Video: The biggest challenges and opportunities facing Amazon Web Services
https://hub.zdnet.com/core/object/lookup/common/content_video/9f2ce58b-18f8-47c4-a3b5-9930a4d39972AWS CEO Andy Jassy has on Wednesday announced further machine learning capabilities targeted at builders, aimed at making more developers machine learning experts.
During the first keynote of AWS re:Invent, Jassy launched Amazon SageMaker, which he described as an easy way to build, train, and deploy machine learning models.
When announcing AWS' further investment in machine learning, Jassy said with all of the buzzwords flooding the market over the years, machine learning might just be the loudest.
"The hype and hope of machine learning is at an all time high," he said. "But it's still very early for most customers."
Jassy said previously machine learning was reserved only for those who had the resources to build and train the machine.
"There just aren't that many expert machine learning practitioners ... most of them end up living at the big technology companies," the cloud giant's CEO said. "But if we want more to use it, we have to make it more accessible for those that are every day developers."
Amazon SageMaker is a fully managed end-to-end machine learning service that enables data scientists, developers, and machine learning experts to quickly build, train, and host machine learning models at scale.
According to the CEO, it drastically accelerates machine learning efforts already underway and allows users to add machine learning to production applications quickly.
There are three main components of Amazon SageMaker: Authoring, model training, and model hosting.
"We want every day developers and scientists to use machine learning much more expansively," Jassy said.
He also said it's easy to train models in SageMaker, and that the service will also be deployed across multiple availability zones.
Also announced on Tuesday was AWS DeepLens, which is a wireless deep learning-enabled video camera for developers.
The camera runs deep learning models directly on the device, and can be used to build apps while getting hands-on experience with AI, IoT, and serverless computing, allowing for the use of AWS Greengrass, AWS Lambda, and other AWS AI infrastructure.
DeepLens will ship next year, with pre-orders available as of Wednesday.
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Disclaimer: Asha Barbaschow travelled to AWS re:Invent as a guest of AWS.