaceX Stacks Ship 28 on Booster 10 1:51:08 [Turkish] Let's Learn .NET - Blazor 50:15 Neuromorphic computing with emerging memory devices 5:04:45 SCRUB: SpaceX Performs Wet Dress Rehearsal of Third Starship Flight Stack 58:49 TinyML and Efficient Deep Learning on IoT Devices 1:00:46 On .NET Live - Every Cache a Painting 59:02 Terence Tao "Correlations of Multiplicative Functions" 22:28 SpaceX Starship Flight 3's Launch Timeline - Get Ready! 3:40:25 Build and Deploy a GraphQL API using NodeJS (tutorial for beginners) 58:34 History of IBM mainframe operating systems - M243 1:06:39 Lecture 11 - MCUNet: Tiny Neural Network Design for Microcontrollers | MIT 6.S965 12:18 OpenAI Shocks the AI Video World - Sora Changes Everything 55:16 Terence Tao "Translational Tilings of Euclidean Space" Similar videos 45:54 tinyML Summit 2021 Keynote Song Han: Putting AI on a Diet: TinyML and Efficient Deep Learning 32:46 tinyML Asia 2021 Plenary - Song Han: Putting AI on a Diet: TinyML and Efficient Deep Learning 56:31 MIT Prof. Song Han on Reducing AI's Carbon Footprint | Stanford MLSys Seminar Episode 9 40:16 TinyML and Efficient Deep Learning 37:51 [SPCL_Bcast] TinyML and Efficient Deep Learning 1:01:20 tinyML Talks: A Practical Guide to Neural Network Quantization 04:08 Athena kickoff meeting - Prof. Song Han (MIT) - TinyML and Efficient Deep Learning on Edge Devices 50:18 Small is big: Making Deep Neural Nets faster and energy-efficient on low power hardware 02:00 The Future of ML is Tiny and Bright 08:20 What is Tiny ML? More results