Amazon Web Services Inc. is not only infusing its own tools with machine learning capabilities, the cloud giant is also providing technology for developers, scientists and engineers to run and manage thousands of complex machine learning workloads at the same time.

An example can be found in how Ampersand Inc., a data-driven TV advertising sales and technology firm, uses AWS Batch to run 50,000 concurrent machine learning models in less than one day.

A look at how AWS enables enterprises to put data to work with artificial intelligence and machine learning-powered low-code and automation initiatives will be the focus for theCUBE, SiliconANGLE Media’s livestreaming studio, during its coverage of the AWS Summit San Francisco event, airing April 20-21. (* Disclosure below.)

Data-heavy work

Ampersand’s business model delivers data-driven insights to assist TV advertisers in planning and measuring campaigns for apps and networks in all U.S. markets. It is complicated, data-heavy work that requires the creation of machine learning models at scale to produce viewer insights. The company uses AWS Batch to translate data partitions into Docker images for code deployment. AWS Batch then schedules and orchestrates the images across Amazon EC2 Spot Instances for running hyperscale workloads.

AWS Batch also allowed Ampersand to scale clusters up and down, an important cost factor when it comes to managing the compute costs associated with generating machine learning models.

Machine learning and low-code/no-code solutions will be on the agenda for the upcoming AWS Summit San Francisco event. TheCUBE will interview AWS executives and industry thought leaders as part of its event coverage on April 20-21.

AWS has infused a number of its core enterprise tools with machine learning capabilities. These include its Athena interactive query technology, which analyzes data in Amazon S3 using standard SQL, and the Redshift cloud data warehouse for deriving insights from stored structured and semi-structured data. In addition, AWS is adding new machine learning workforce optimization features as part of its Amazon Connect contact center-as-a-service platform. Amazon Connect users can leverage machine learning for generating contact center schedules and make short- and long-term predictions for staffing needs.

“We’re trying to bring machine learning closer to data,” said Rahul Pathak, vice president of analytics at AWS, during a recent interview with theCUBE. “It’s about unifying data wherever it lives, connecting it so customers can build a complete picture of their business.”

New low-code/no-code solutions

In addition to bringing machine learning closer to customer data, AWS has developed a set of low-code/no-code tools in the execution of this strategy. The cloud giant announced the availability of no-code SageMaker Canvas for machine learning during the re:Invent conference in December and unveiled Amplify Studio as a low-code solution for web development.

The rollout of new low-code/no-code solutions last year was preceded by the launch of Amazon Honeycode, a low-code software development service, in 2020. AWS is following a strategy to make low code/no code an important part of its cloud infrastructure and platform services while appealing to an enterprise market that research firm Gartner Inc. believes will account for more than 65% of all application development by 2024.

“Amazon has very few white spots within its portfolio of tools, but low code and no code was one of them,” said Constellation Research Inc. analyst Holger Mueller, during an interview with SiliconANGLE at the time of the Honeycode release. “These kinds of tools are critical for enterprise acceleration, as they give technically savvy business users the ability to own their automation faith.”

Livestream of the AWS Summit San Francisco event

The AWS Summit San Francisco event will feature interviews to be broadcast on theCUBE. You can watch the event live. Plus, you can watch theCUBE interviews here on demand after the live event.

How to watch theCUBE interviews

We offer you various ways to watch the AWS Summit San Francisco event, including theCUBE’s dedicated website and YouTube channel. You can also get all the coverage from this year’s events on SiliconANGLE.

TheCUBE Insights podcast

SiliconANGLE also has podcasts available of archived interview sessions, available on iTunes, Stitcher and Spotify, which you can enjoy while on the go.

Guests

Guests include Corey Quinn, chief cloud economist from The Duckbill Group; Serge Shevchenko, startup partnerships at AWS; Jeff Grimes, partner leader for Startup ISVs at AWS; Jeremy Burton, CEO of Observe Inc.; Jon Sakoda, founder at Decibel Partners; Justin Copie, CEO and owner of Innovative Solutions; Matthew Park, director of solutions architecture at Innovative Solutions; Muddu Sudhakar, CEO and Investor at Aisera; and more.

Event Update!

Check out our full event coverage, as well as post-event coverage, and watch the complete event video playlist below:

(* Disclosure: TheCUBE is a paid media partner for the AWS Summit San Francisco event. Neither AWS, the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Image: SiliconANGLE