Amazon Web Services (AWS) has revealed that several customers are using AWS machine learning services and the benefits to them.
The number of active users of AWS machine learning services rose more than 250 percent in the last year, fuelled by the adoption of Amazon SageMaker, a managed service that removes the heavy lifting and complexity.
Enterprise customers are using AWS machine learning for building intelligent applications and solutions with the help of AWS’s P2 and P3 graphical processing unit (GPU) instances, deep learning Amazon Machine Images (AMIs), Amazon SageMaker, AWS DeepLens, Amazon Rekognition, Amazon Polly, Amazon Lex, and Amazon Comprehend.
AWS also announced the availability of two new machine learning services — Amazon Transcribe and Amazon Translate.
Amazon Transcribe provides grammatically correct transcriptions of audio files to allow audio data to be analyzed, indexed, and searched.
Amazon Translate is a deep learning powered machine translation service that provides natural sounding language translation in both real-time and batch scenarios.
AWS is already supplying Amazon Lex for conversational interfaces, Amazon Polly for Text-to-Speech, and Amazon Comprehend for processing natural language to discover insights and contextual relationships in text.
“Companies are talking about the potential of machine learning and artificial intelligence, and thinking about how to incorporate these technologies in their applications, but in reality, machine learning has been out of reach for all but the few organizations who have expert practitioners and data scientists on staff,” said Swami Sivasubramanian, vice president of Machine Learning at AWS.
Latest customer wins
Articulate, Cathay Pacific, Cerner, Cookpad, Cox Automotive, DailyLook, DigitalGlobe, Dow Jones, Echo360, Edmunds.com, Enetpulse, Expedia.com, FamilySearch, FICO, GE Healthcare, Genesys, Grammarly, Intuit, KloudGin, Lau Brothers, Limbik, Lionbridge, NFL, One Hour Translation, Polotico.eu, POPSUGAR, PubNub, Realtor.com, RedAwning.com, Shutterfly, TINT, Tinder, VidMob, VMWare, and ZipRecruiter are using AWS machine learning technologies to reimagine customer experiences and innovate across their businesses.
How AWS machine learning is assisting
GE Healthcare is transforming healthcare by delivering better outcomes for providers and patients. “Amazon SageMaker allows GE Healthcare to access powerful artificial intelligence tools and services to advance improved patient care,” said Sharath Pasupunuti, Artificial Intelligence Engineering Leader at GE Healthcare.
“The scalability of Amazon SageMaker, and its ability to integrate with native AWS services, adds enormous value for us. Collaboration between the GE Health Cloud and Amazon SageMaker will drive better outcomes for our healthcare provider partners and deliver improved patient care,” Sharath Pasupunuti said.
Intuit, a financial technology company, is using AWS machine learning.
“We can accelerate the end-user benefits within our flagship products like QuickBooks, Mint, and TurboTax,” said H. Tayloe Stansbury, Intuit’s Chief Technology Officer. “Intuit started our artificial intelligence journey over ten years ago and we have over 150 patents and 40 systems in production in this area.”
Edmunds.com, a car-shopping website with 20 million monthly visitors, is using AWS.
Stephen Felisan, chief information officer at Edmunds.com, said: “Amazon SageMaker is key to helping us achieve this goal, making it easier for engineers to build, train, and deploy machine learning models and algorithms at scale.”
Vineet Singh, chief data officer of Move, believes Amazon SageMaker is a transformative addition to the realtor.com toolset.
Dow Jones Group’s chief product and technology officer Ramin Beheshti said AWS team provided training to participants on Amazon SageMaker and Amazon Rekognition leading up to its Machine Learning Hackathon.
Every day Grammarly is using AWS machine learning technologies for tackling critical communication and business challenges.
“Amazon SageMaker makes it possible for us to develop our TensorFlow models in a distributed training environment,” said Stanislav Levental, technical lead at Grammarly.
Cookpad is Japan’s largest recipe sharing service, with about 60 million monthly users in Japan and about 90 million monthly users globally.
“With the increasing demand for easier use of Cookpad’s recipe service, our data scientists will be building more machine learning models in order to optimize the user experience,” said Yoichiro Someya, research engineer at Cookpad.
Echo360 provides video platform technology that helps instructors and students record, stream, manage, and share interactive video to improve student engagement.
Fred Singer, chief executive officer of Echo360, said: “Amazon Transcribe offers our university partners high-quality transcripts for each video, enabling more powerful search, lower cost captioning of educational video content, and enhanced note-taking, making learning assets more valuable and accessible to students.”
PubNub is a provider of real-time APIs for building chat, device control, and real-time mapping apps.
David Hegarty, director of Product Management, PubNub, said: “We will bring Amazon Translate to PubNub ChatEngine, a framework for chat and serverless deployment. Combined with other artificial intelligence offerings like Amazon Polly (text-to-speech) and Amazon Lex (chatbots).”
One Hour Translation CEO Ofer Shoshan said the company is excited about the initial results with Amazon Translate on a translation project for iHerb. The translation time was cut by 67 percent.
Mike Olivieri, senior vice president of Engineering at Articulate, said: “With the integrated text-to-speech feature powered by Amazon Polly, Articulate Storyline 360 users can generate narration for their e-learning courses very quickly. Amazon Polly makes it easy to switch out languages and voices to localize Articulate Storyline 360 courses and make sure every word sounds the way it should.”
Elie Seidman, chief executive officer of Tinder, said: “Amazon SageMaker simplifies machine learning, helping our development teams to build models for predictions that create new connections that otherwise might have never been possible.”
POPSUGAR, is a media and technology company that delivers multi-platform content to a global audience of over 400 million, sought to take away the pains of manually tagging photos and begin leveraging machine learning automation at a low cost.
“We use Amazon Rekognition to identify celebrities in our huge digital asset library,” said Bjorn Pave, senior director of IT at POPSUGAR. “Amazon Rekognition enabled us to stop manually tagging thousands of photos and provides us with much needed automation for our ever-growing library.”
Enetpulse offers sports data products, including sports data feeds or API services, and sports data solutions, such as live scores and results data.
Mads Mollegaard, chief technology officer, Enetpulse. “Amazon Translate provides us with high-quality machine translation that requires little post editing. This increases professional translator efficiency, thereby reducing costs and turnaround times.”