New collaboration and education program connects Amazon machine learning experts with AWS customers and partners to accelerate the application of machine learning within their organizations
Johnson & Johnson, Washington Post, and World Bank Group are the first customers to join the program
Amazon Web Services, Inc. (AWS), an Amazon.com company (NASDAQ: AMZN), announced the Amazon ML Solutions Lab, a new program that connects machine learning experts from across Amazon with AWS customers to help identify practical uses of machine learning inside customers’ businesses, and guide them in developing new machine learning-enabled features, products, and processes. The Amazon ML Solutions Lab combines hands-on educational workshops with brainstorming sessions to help customers “work backwards” from business challenges, and then go step-by-step through the process of developing machine learning-based solutions. Customers will work with Amazon machine learning experts to prepare data, build and train models, and put models into production. At the end of the program, customers will be able to take what they have learned through the process and use it elsewhere in their organization. To get started with the Amazon ML Solutions Lab, visit https://aws.amazon.com/ml-solutions-lab.
While AWS customers across various industries are moving quickly to adopt machine learning, relatively few organizations have machine learning expertise, and many are challenged in taking the first steps to introduce machine learning and artificial intelligence into their products and processes. Amazon has been investing in machine learning for 20 years, using machine learning and deep learning to make product recommendations, optimize robotic picking routes in fulfillment centers, sharpen algorithms that inform Amazon’s supply chain, forecasting, and capacity planning, provide the intelligence in Amazon Alexa’s natural language understanding (NLU) and automated speech recognition (ASR), and support Amazon’s drone delivery initiative (Prime Air). Thousands of engineers across Amazon are working on machine learning. The Amazon ML Solutions Lab provides customers access to the same talent that built many of these machine learning-powered products and services. Amazon ML Solutions Lab engagements (which range from weeks to months depending on the nature of the solution) are designed to take customers through the full process of implementing machine learning, combining educational workshops and boot camps, advisory professional services, and hands-on help building custom models with a customer’s own data. For organizations who already have data prepared for machine learning, AWS offers the ML Solutions Lab Express. This four-week intensive program starts with a boot camp hosted at Amazon, and is followed by three weeks of intensive problem-solving and machine learning model building with Amazon machine learning experts.
“We can’t wait for developers to start their journeys into machine learning with the Amazon ML Solutions Lab,” said Swami Sivasubramanian, Vice President of Amazon AI. “By combining the expertise of the best machine learning scientist and practitioners at Amazon with the deep business knowledge of our customers, the Amazon ML Solutions Lab will help customers get up to speed on machine learning quickly, and start putting machine learning to work inside their organizations.”
Janssen, the pharmaceutical companies of Johnson & Johnson, is committed to collaborating with the world for the health of everyone in it. “We recently reached out to the Amazon ML Solutions Lab to collaborate with our data scientists on a deep learning initiative,” said Jesse Heap, Senior IT Manager, Data Sciences at Janssen Inc. “We are pleased to state that the Amazon ML Solutions Lab quickly kicked off a deep learning workshop through which machine learning experts from Amazon have been brainstorming with and training our data scientists on applying deep learning to pharma-related use cases.”
The Washington Post is one of the leading daily newspapers in the United States. “At The Washington Post, we are continually working to improve the experience of our readers using machine learning algorithms,” said Dr. Sam Han (PhD), director of data science at The Washington Post. “We are pleased to collaborate with the Amazon ML Solutions Lab to build models in application areas such as comment moderation, keyword tagging, and headline generation. Through our joint sessions, we have already developed a much better understanding of the challenges involved, and a path to solution, and we look forward to partnering with the Amazon ML Solutions Lab to build out cutting-edge machine learning models to improve the accuracy of our existing models.”
With 189 member countries, staff from more 170 countries, and offices in over 130 locations, the World Bank Group is a unique global partnership. “We are excited to collaborate with Amazon ML Solutions Lab folks to leverage machine learning in our mission to end extreme poverty and promote shared prosperity, ” Misha Lokshin, World Bank, Development Economics Group.
Amazon ML Solutions Lab engagements are available to all AWS customers with AWS Business Support today. Customers can learn more at https://aws.amazon.com/ml-solutions-lab.
About Amazon Web Services
For 11 years, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud platform. AWS offers over 90 fully featured services for compute, storage, networking, database, analytics, application services, deployment, management, developer, mobile, Internet of Things (IoT), Artificial Intelligence (AI), security, hybrid, and enterprise applications, from 44 Availability Zones (AZs) across 16 geographic regions in the U.S., Australia, Brazil, Canada, China, Germany, India, Ireland, Japan, Korea, Singapore, and the UK. AWS services are trusted by millions of active customers around the world — including the fastest growing startups, largest enterprises, and leading government agencies — to power their infrastructure, make them more agile, and lower costs. To learn more about AWS, visit https://aws.amazon.com.
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