This month in AWS Machine Learning: August 2020 edition
Every day there is something new going on in the world of AWS Machine Learning—from launches to new use cases to interactive trainings. We’re packaging some of the not-to-miss information from the ML Blog and beyond for easy perusing each month. Check back at the end of each month for the latest roundup.
This month we gave you a new way to add intelligence to your contact center, improved personalized recommendations, made our Machine Learning University content available, and more. Read on for our August launches:
- AWS Contact Center Intelligence (AWS CCI) solutions is now available. It’s a combination of services that empowers you to easily integrate AI into contact centers, made available through AWS Partner Network (APN) partners.
- Amazon’s Machine Learning University is making its online courses available to the public. Amazon.Science interviewed Brent Werness, AWS research scientist, and Bree Al-Rashid, who manages the Machine Learning University team, on the initiative. Check out the classes yourself on the Machine Learning University YouTube channel.
- Amazon Personalize can now create up to 50% better recommendations for fast-changing catalogs of new products and fresh content. And Amazon Forecast can now use Convolutional Neural Networks (CNNs) to train forecasting models up to two times faster with up to 30% higher accuracy.
- Formula 1 launched Fastest Driver, an F1 Insight powered by AWS. Find out how we determined where your current favorite driver ranks against the F1 legends of the past via the new Fastest Driver Insight tool, and check out the following video:
- With custom language models for Amazon Transcribe, you can now use pre-existing data to build a custom speech engine tailored for your transcription use case. Amazon Transcribe customers who operate in domains as diverse as law, finance, hospitality, insurance, and media all stand to benefit. We also launched natural language understanding improvements and confidence scores on Amazon Lex.
- Amazon Elastic Compute Cloud (Amazon EC2) Inf1 instances featuring AWS Inferentia chips are now available in five new Regions and with improved performance. And Amazon Textract is now available in Asia Pacific (Mumbai) and EU (Frankfurt) Regions.
Get ideas and architectures from AWS customers, partners, ML Heroes, and AWS experts on how to apply ML to your use case:
- Thermo Fisher Scientific, a world leader in serving science, used Amazon Personalize to deliver highly personalized, multi-channel content in an ever-developing ecosystem. For more information about how they’re providing their researchers, and others like them, the tools and materials they need to study the world’s most pressing problems, see Expanding scientific portfolios and adapting to a changing world with Amazon Personalize.
- Learn how TalkingData, a data intelligence service provider that offers data products and services to provide businesses insights on consumer behavior, preferences, and trends, uses AWS open-source Deep Java Library with Apache Spark for machine learning inference at scale.
- From the community, AWS ML Hero Rustem Feyzkhanov shares how to monitor cloud applications with Amazon CodeGuru Profiler (with code samples), AWS Hero Luca Bianchi shares how to build a neural network on Amazon SageMaker with PyTorch Lightning (with code samples), and Martin Paradesi shares how to train RL models for financial trading using TensorTrade on Amazon SageMaker Studio (with code samples).
- Get best practices on machine learning in financial services, including information around authentication and access management, data and model security, and ML operationalization (MLOps) best practices.
- Citibot provides tools for citizens and their governments to use for efficient and effective communication and civic change. Its chatbot search engine uses AI to find more answers for constituents, which allows government employees to allocate more time to higher-impact community actions.
- Are you bored of the same old board games? Tired of going through the motions with charades week after week? In need of a fun and exciting way to mix up game night? Guess My Drawing with DeepLens is a do-it-yourself recipe for building your very own ML-enabled Pictionary-style game! You can learn how to harness the power of AWS DeepLens, the AWS programmable video camera for developers to learn ML, and Amazon Alexa, the Amazon cloud-based voice service, to build your own game.
Explore more ML stories
Want more news about developments in ML? Check out the following stories:
- The “AI & Machine Learning Imperative” on MIT Sloan Management Review offers new insights from leading academics and practitioners in data science and artificial intelligence. This guide explores how managers and companies can overcome challenges and identify opportunities by assembling the right talent, stepping up their own leadership, and reshaping organizational strategy.
- Dive in to how Marinus Analytics uses the power of machine learning to analyze patterns in advertisements to combat human trafficking.
- Learn how AWS teamed up with RallyPoint military social media platform and Harvard University’s Nock Lab to use machine learning to aid intervention efforts by analyzing at-risk public posts.
- Michelle McKenna, CIO of the NFL, joins the Conversations with Leaders podcast to , including ML and the virtual draft.
- In the new workshop Machine Learning Training using SageMaker Studio, you can learn how to train and tune ML models to the highest accuracy within Amazon SageMaker Studio using built-in algorithms. You also learn about using Amazon SageMaker Debugger to gain full visibility.
- Gartner subscribers can learn more about why we have an Overall Score of 84/100, the highest rating among our peer group. According to Gartner, we met 87% of Gartner’s required criteria, 73% of preferred, and 85% of optional in the Gartner “Solution Scorecard for Amazon SageMaker, July 2020.”
Mark your calendars
Join us for the following exciting ML events:
- Register for the Public Sector AWS Artificial Intelligence and Machine Learning Week, September 14–18, 2020. Whether you’re in a government, nonprofit, university, or hospital setting, this webinar series is designed to help educate those new to AI, spark new ideas for business stakeholders, and deep dive into technical implementation for developers.
- AWS Power Hour: Machine Learning streams every Thursday at 4:00 PM PST on Twitch. The series offers free, fun, and interactive training with AWS expert hosts as they demonstrate how to build apps with AWS AI services. Designed for developers—even those without prior ML experience—the show helps you learn to build apps that showcase natural language, speech recognition, and other personalized recommendations. Tune in live, or catch the recorded episodes whenever it’s convenient for you.
- AWS and Pluralsight are hosting a three-part webinar series on the ins-and-outs of AWS DeepRacer. In the series, you will learn about the basics of DeepRacer, reinforcement learning and refinement, and the future of DeepRacer. View the first two webinars and register for the live webinar on September 22 here.
Also, if you missed it, the season finale of SageMaker Fridays aired on August 28. Stay tuned for more news on season 2!
See you next month for more on AWS ML!
About the Author
Laura Jones is a product marketing lead for AWS AI/ML where she focuses on sharing the stories of AWS’s customers and educating organizations on the impact of machine learning. As a Florida native living and surviving in rainy Seattle, she enjoys coffee, attempting to ski and enjoying the great outdoors.