AI News, Revolutions

Revolutions

This is the first edition of a monthly roundup of news about Artificial Intelligence, Machine Learning and Data Science.

This is an eclectic collection of interesting blog posts, software announcements, applications and events I've noted over the past month or so.

Google releases DeepLab on Github, a trained CNN model to assign semantic labels to every pixel of an image.

Google releases Lucid, a neural-network visualization library designed to help with the interpretability of vision systems.

The Geo AI Data Science VM, including ESRI ArcGIS Pro and a land cover classification tutorial dataset, is now available in the Azure Marketplace.

podcast interview about Project InnerEye, an innovative machine learning tool that helps radiologists identify and analyze 3-D images of cancerous tumors.

Microsoft Research has developed a system to translate news articles from Chinese to English with the same accuracy as human translators.

An overview of LUIS, Microsoft's cloud-based service for developing language- and speech-based applications.

Microsoft announces Azure Databricks powered by Apache® Spark, new AI, IoT and machine learning tools for developers

New tools to help increase developer productivity and simplify app development for intelligent cloud and edge, across devices, platforms or data sources NEW YORK — Nov. 15, 2017 — Wednesday at Connect();

we’re announcing new tools and services that help developers build applications and services for the AI-driven future, using the platforms, languages and collaboration tools they already know and love.” Across devs, apps, data, platforms Microsoft is continuing its commitment to delivering open technologies and contributing to and partnering with the open source community.

New tools and partnerships are designed to help developers build intelligent, enterprise-ready and cloud-scale apps — regardless of their platform, and to give them the peace of mind with the built-in security, performance, compliance features, support and SLAs available in Azure.

Azure IoT Edge Azure Machine Learning updates  Visual Studio Tools for AI Azure SQL Database Machine Learning services preview For the next three days, Microsoft is streaming more than 36 live, engineering-led training sessions that are designed to give developers hands-on experience with the tools and technologies featured throughout the keynote presentations.

Announcing tools for the AI-driven digital transformation

Artificial Intelligence (AI) has emerged as one of the most disruptive forces behind the digital transformation of business.

Today, at Microsoft Ignite 2017, as we engage in conversations about digital transformation with over 25,000 customers and partners, I am pleased to share some of our latest and most exciting innovations in AI development platforms.

demonstrate our mission to bring AI to every developer and every organization on the planet, and to help businesses augment human ingenuity in unique and differentiated ways.

Today we are announcing a set of powerful new capabilities in AML for developers to exploit big data, GPUs, data wrangling and container based model deployment.

we have created a data wrangling experience (Figure 1) that drastically reduces the time that data scientists have to spend in transforming data for machine learning.

Figure 1: AI-powered data wrangling in the workbench learns from examples and automatically synthesizes code for data transformations using program synthesis technology.

The experimentation service tracks, stores and manages models, configurations, parameters and data using Git repositories so that data scientists have full versioning and visibility of experimentation history and reproducibility.

The AML Model Management Service allows developers and data scientists to deploy and manage their trained models locally, to the edge, or to large scale cluster deployments in the cloud.

Once in production, models can be monitored for performance using Azure Application Insights and then proactively retrained if data drift or other circumstances begin to degrade performance.

Every organization can create models using AML (Figure2) that are customized for their needs, and deploy them as cloud hosted functions in Excel, to make AI a really natural, everyday part of the spreadsheet.

This technology empowers businesses of any size, right from small entrepreneurs to large organizations, to design and deploy custom web search applications.

This includes some of the latest AI capabilities in Office and Windows, new advances in Microsoft customer service, and even the way our finance team generates our internal company revenue forecast.

We are excited to announce we are expanding Microsoft Dynamics 365 with new AI solutions that transform critical Enterprise scenarios to help business users reinvent the processes they use every day.

By bringing together the best of our secure, scalable, and reliable Azure platform to build end to end systems of intelligence, these solutions will allow you to address mission critical enterprise scenarios with AI.

The first solution we’re announcing is focused on customer support, with an intelligent virtual agent for customer interaction, an intelligent assistant for customer service staff, and conversation management tools (Figure 4).

A fascinating example is how the Snow Leopard Trust is using Azure Machine Learning in their efforts to survey and protect this rare and beautiful species that lives in the remote Himalayan region (Figure 5).

“Since visual surveying is not an option in the remote mountains, biologists deploy motion-sensing cameras in snow leopard habitat that capture images of snow leopards, prey, livestock, and anything else that moves,”

Microsoft Build highlights new opportunity for developers, at the edge and in the cloud

“These advancements create incredible developer opportunity and also come with a responsibility to ensure the technology we build is trusted and benefits all.” As part of Microsoft’s commitment to trusted, responsible AI products and practices, the company also today announced AI for Accessibility, a new $25 million, five-year program aimed at harnessing the power of AI to amplify human capabilities for more than 1 billion people around the world with disabilities.

Today Microsoft is announcing new capabilities for developers to extend to the edge: Data and AI development for a new era Using data, machine learning and cognitive intelligence, developers can build and manage AI-rich solutions that transform the ways people work, collaborate and live: Multisense and multidevice experiences Microsoft also demonstrated mixed-reality capabilities to enable richer experiences that understand the context surrounding people, the things they use, their activities and relationships: Modern tooling and experiences for any platform in any language Microsoft is empowering developers to build for the new era of the intelligent edge, across Azure, Microsoft 365 and other platforms, using the languages and frameworks of their choice: Microsoft (Nasdaq “MSFT” @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge.

AI news from Microsoft’s Build developers conference

At Microsoft’s Build developers conference in Seattle this week, the company is unveiling a series of new and updated tools that will help developers incorporate artificial intelligence into their processes and applications, regardless of their background and training in the fast-emerging field of AI.

limited preview will allow customers to bring Project Brainwave to the edge, meaning customers could take advantage of that computing speed in their own businesses and facilities, even if their systems lack a network or Internet connection.

Azure Machine Learning also is announcing new Azure Machine Learning Packages, which are sets of algorithms that enable data scientists to easily build, train, fine tune and deploy highly accurate and efficient models for computer vision, text analytics and financial forecasting.

The improvements include the ability to customize models for specific speaking styles and the vocabulary of an industry, and to create a unique brand voice, for example for an interactive bot on a customer’s e-commerce website.

For example, a new feature in preview allows users to train models to identify objects within images – to pick out the trained object and show its location within the image.

Project Personality Chat makes intelligent agents more complete and conversational by handling small talk in a consistent tone and reducing fallback responses such as “I don’t understand.” Project Personality Chat also allows developers to give their agents a personality, from professional to humorous, that aligns with a brand voice.

In addition to all these new AI tools for developers, Microsoft also announced AI Lab, a new collection of AI projects designed to enable developers to get started with AI by exploring, experiencing, learning and coding the latest Microsoft AI technology innovations.

All the Build announcements illustrate how new technologies are rapidly changing the way people live, learn and work – progress that comes with an opportunity and responsibility to make sure technology is used well.

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