AI at Scale
Models, infrastructure and hardware for next-generation AI applications
News & features
In the news | VentureBeat
Microsoft trains world’s largest Transformer language model
Microsoft AI & Research today shared what it calls the largest Transformer-based language generation model ever and open-sourced a deep learning library named DeepSpeed to make distributed training of large models easier.
In the news | InfoWorld
Microsoft speeds up PyTorch with DeepSpeed
Microsoft has released DeepSpeed, a new deep learning optimization library for PyTorch, that is designed to reduce memory use and train models with better parallelism on existing hardware.
In the news | MSPoweruser
Meet Microsoft DeepSpeed, a new deep learning library that can train massive 100-billion-parameter models
Microsoft Research today announced DeepSpeed, a new deep learning optimization library that can train massive 100-billion-parameter models. In AI, you need to have larger natural language models for better accuracy. But training larger natural language models is time consuming and…
In the news | Forbes
Microsoft Brings Enhanced NLP Capabilities To ONNX Runtime
Microsoft has announced that it has integrated an optimized implementation of BERT (Bidirectional Encoder Representations from Transformers) with the open source ONNX Runtime. Developers can take advantage of this implementation for scalable inferencing of BERT at an affordable cost.
In the news | WinBuzzer
Microsoft Open Sources BERT for ONNX Runtime
In December, Microsoft open sourced its ONNX Runtime inference engine. Now, the company says it also open-sourced an optimized version of BERT, a natural language model from Google, for ONNX.
In the news | VentureBeat
Microsoft open-sources ONNX Runtime model to speed up Google’s BERT
Microsoft Research AI today said it plans to open-source an optimized version of Google’s popular BERT natural language model designed to work with the ONNX Runtime inference engine. Microsoft uses to the same model to lower latency for BERT when…
In the news | Microsoft Open Source Blog
Microsoft open sources breakthrough optimizations for transformer inference on GPU and CPU
One of the most popular deep learning models used for natural language processing is BERT (Bidirectional Encoder Representations from Transformers) (opens in new tab). Due to the significant computation required, inferencing BERT at high scale can be extremely costly and may…
In the news | ZDNet
Microsoft makes performance, speed optimizations to ONNX machine-learning runtime available to developers
Microsoft is open sourcing and integrating some updates it it has made in deep-learning models used for natural-language processing. On January 21, the company announced it is making available to developers these optimizations by integrating them into the ONNX Runtime.
In the news | Search Engine Land
Bing says it has been applying BERT since April
Bing has been using BERT to improve the quality of search results since April, Microsoft has stated. The transformer models are now applied to every Bing query globally.