Amazon has kicked off its annual re: Invent conference in Las Vegas and made three major AI announcements.
During a midnight keynote, Amazon unveiled Transcribe Medical, SageMaker Operators for Kubernetes, and DeepComposer.
The first announcement we’ll be talking about is likely to have the biggest impact on people’s lives soonest.
Transcribe Medical is designed to transcribe medical speech for primary care. The feature is aware of medical speech in addition to standard conversational diction.
Amazon says Transcribe Medical can be deployed across “thousands” of healthcare facilities to provide clinicians with secure note-taking abilities.
Transcribe Medical offers an API and can work with most microphone-equipped smart devices. The service is fully managed and sends back a stream of text in real-time.
Furthermore, and most importantly, Transcribe Medical is covered under AWS’s HIPAA eligibility and business associate addendum (BAA). This means that any customer that enters into a BAA with AWS can use Transcribe Medical to process and store personal health information legally.
SoundLines and Amgen are two partners which Amazon says are already using Transcribe Medical.
Vadim Khazan, president of technology at SoundLines, said in a statement:
“For the 3,500 health care partners relying on our care team optimisation strategies for the past 15 years, we’ve significantly decreased the time and effort required to get to insightful data.”
SageMaker Operators for Kubernetes
The next announcement is Amazon SageMaker Operators for Kubernetes.
Amazon’s SageMaker is a machine learning development platform and this new feature lets data scientists using Kubernetes train, tune, and deploy AI models.
SageMaker Operators can be installed on Kubernetes clusters and jobs can be created using Amazon’s machine learning platform through the Kubernetes API and command-line tools.
In a blog post, AWS deep learning senior product manager Aditya Bindal wrote:
“Customers are now spared all the heavy lifting of integrating their Amazon SageMaker and Kubernetes workflows. Starting today, customers using Kubernetes can make a simple call to Amazon SageMaker, a modular and fully-managed service that makes it easier to build, train, and deploy machine learning (ML) models at scale.”
Amazon says that compute resources are pre-configured and optimized, only provisioned when requested, scaled as needed, and shut down automatically when jobs complete.
SageMaker Operators for Kubernetes are generally available in AWS server regions including US East (Ohio), US East (N. Virginia), US West (Oregon), and EU (Ireland).
We are AI ML Editorial Team. We come up with informative quality articles on AI, Data Science, and Machine Learning. If you also want to contribute, kindly get in touch with us.