Tag: Machine Learning

Machine learning (ML) isn’t just for the technology industry. Today, machine learning influences research and consumer products and is leading to breakthroughs across industries like healthcare, manufacturing, finance, and retail. In the field of reinforcement learning, machine learning meets the real world when applied to robotics. Knowing this, how can we ensure students are skilled and prepared to leverage the power of this technology?

Data is an organization’s most valuable asset, and the volume and variety of data that organizations amass is always growing. Simpler data analytics, cheaper data storage, advanced predictive tools like machine learning (ML) and data visualization are necessary to make data-driven decisions and maximize the value of data. The new Data Lifecycle and Analytics in […]

Machine learning (ML) is one of the fastest growing areas in technology. AWS DeepRacer helps anyone get started with ML through autonomous driving. Tyler Technologies, an Amazon Web Services (AWS) Partner Network (APN) partner held a DeepRacer event at their annual internal conference, Tyler Mesh, in September in Indianapolis, Indiana, to help their organization learn about ML and ML on AWS.

From healthcare to veteran services to aerospace research, federal agencies have leveraged the cloud to advance their missions. With benefits from the cloud, such as cost savings, data redundancy, and opportunities to adopt emerging technology, federal customers can better serve and protect their constituents. Three federal agencies recently shared how they improved efficiency through information technology (IT) modernization to ultimately better serve citizens.

At the Amazon Web Services (AWS) Public Sector Summit in Washington, DC, AWS employees shared and demonstrated our newest homegrown AWS innovations in the AWS Builders Fair. These demos featured real-world use cases for government, education, and nonprofits. Using artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), natural language processing, and robotics, the demos show how technology can help address issues from recycling to translation to safe transportation. Check out the top six Builders Fair demos, now on our YouTube channel.

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.

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.

Tasking someone to find a singular image in a sea of millions of captured images would be like telling them to find a needle in a haystack. Yet, this is one project for which Ralph Perko is developing a solution. Perko is a lead senior software engineer at the Pacific Northwest National Laboratory (PNNL) in the state of Washington. In his role, he is responsible for taking the lab’s research and creating applied, scalable solutions to support PNNL’s customers’ missions.