It’s still early days for machine learning as AWS works with startup community to foster new technologies

Ten years may seem like a long time to some, but in the world of technology, it can also mean that things are just getting started.

This month marks the 10-year anniversary of the launch of Amazon DynamoDB, the flexible NoSQL database service that offers single-digit millisecond performance at scale. The project sprang from a paper written in 2007 that was co-authored by Swami Sivasubramanian (pictured), an Amazon research engineer at the time, who is now vice president of database, analytics and machine learning at Amazon Web Services Inc.

Database technology has evolved since then to allow for providing more than just a place to store and query data. Enterprises today leverage machine learning for predictive analytics within databases, yet Sivasubramanian says even this advancement is only the beginning of a much longer journey.

“In Amazon, we tend to use the phrase that it’s Day One in the age of internet,” Sivasubramanian said. “In the world of machine learning it’s Day One. We just woke up, and we haven’t even had a cup of coffee yet. It’s that early.”

Sivasubramanian spoke with John Furrier and Lisa Martin, co-hosts of theCUBE, SiliconANGLE Media’s livestreaming studio, during the opening session of the AWS Startup Showcase: Open Cloud Innovations event. Serge Shevchenko, global startup partner development manager of developer tools at AWS, was also interviewed during the opening segment, and the discussion focused on AWS initiatives for machine learning education, along with the cloud provider’s work with startups and the open-source community. (* Disclosure below.)

Support for builders

Sivasubramanian’s point around early days for machine learning reinforces the theme of the Startup Showcase event itself. Fledgling companies are leveraging open-source tools to build new technologies on top of cloud infrastructure, and the potential impact of this development is in a very early stage as well.

In December, AWS announced two new initiatives to make machine learning more accessible. These included an AI & ML Scholarship Program and the Amazon SageMaker Studio Lab, which will provide a no-cost version of SageMaker to help users build, train and deploy machine learning models.

“We need to help our builders learn machine learning and help our business leaders understand the power of machine learning,” Sivasubramanian said. “We want to partner with the broader community on problems that really matter to the customers and ensure they get the benefits of this.”

Partnering with the broader community also involves working actively within the open-source world to foster innovation. AWS contributes to a variety of open-source projects, and this has enhanced the cloud provider’s work with a number of companies since the launch of its Global Startup Program in 2019.

“We believe in open source,” Shevchenko said. “In supporting dozens of independent software vendors myself over the years, I’ve seen explosive growth in open-source adoption. We’re very intentional about cultivating a vigorous AWS community.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the AWS Startup Showcase: Open Cloud Innovations event. (* Disclosure: AWS sponsored this segment of theCUBE. Neither AWS nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE