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Federated Learning Demo (AI Summit 2018)

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Federated Learning enables devices (IoT) and services to learn from each other. See a live demo from byteLAKE and Lenovo during #AISummit in San Francisco (Sept. 19-20, 2018, booth #607). Read more: http://www.bytelake.com/en/AISummit2018

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Federated Learning Demo (AI Summit 2018)

  1. 1. byteLAKE We build intelligent software and hardware solutions Federated Learning in action (example demo scenario for manufacturing)
  2. 2. 2 Machine Learning Sensor Data Time Local training & inferencing Lenovo’s Tiny device Aggregating local models & redistributing updates Federated Learning Lenovo’s Data Center How it works
  3. 3. ➢ learning to predict pressure changes (locally) ➢ learning locally & from already trained systems (federated learning) Simulation Fan 1 Fan 2 Barometric pressure sensor Filter 1 Filter 2 Styrofoam balls Flying Styrofoam balls… … simulate filters clogging & pressure changes. Demo
  4. 4. 4 Demo
  5. 5. Lenovo’s Tiny Think Centre Simulation - Arduino Uno Rev3 - Barometric Pressure Sensor (BMP180) - Ultrasonic Distance Sensor (HC-SR04) - Federated learning - Machine learning model (based on regression method) Lenovo’s Data Center Technology highlights Software highlights - Arduino Software (IDE) - PC/Server: C++ - GUI: QT v5 - Graphics: OpenGL - Client-Server: Unix Sockets - Server: OpenMP Demo
  6. 6. ➢System reached the accuracy of 95-98% (federated learning) ➢At the same time, local model reached 40% (tens of iterations to reach 60-80% accuracy) 6 Simulation results Demo
  7. 7. 7 Read more: Video: www.byteLAKE.com/en/AISummit2018 www.byteLAKE.com/en/AISummit2018-video Demo
  8. 8. Federated Learning enables devices (IoT) to learn from each other AI Summit, San Francisco, CA, booth #607 (Sept. 19-20 2018) Meet & to see a live demo
  9. 9. ✓Enable Scalability (Decentralized AI enables IoT/devices to learn from each other) ✓Solve low-throughput and high-latency challenges (Local AI models reduce latencies, lower power consumption) ✓Improve accuracy (Have smarter models via aggregation of many local models) ✓Reduce training time (Benefit from local training and already trained models in the neighborhood) ✓Lower the cost of training (Bringing data from all devices is expensive) ✓Ensure privacy (Sensitive data stays local) 9 Benefits of Federated Learning
  10. 10. Explore new possibilities with federated learning 10 Healthcare Aggregate knowledge from many specialists Industry Enable devices to learn from each other Expert Systems Better decisions
  11. 11. Embrace the new possibilities of Augmented Intelligence with
  12. 12. We build intelligent software and hardware solutions. We port and optimize algorithms for parallel, CPU+GPU HPC architectures. We deploy AI on data centers, in the cloud and on constrained, embedded devices (AI on Edge). byteLAKE We are specialists in: www.byteLAKE.com Machine Learning Deep Learning Computer Vision High Performance Computing Heterogeneous Computing Edge Intelligence Enabling companies to become more efficient and increase competitiveness in their markets. We are a team of scientists, programmers, designers and technology enthusiasts helping industries incorporate AI techniques into products.

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