AWS introduces new features to make machine learning more accessible

Amazon Web Services (AWS) has announced a slew of features and services to make technologies like machine learning more accessible and cost-effective, along with a new USD 10 million scholarship programme for careers in ML. These announcements were made at the 10th annual re: Invent conference.

During his keynote, Swami Sivasubramanian, Vice President of Amazon Machine Learning at AWS, unveiled new solutions to make ML even more accessible and cost-effective as well as new training programmes to further democratise the technology and make it easier to experiment with.

AWS announces six new capabilities for its ML service Amazon SageMaker. This brings together powerful new capabilities, including a no-code environment for creating accurate ML predictions, more accurate data labelling using highly skilled annotators and a universal Amazon SageMaker Studio notebook experience for greater collaboration across domains.

Besides, AWS has announced two new initiatives designed to make ML more accessible for anyone interested in learning and experimenting with the technology.

The AWS AI and ML Scholarship of USD 10 million is a new education and scholarship programme, aimed at preparing underrepresented and underserved students globally for careers in ML.

The programme uses AWS DeepRacer and the new AWS DeepRacer Student League to teach students foundational ML concepts by giving them hands-on experience in training ML models for autonomous racecars while providing educational content centred on ML fundamentals.

AWS is further increasing access to ML through Amazon SageMaker Studio Lab, which gives everyone access to a no-cost version of Amazon SageMaker — an AWS service that helps customers build, train, and deploy ML models.

Kumar Chellapilla, General Manager ML Services at AWS, on Thursday said the industry needs to make it easier for everyone, regardless of their skill level or resources, to be able to incorporate ML into applications and business processes that will help machine learning to truly scale.

“AWS has been helping customers with their machine learning journey and achieving their business outcomes.

“We do that by providing the broadest and most complete set of ML and AI services for builders at all levels of expertise. One key way we do this is by providing training resources to help our customers upskill and learn best practices for machine learning,” Chellapilla said.

He added that AWS offers over 80 free digital training courses that cover a variety of AWS’ ML services and solutions.

The content ranges from foundational level topics such as machine learning essentials for businesses and technical decision-makers, all the way to advanced level topics, such as developing machine learning applications, he noted.

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