Amazon SageMaker benefits tens of thousands of customers

AutoCAD, a commercial computer-aided design and drafting software application from Autodesk, uses Amazon SageMaker to optimise its generative design process.

Director of Product Management for AutoCAD at Autodesk Dania El Hassan said, “We wanted to empower AutoCAD customers to be more efficient by providing personalised, in-the-moment usage tips and insights, ensuring the time they spend on AutoCAD is as productive as possible.”

Amazon SageMaker benefits tens of thousands of customers

“Amazon SageMaker was an essential tool that helped us provide proactive command and shortcut recommendations to our users, allowing them to achieve powerful new design outcomes,” added El Hassan.

Salesforce – the world’s leading CRM platform – recently announced new integrations that will enable the use of Amazon SageMaker alongside Einstein – Salesforce’s AI technology.

Rahul Auradkar, executive vice president of Einstein and Unified Data Services at Salesforce said, “One of the biggest challenges companies face today is that their data is siloed. It is difficult to bring data together to deliver customer engagement in real time across all touch points and glean meaningful business insights."

"Powered by Genie, Salesforce’s real-time customer data platform, the Salesforce and Amazon SageMaker integration enables data teams with seamless access to unified and harmonised customer data to build and train machine learning (ML) models in Amazon SageMaker. Once deployed, these Amazon SageMaker models can be used with Einstein to power predictions and insights across the Salesforce Platform,” Auradkar explained.

They are among tens of thousands of customers that have benefited from Amazon SageMaker over the past five years. Customers of all sizes and across all industries are benefiting from Amazon SageMaker to experiment, innovate, and deploy ML models in less time and at a lower cost than ever.

For example, iCapital One and Fannie Mae in financial services, Philips and AstraZeneca in healthcare and life sciences, Conde Nast and Thomson Reuters in media, NFL and Formula 1 in sports, Amazon and Mercado Libre in retail, and Siemens and Bayer in the industrial sector all rely on this service.

Amazon SageMaker, Amazon Web Services’ (AWS) flagship fully managed ML service, was launched at AWS re:Invent five years ago and has become one of the fastest-growing services in AWS history.

In 2017, ML still required specialised skills typically possessed by a limited group of developers, researchers, PhD students, or companies that built their businesses around ML. Previously, developers and data scientists had to first visualise, transform, and preprocess data into formats that algorithms could use to train models, which required massive amounts of computing power, lengthy training periods, and dedicated teams to manage environments that often spanned multiple GPU-enabled servers – and a healthy amount of manual performance tuning.

Additionally, deploying a trained model within an application required a different set of specialised skills in application design and distributed systems. As datasets and variables grew, companies had to repeat this process to learn and evolve from new information as older models became outdated. These challenges and barriers meant ML was out of reach to all but the most well-funded organisations and research institutions.

To break down the barriers, AWS launched Amazon SageMaker to help democratise access to cutting-edge technology, leading to the dawn of a new era in ML.

Ankur Mehrotra, general manager of Amazon SageMaker

General manager of Amazon SageMaker Ankur Mehrotra said, "That’s why we introduced Amazon SageMaker. Over the past five years, we’ve added more than 250 new features and capabilities, including the world’s first integrated development environment for ML, debuggers, model monitors, profilers, AutoML, a feature store, no-code capabilities, and the first purpose-built continuous integration and continuous delivery tool to make ML less complex and more scalable in the cloud and on edge devices."

In 2021, AWS pushed democratisation even further to put ML within the reach of more users. Amazon SageMaker enables more groups of people to create ML models, including the no-code environment in Amazon SageMaker Canvas for business analysts without ML experience, as well as a no-setup, no-charge ML environment for students to learn and experiment with ML more quickly.

Moving forward, AWS continues to aggressively develop new features that can help customers take ML further. Mehrotra said that SageMaker multi-model endpoints (MMEs) allow customers to deploy thousands of ML models on a single Amazon SageMaker endpoint and lower costs by sharing instances provisioned behind an endpoint across all the models.

He added, "Until recently, MMEs were supported only on CPUs, but, Amazon SageMaker MMEs now support GPUs. Customers can use Amazon SageMaker MME to deploy deep learning models on GPU instances and save up to 90 per cent of the cost by deploying thousands of deep learning models to a single multi-model endpoint."

"Amazon SageMaker has also expanded support for compute-optimised Amazon Elastic Compute Cloud instances powered by AWS Graviton 2 and Graviton 3 processors, which are well suited for CPU-based ML inference, so customers can deploy models on the optimal instance type for their workloads," concluded Mehrotra.

AWS offerings turbocharge wide support for customers in Vietnam Amazon Web Services (AWS) is expected to increase investment in infrastructure and digital skills, and bring best practices to Vietnam as a way to increase its footprint in the market. Phil Davis, the US tech firm’s managing director for Asia-Pacific and Japan, discussed with VIR’s Bich Thuy the changes in its future business strategy here.

Public Sector Summit 2022 - Empowering cloud technology in ASEAN The AWS Public Sector Summit opened in Singapore on October 6, discussing cloud transformation and the upscaling of cloud technology in ASEAN.

Clouds in ASEAN set to turbocharge digital innovation Vietnam and regional countries are making big steps in cloud transformation as part of their digital transformation journey, with the trend to further intensify. Eric Conrad, regional managing director for Worldwide Public Sector ASEAN at Amazon Web Services, known as AWS, talked with VIR’s Bich Thuy about the cloud journey in Vietnam and the region, as well as future opportunities at the AWS Public Sector Summit 2022 in Singapore.

ASEAN countries rush to address digital skills gap Amazon Web Services (AWS) has been cooperating with countries across ASEAN in upskilling to meet their digital transformation needs.

AWS expands in Asia-Pacific with launch of Infrastructure Region in Thailand Amazon Web Services (AWS) on October 24 announced plans to open an infrastructure Region in Thailand as a move to boost its footprint in the Asia-Pacific region.