Proving the Business Case for the Internet of Things

AWS announces five AI services at Re:Invent

Steve Rogerson
December 4, 2019



At this week’s AWS Re:Invent conference in Las Vegas, Amazon Web Services (AWS) announced five artificial intelligence (AI) services designed to put machine learning in the hands of more application developers and end users with no machine learning experience required.
 
The five services are:

  • Kendra reinvents enterprise search by using natural language processing and other machine learning techniques to unite multiple data silos inside an enterprise and consistently provide high-quality results to common queries instead of a random list of links in response to keyword queries.
  • CodeGuru helps software developers automate code reviews and identify an application’s most expensive lines of code.
  • Fraud Detector helps businesses identify online identity and payment fraud in real time, based on the same technology developed for Amazon.com.
  • Transcribe Medical offers healthcare providers accurate, real-time speech-to-text transcription so they can focus on patient care.
  • Augmented Artificial Intelligence helps machine-learning developers validate machine learning predictions through human confirmation.
The services use AI to allow more developers to apply machine learning to create better end user experiences, including machine learning-powered enterprise search, code reviews and profiling, fraud detection, medical transcription, and human review of AI predictions.
 
Machine learning continues to grow at a rapid clip, and today there are tens of thousands of users doing machine learning on AWS, including many that opt to use AWS’s fully managed AI services. These companies include Alfresco, Bayer Crop Science, Cerner, CJ Cox Automotive, C-Span, Deloitte, Domino’s, Emirates NBD, Fred Hutchinson Cancer Research Center, Fico, Finra, Gallup, Kelley Blue Book, Kia, Mainichi Newspapers, Nasa, Price Waterhouse Coopers, White House Historical Association and Zola.
 
In the past year, AWS has introduced several fully managed AI services such as Amazon Personalize and Amazon Forecast that allow users to benefit from the same personalisation and forecasting machine learning technology used by Amazon’s consumer business to power its customer experiences.
 
AWS says its customers are interested in learning from Amazon’s experience using machine learning at scale to improve operations and deliver better customer experiences, without needing to train, tune and deploy their own custom machine learning models. The five added AI services build upon Amazon’s experience with machine learning, and allow organisations of all sizes across all industries to adopt machine learning in their enterprises with no machine learning experience required.
 
“Companies across various industry segments tell us that they want to leverage Amazon’s extensive experience with machine learning to address some of the common challenges they face as enterprises on an on-going basis,” said Swami Sivasubramanian, vice president of Amazon Machine Learning. “These challenges include internal search, helping software developers write better code, identifying fraudulent transactions, and improving the overall quality of all machine learning systems. With decades of experience in building machine learning systems, Amazon has created internal systems that successfully address such challenges, and today’s launches are the next iteration of the same customer obsession that spurred the development of these systems. With these launches, we are excited to make these machine learning-powered capabilities available to enterprise users without requiring any machine learning expertise.”
 
AWS is now a cloud, machine learning and artificial intelligence provider for the Seattle Seahawks gridiron football team. In addition to moving most of its infrastructure to AWS, the National Football League (NFL) team will use AWS’s services, including compute, storage, database, analytics and machine learning to drive deep analysis of game footage to inform game strategy, improve operational efficiencies, and accelerate decision-making to advance team performance game to game. The Seahawks will combine the weekly NFL Next Gen Stats player tracking data, which tracks the position of the ball and every player ten times per second, with its own player and club data to develop custom analytics and proprietary statistics.