| Ali Alvi and Paresh Kharya
We are excited to introduce the DeepSpeed- and Megatron-powered Megatron-Turing Natural Language Generation model (MT-NLG), the largest and the most powerful monolithic transformer language model trained to date, with 530 billion parameters. It is the result of a research collaboration…
In the news | VentureBeat
Today, Microsoft announced that Microsoft Translator, its AI-powered text translation service, now supports more than 100 different languages and dialects. With the addition of 12 new languages including Georgian, Macedonian, Tibetan, and Uyghur, Microsoft claims that Translator can now make…
Awards | X-Rings: A Hand-mounted 360 Degree Shape Display for Grasping in Virtual Reality
In the news | Microsoft AI Blog
Microsoft announced today that 12 new languages and dialects have been added to Translator. These additions mean that the service can now translate between more than 100 languages and dialects, making information in text and documents accessible to 5.66 billion…
In the news | MSPoweruser
Microsoft Research has shown off a new technology which makes it easier to manage and spread your workspace intelligently over a variety of devices.
In the news | IEEE Spectrum
Imagine you're a farmer in the northern United States. It's early spring, and nighttime temperatures are just starting to rise above freezing. You need to fertilize your newly-planted crops, but you also know that at freezing temperatures, the fertilizer will…
How our research findings helped inform our UX directions to use the intelligent model in shaping how to smartly light up the automatic calculation capabilities to assist users to achieve their tasks efficiently without relying on a calculator.
In the news | IEEE Spectrum
Researchers at Microsoft have developed a framework called DeepMC that can very accurately predict local weather, and could be used by farmers, renewable energy producers, and others.
We have developed a globally applicable diagnostic COVID-19 model by augmenting the classical SIR epidemiological model with a neural network module. Our model does not rely upon previous epidemics like SARS/MERS and all parameters are optimized via machine learning algorithms…