During a marathon presentation at the annual Build developers conference, Microsoft executives laid out their vision of a smarter, more responsive IoT-driven future. The company is leveraging AI to better serve those with physical disabilities, repurposing the Kinect to boost its Azure development, and investing heavily in its developer community. Numbers because how else would we have realized the keynote went on for longer than Infinity War? The investment will focus on leveraging machine learning to improve the employment prospects and social interactions for those who need it. The company's "Your Phone" feature is designed to facilitate sharing files and notifications between, uh, your phone and your desktop.
Adapted from the VERGE Weekly newsletter, published Wednesdays. Early warning systems informed by sensors and big data. It felt appropriate to weigh in with a year-end riff about a topic that's guaranteed to spark debate at holiday parties -- when and how to use AI for jobs that humans just can't perform as efficiently as smart software. This somewhat hypothetical question has special relevance in the context of recent developments at Amazon and Microsoft, two tech giants seeking to outwit each other in establishing their cloud software services as platforms for running and managing AI applications. On Dec. 10, Amazon Web Services quietly launched what it's calling the Amazon Sustainability Data Initiative, which builds on the "vast amounts of data that describe our planet."
Microsoft Cognitive Toolkit (CNTK) is a production-grade, open-source, deep-learning library. In the spirit of democratizing AI tools, CNTK embraces fully open development, is available on GitHub, and provides support for both Windows and Linux. These enhancements, combined with unparalleled scalability on NVIDIA hardware, were demonstrated by both NVIDIA at SuperComputing 2016 and Cray at NIPS 2016. These enhancements from the CNTK supported Microsoft in its recent breakthrough in speech recognition, reaching human parity in conversational speech. The toolkit is used in all kinds of deep learning, including image, video, speech, and text data.
Microsoft says that Artificial Intelligence (AI) should be built around three core directives: augmenting human abilities, being trustworthy and being respectful. Microsoft hosts its Future Decoded event on an annual basis at London's ExCeL center in the fast-regenerating'docklands' area. But was this year's event just another set of polished executives striding around talking about so-called'business transformation', or were there guts and substance of any kind? The firm in fact devoted much of its opening statements and arguments to discuss intelligent machines, neural networks and Artificial Intelligence (AI). By way of introduction, Microsoft UK CEO Cindy Rose leads the software firm's British operations.
The Azure Machine Learning service speeds up the process of identifying useful algorithms and machine learning pipelines, which automates model selection and tuning. This can cut development time from days to hours, said Bharat Sandhu, director of product marketing, big data and analytics at Microsoft. It also provides DevOps capabilities, via integrated CI/CD tooling, to enable experiment tracking and manage machine learning models deployed in the cloud and on the edge, said Venky Veeraraghavan, group program manager for Microsoft Azure, in a blog post. The Azure Machine Learning service supports popular open source frameworks, including PyTorch, TensorFlow and scikit-learn, so developers and data scientists can use familiar tools. Developers can use Visual Studio Code, Visual Studio, PyCharm, Azure Databricks notebooks or Jupyter notebooks to build apps that use the service.