Turing-NLG: A 17-billion-parameter language model by Microsoft - Microsoft Research
Microsoft Research Forum Episode 3: Globally inclusive and equitable AI, new use cases for AI, and more In the latest episode of Microsoft Research Forum, researchers explored the importance of globally inclusive and equitable AI, shared updates on AutoGen and MatterGen, presented novel use cases for AI, including industrial applications and the potential of multimodal models to improve assistive
DeepSpeed: Extreme-scale model training for everyone - Microsoft Research
In February, we announced DeepSpeed, an open-source deep learning training optimization library, and ZeRO (Zero Redundancy Optimizer), a novel memory optimization technology in the library, which vastly advances large model training by improving scale, speed, cost, and usability. DeepSpeed has enabled researchers to create Turing Natural Language Generation (Turing-NLG), the largest language model
ZeRO-Infinity and DeepSpeed: Unlocking unprecedented model scale for deep learning training - Microsoft Research
ZeRO-Infinity and DeepSpeed: Unlocking unprecedented model scale for deep learning training Published April 19, 2021 By DeepSpeed Team Rangan Majumder , Vice President Andrey Proskurin , Corporate Vice President of Engineering Since the DeepSpeed optimization library was introduced last year, it has rolled out numerous novel optimizations for training large AI models—improving scale, speed, cost,
Microsoft researchers unlock the black box of network embedding - Microsoft Research
As humans, we have great capacity to understand knowledge, notice similarities and make connections and inferences. However, our capacity is limited by the amount of information we can process. Computers, on the other hand, can process tremendous amounts of information, but their ability to understand knowledge and make inferences is limited. That’s because humans think in symbols and computers th
Serving DNNs in Real Time at Datacenter Scale with Project Brainwave - Microsoft Research
Eric Chung , Jeremy Fowers , Kalin Ovtcharov , Michael Papamichael , Adrian Caulfield , Todd Massengill , Ming Liu , Mahdi Ghandi , Daniel Lo , Steve Reinhardt , Shlomi Alkalay , Hari Angepat , Derek Chiou , Alessandro Forin , Doug Burger , Lisa Woods , Gabriel Weisz , Michael Haselman , Dan Zhang IEEE Micro | March 2018 , Vol 38: pp. 8-20 To meet the computational demands required of deep learnin
Microsoft unveils Project Brainwave for real-time AI - Microsoft Research
First, Project Brainwave leverages the massive FPGA infrastructure (opens in new tab)that Microsoft has been deploying over the past few years. By attaching high-performance FPGAs directly to our datacenter network, we can serve DNNs as hardware microservices (opens in new tab), where a DNN can be mapped to a pool of remote FPGAs and called by a server with no software in the loop. This system a
1-Bit Stochastic Gradient Descent and Application to Data-Parallel Distributed Training of Speech DNNs - Microsoft Research
We show empirically that in SGD training of deep neural networks, one can, at no or nearly no loss of accuracy, quantize the gradients aggressively—to but one bit per value—if the quantization error is carried forward across minibatches (error feedback). This size reduction makes it feasible to parallelize SGD through data-parallelism with fast processors like recent GPUs. We implement data-parall
Quantum Nearest-Neighbor Algorithms for Machine Learning - Microsoft Research
We present several quantum algorithms for performing nearest-neighbor learning. At the core of our algorithms are fast and coherent quantum methods for computing distance metrics such as the inner product and Euclidean distance. We prove upper bounds on the number of queries to the input data required to compute these metrics. In the worst case, our quantum algorithms lead to polynomial reductions
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John Snyder at Microsoft Research
About Dr. John Snyder is a Principal Researcher at Microsoft Research, Redmond, WA in the 3D Graphics research group. He is leading research efforts on real-time global illumination effects such as soft shadowing and is also interested in mathematical methods and representations for rendering and processing synthetic geometry. Dr. Snyder joined Microsoft Research in January 1994. Prior to that, h
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Holographic Near-Eye Displays for Virtual and Augmented Reality - Microsoft Research
Geodesic Image and Video Editing - Microsoft Research
Direct GPU/FPGA Communication Via PCI Express - Microsoft Research
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Photo Tourism: Microsoft Research, Interactive Visual Media Group
Microsoft Surface - 新しいタブレット PC
C++: 水面下の仕組み - Microsoft Visual C++ Web Site