Intel® AI: AI Lab at Intel
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AI Lab at Intel - At Intel, we believe there is a virtuous cycle between research, algorithms and compute that’s leading to the tremendous growth we are seeing in AI.
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Intel® AI: AI Lab at Intel
- 1. AI Lab @ Intel Arjun.Bansal@intel.com
- 2. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. 3 Research drives need for AI compute https://blog.openai.com/ai-and-compute/
- 3. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. 4 All products, computer systems, dates, and figures are preliminarily based on current expectations and are subject to change without notice.
- 4. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. 5 1 An open source version is available at: 01.org/openvinotoolkit *Other names and brands may be claimed as the property of others. Developer personas show above represent the primary user base for each row, but are not mutually-exclusive All products, computer systems, dates, and figures are preliminary based on current expectations, and are subject to change without notice. Speedupdevelopment Optimization Notice TOOLKITS App developers libraries Data scientists Kernels Library developers Open source platform for building E2E Analytics & AI applications on Apache Spark* with distributed TensorFlow*, Keras*, BigDL Deep learning inference deployment on CPU/GPU/FPGA/VPU for Caffe*, TensorFlow*, MXNet*, ONNX*, Kaldi* Open source, scalable, and extensible distributed deep learning platform built on Kubernetes (BETA) Intel-optimized Frameworks And more framework optimizations underway including PaddlePaddle*, Chainer*, CNTK* & others Python R Distributed • Scikit-learn • Pandas • NumPy • Cart • Random Forest • e1071 • MlLib (on Spark) • Mahout Intel® Distribution for Python* Intel® Data Analytics Acceleration Library (DAAL) Intel distribution optimized for machine learning High performance machine learning & data analytics library Open source compiler for deep learning model computations optimized for multiple devices (CPU, GPU, NNP) from multiple frameworks (TF, MXNet, ONNX) Intel® Math Kernel Library for Deep Neural Networks (MKL-DNN) Open source DNN functions for CPU / integrated graphics Machinelearning Deeplearning * * * * * using open AI software Visit: www.intel.ai/technology
- 5. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. Algorithms Research drives AI innovations ICML ICLR CVPRNeurIPS Research presented at major AI conferences: SF, Santa Clara San Diego Israel ICASSP EMNLP ACL
- 6. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. 8 • Research tracks • Vision: Graph NNs • Audio: Multi-task & Semi-supervised learning • Natural Language Processing • Reinforcement Learning • Model compression • Product guidance • HW architecture roadmap • SW data science • AI business applications Intel AI Lab • Open Source libraries • NLP Architect • RL Coach • Distiller
- 7. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. 9 Reinforcement Learning Collaborative Evolutionary Reinforcement Learning (CERL) - ICML 2019 Shauharda Khadka, Somdeb Majumdar, Santiago Miret, Evren Tumer, Zach Dwiel, Tarek Nassar, Yinyin Liu, Kagan Tumer (Oregon State) Mariano Phielipp - Combines gradient-based learning with evolution - Sample efficient and robust to hyper-parameters - Consistently beats single-agent TD3 (SoA for continuous control) on Mujoco Humanoid Half-Cheetah https://arxiv.org/pdf/1905.00976.pdf
- 8. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. 10 Computer Vision Image Generation from Scene Graphs ICLR 2019 LLLD Workshop Subarna Tripathi Anahita Bhiwandiwalla Alexei Bastidas Hanlin Tang PartNet: Benchmark for 3D Object Understanding CVPR 2019, with Hao Su @ UCSD https://arxiv.org/abs/1812.02713 https://arxiv.org/abs/1901.03762
- 9. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. 11 Audio Multitask Learning ICLR 2019 LLLD Workshop Oguz H. Elibol Gokce Keskin Cory Stephenson Anil Thomas Voice Conversion using Adversarially Trained Autoencoders ICASSP 2019, with Berkeley BASICS Lab Tyler Lee Ting Gong Suchismita Padhy Anthony Ndirango Semi-supervised learning ICASSP 2019 https://openreview.net/forum?id=BkecJjCEuN http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber =8683204&isnumber=8682151 http://ieeexplore.ieee.org/stamp/stamp.jsp? tp=&arnumber=8683265&isnumber=86821 51
- 10. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. 12 NLP Term set expansion using multi-context term embeddings NACCL-HLT 2019 RepEval Workshop, with Ido Dagan at Bar Ilan University Jonathan Mamou Oren Pereg Moshe Wasserblat Alon Eirew arXiv:1807.10104
- 11. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. 13 Bayesian Structure Learning Constructing Deep Networks - NeurIPS 2018 Raanan Y. Rohekar Shami Nisimov Yaniv Gurwicz Guy Koren Gal Novik arXiv:1807.10104
- 12. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. 14 Graph Neural Networks Marcel Nassar Evren Tumer Hierarchical Bipartite Graph Convolution Relational Representation Learning Workshop, NeurIPS 2018 GraphDQN: Generalization to Novel Objects using Prior Relational Knowledge SPiRL Workshop, ICLR 2019 Conditional Graph Neural Processes Bayesian Deep Learning, NeurIPS 2018 Varun V. Kumar Hanlin Tang Abhinav Ganesh http://spirl.info/2019/camera-ready/spirl_camera-ready_07.pdfarXiv:1812.05212 arXiv:1812.03813
- 13. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. 15 University Collaborations UC Berkeley UMontreal Stanford Caltech MIT Brown UCSB UCSD Oregon State University Bar Ilan University
- 14. Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. © 2019 Intel Corporation. *Other names and brands may be claimed as the property of others. 16 github.com/NervanaSystems intel.ai/research