Machine Learning in Google I/O 19
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올해 Google I/O에서는 구글의 머신러닝 및 딥러닝 분야에 대한 다양한 접근이 소개되었습니다. 이 발표에서는 Google I/O 2019에서 다룬 머신러닝 세션들을 크게 머신러닝 플랫폼, 머신러닝 클라우드 및 머신러닝 기반의 응용 서비스 확장으로 구분하고, 각각에 대하여 요약해 봅니다. 또한 현재의 발표를 바탕으로 이후의 방향성이 어떻게 될 것인지에 대하여 몇가지 예측을 해 봅니다. 이 슬라이드는 2019년 6월 Google I/O Extended 판교 및 서울에서 발표한 슬라이드입니다. This talk covers the machine learning activities published during Google I/O.
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Machine Learning in Google I/O 19
- 1. Machine Learning in Google I/O 19 Jeongkyu Shin Google I/O `19 Extended Seoul / Pangyo
- 2. • Lablup Inc. • • Backend.AI • • Google Developer Expert • ML / DL GDE, Sprint Master
- 3. My Google I/O `19 • 41 • 20 • 7 • 5 GDE/GDE
- 4. extended
- 5. extended
- 6. “ ” ? :
- 7. • : AI → • “ ” “ ” ? • “ ?” → • “ ?” → • “ ?” → , , OS, Stadia, Fuchusia… “ ” “ ” Google I/O `19
- 9. • 14 + ⍺ • • 3 TensorFlow DevSummit …
- 10. + • Coral, Edge TPU • TensorFlow Lite • TensorFlow.js + PWA • Swift for TensorFlow • TensorFlow 2.0 • TF-Agents • • / • Federated Learning • On-chip • Private Join and Compute • TPU Pods V3 • Cloud TPU Pods Beta • ML Kit + Firebase :
- 11. : • Coral, Edge TPU • TensorFlow Lite • TensorFlow.js + PWA • Swift for TensorFlow
- 12. : • TensorFlow 2.0 • TF-Agents • (Machine Learning Fairness) • / •
- 13. • Federated Learning • On-chip • Private Join and Compute
- 14. • Federated Learning • On-chip • Private Join and Compute • I/O … • 2019 6 19 . • !
- 15. + • TPU Pods V3 • Cloud TPU Pods Beta • ML Kit + Firebase
- 16. : Coral, Edge TPU / TensorFlow Lite / TensorFlow.js + PWA / Swift for TensorFlow
- 18. Coral • Edge TPU • • USB • PCI-E, SOM • • Mendel OS (Debian Fork) • TF Lite Edge TPU • Python SDK
- 19. • I/O `19: SDK • • ops : • • Edge AI ASIC • Neural ComputeStick / Jetson Nano • RP4 + Add-on • ? Coral
- 20. • TF • XLA • TensorFlow 2.0 / TensorFlow.js • GPU / NPU ( ) TensorFlow Lite
- 21. • node.js • prebuilt / TF Hub (AI Hub) TensorFlow.js
- 22. • node.js • prebuilt / TF Hub (AI Hub) TensorFlow.js
- 23. • • Backend Frontend • C++ + Python + (TF Lite) + … ! • Swift: • LLVM • ( Python + ) • On-the-track: (O’reilly) • Swift for TensorFlow
- 24. : TensorFlow 2.0/ TF-Agents / (Machine Learning Fairness) / /
- 25. • (6 ) • Keras / Eager Execution • • tf.compat.v1 • TF Docs Sprint Seoul TensorFlow 2.0 http://bit.ly/2Y2VdR5
- 26. • Jupyter Notebook • TensorFlow / pybullet • • TensorFlow 1.14 2.0 • 2019 6 7 : RL (GFootball) • https://github.com/google-research/ football TF TF-Agents https://github.com/tensorflow/agents
- 28. • • - , , • “ ” (ML Fairness)
- 29. • • • (Transparency Framework)
- 30. • • / What-if
- 31. • TensorFlow Model Analysis • • • •
- 32. : (Federated Learning) / On-chip
- 33. Federated Learning • (Data island) + • + + • 2016 • 2019 : TensorFlow Federated • PySyft (for PyTorch) *Sources: [1] https://ai.googleblog.com/2017/04/federated-learning-collaborative.html [2] Federated Learning: Machine Learning on Decentralized Data (Google I/O 19)
- 34. • • • • GBoard • / Federated Learning extended
- 35. TensorFlow TensorFlow Federated • API • • • API • • *Source: Federated Learning: Machine Learning on Decentralized Data
- 36. • • Pixel • • 1/10 • : • • ( ) • On-chip
- 37. Title + :
- 38. + • TPU Pods V3 • Cloud TPU Pods Beta • ML Kit + Firebase extended
- 39. • ? → ! TPU Pods ! Cloud TPU Pods Beta • XLNet ( 6 20 ) • BERT • Cloud TPU Pod 2.5 ! • 2.5 2.9 . extended
- 40. • • → → • / Transfer Learning Firebase + + AutoML Vision Edge
- 41. + • Coral, Edge TPU • TensorFlow Lite • TensorFlow.js + PWA • Swift for TensorFlow • TensorFlow 2.0 • TF-Agents • • / • Federated Learning • On-chip • Private Join and Compute • TPU Pods V3 • Cloud TPU Pods Beta • ML Kit + Firebase