Amazon’s annual re:Invent conference in Las Vegas began this week with three major AI announcements. The company presented the public with Transcribe Medical, SageMaker Operators for Kubernetes, and DeepComposer.
What is being called the biggest announcement of the three, Transcribe Medical is the newest edition to the company’s transcribe speech recognition service. It will transcribe medical speech for primary care. The program is capable of operating in medical speech as well as standard conversational diction.
According to the company, Transcribe Medical can be used across thousands of healthcare facilities, and it will help aid medical professionals in taking notes and other important information. It offers an API and will be able to be used with most smart devices containing a microphone. When the program reads and processes the information, it returns text in real-time.
Transcribe Medical is currently being used by SoundLines and Amgen.
Vadim Khazan is the president of technology at SoundLines.
“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 ton insightful data,” he said in a statement.
DeepComposer is an AI-enabled piano keyboard that will allow AWS customers to use AI and a MIDI controller to compose music. Amazon is calling the new technology the “world’s first” machine learning-enabled musical keyboard. It has 32 keys, and it is a two-octave keyboard.
Composers who use the program can choose whether to record a short musical tune or use a prerecorded one. They will then select a model for their desired genre and the model’s architecture parameters. They can also set the loss function, a feature used to measure the difference between the algorithm’s output and expected value. The composer can also choose hyperparameters and a validation sample. DeepComposer then creates a composition which can either be played in the AWS console or exported or shared on SoundCloud.
DeepComposer uses a generative adversarial network (GAN) to fill in compositional gaps in songs. Random data is taken by a generator component and used to create samples which are forwarded to a discriminator bit. The discriminator bit then separates the real samples from the fake ones, and the generator improves along with the discriminator. The generator progressively gets better at learning how to create samples as close to the genuine ones as possible.
SageMaker Operators for Kubernetes
AWS also launched Amazon SageMaker Operators for Kubernetes, which allows data scientists to train, tune, and deploy AI models in Amazon’s SageMaker machine learning development platform. AWS customers are able to install SageMaker Operators on Kubernetes clusters, and this can create Amazon SageMaker jobs natively using the Kubernetes API and command-line Kubernetes tools.
Aditya Bindal is the AWS Deep Learning senior product manager.
“Now with Amazon SageMaker Operators for Kubernetes, customers can continue to enjoy the portability and standardization benefits of Kubernetes … along with integrating the many additional benefits that come out-of-the-box with Amazon SageMaker, no custom code required,” she wrote in a press release.
Kubernetes is an open-source general-purpose container orchestration system that is used to deploy and manage containerized applications. This is often done via a managed service like Amazon Elastic Kubernetes Service (EKS). Scientists and developers are able to gain greater control over their training and interface workloads with the program.