Tag: Amazon Sagemaker

ServerCentral Turing Group (SCTG), an Amazon Web Services (AWS) Advanced Consulting Partner, recently held a self-driving car challenge open to all employees. After the 2018 acquisition of Turing Group by ServerCentral, the AWS Public Sector Partner aimed to use the competition to unite the two legacy companies, while also building expertise across AWS services. Over […]

Amazon Web Services (AWS) and the Disruptive Innovators Network (DIN) hosted the first competitive social housing hackathon this past May in London. Four UK housing associations – including Great Places, Places for People and Metropolitan Thames Valley – were teamed with members of the AWS Partner Network (APN), and had 36 hours to analyse one of four housing problems and hack a solution.

Amazon Comprehend Medical is a natural language processing (NLP) service that simplifies the use of machine learning (ML) to extract relevant medical information from unstructured text often found in clinical charts or doctor’s notes. Since the service launched in the AWS Canada (Central) Region in June 2019, it opened up possibilities for Canadian healthcare organizations to better serve patients. Vancouver General Hospital (VGH) and University of British Columbia (UBC) researchers are among the organizations who leverage Amazon Comprehend Medical and Amazon SageMaker, to create their own machine learning models that can triage x-rays to provide a better healthcare experience.

Best Friends Animal Society, a leading national animal welfare organization dedicated to ending the killing of dogs and cats in America’s shelters, is going all-in on AWS as its standard for machine learning workloads.

As patients navigate the healthcare system, their records should be easily transferrable between all organizations to ensure continuity of care. Value-based payment programs and increasing consumerism have driven the need for prompt and complete access to clinical information in healthcare systems around the world.

How can organizations build and execute artificial intelligence strategies, addressing current and future mission needs? Tune in July 30th, to Government Matters’ webinar “Building Blocks of AI – Government Innovations” to hear how federal agencies are actively preparing data to take advantage of emerging technologies like artificial intelligence and machine learning. Sponsored by AWS, this hour-long, two-part webinar features technology decision-makers from federal civilian agencies and the U.S. Department of Defense discussing the mission-critical applications of artificial intelligence and machine learning.

The United Nations, World Bank, and International Committee of the Red Cross (ICRC) with support from Amazon Web Services and other technology companies, recently launched the Famine Action Mechanism (FAM). The FAM is the first global mechanism dedicated to preventing future famines. In the past, responses to these devastating events have often come too late, once many lives have already been lost.

AWS Educate is committed to providing students and educators with resources needed to accelerate cloud learning, which is why we have collaborated with Udacity – an online education provider for lifelong learners – to bring our members access to skills, knowledge, and practice for today’s machine learning technology. Beginning on May 18th, AWS Educate members will receive an exclusive benefit of $200 worth of free content on their Machine Learning Engineer Nanodegree Program. With Udacity, AWS Educate members can master valuable machine learning skills and use their AWS Promotional Credits to gain hands-on experience with cutting-edge AWS Machine Learning technologies like Amazon SageMaker.

If you have ever searched for directions, called an Uber, or looked up a trailhead, you have used DigitalGlobe’s imagery or information derived from it. DigitalGlobe went all-in on AWS to meet the growing demand for commercial geo-intelligence, migrating its entire 18-year imagery archive to the cloud. The company used AWS Snowmobile to move 100 petabytes of data to the cloud, allowing it to move away from large file-transfer protocols and delivery workflows.