Looking to extend its cloud leadership beyond the IaaS category it created and dominates, Amazon’s AWS unit disclosed big customer wins and new advanced services in the explosive categories of machine learning and blockchain.
In disclosing Q2 financial results late last week, Amazon—the #2 company on my Cloud Wars Top 10 rankings—pounded home its advances in machine learning and blockchain during earnings-call commentary from CFO Brian Olsavsky and also in accompanying slides and press-release material.
With AWS revenue up an impressive 37% in the quarter to $8.38 billion, the company clearly intended to flag its rapidly advancing capabilities in machine learning to demonstrate its ongoing innovation.
ML as a Competitive Advantage
That expansive thinking is essential if AWS hopes to close the gap with the #1 player in the Cloud Wars, Microsoft, which has been expanding its platform services around Azure at a torrid pace. For more on that competitive battle, please see Satya Nadella Admits: Microsoft Cloud Business Is Bigger than Amazon’s.
“We’re seeing a pickup from customers in their usage, in their increased pace of enterprise migration, and in increased adoption of our services—especially our machine learning services,” Olsavsky said on the earnings call (emphasis added).
Olsavsky also offered these additional comments about AWS’s machine-learning progress during Q2:
- “We’re seeing a lot of increased adoption in machine-learning services, especially Amazon SageMaker.”
- “We have tens of thousands of customers who are now using AWS machine-learning services and we’ll continue to innovate on behalf of those customers.”
- “We released more than 200 machine-learning features and capabilities” in the last year.
ML as a Recruiting Tool
The desire by AWS to be a leader in the high-potential field of ML has also had a huge impact on the company’s recruiting efforts, said Olsavsky. He put ML in the same boat as high-profile Alexa in the context of heavy recruiting:
“If you look at some of [Amazon’s] fastest-growing areas like Alexa and AWS teams working on machine learning and other high-end technical projects, our technical headcount actually grew at nearly twice” the rate for the rest of Amazon.
ML in Amazon Customer Storytelling
In parallel, Amazon’s press release disclosing Q2 earnings results included extensive commentary about ML customers and announcements. Here’s a sampling:
- NASCAR is using SageMaker as its standard for cloud-based machine learning and artificial intelligence workloads.
- Emirates NBD, a leading Middle East bank, is using AWS machine-learning services to build a personalized retail customer-banking experience.
- A new ML service promises to make some of Amazon’s business-operations magic available to other companies. Here’s the verbatim account from Amazon: “AWS announced the general availability of Amazon Personalize, a fully-managed machine learning service that trains, tunes, and deploys custom, private machine-learning models. The service brings the same machine-learning technology used by Amazon.com to engage with millions of shoppers to AWS customers, so they can easily develop applications with a wide array of personalization use cases, including specific product recommendations, individualized search results, and customized direct marketing — with no machine-learning experience required.”
- And the Amazon Textract ML service automatically extracts text and data without requiring any “manual review, custom code, or machine-learning experience,” the company said. The service “significantly” lowers document-processing costs and allows customers “to focus on deriving business value from their text and data instead of wasting time and effort on post-processing.”
Blockchain in Amazon Customer Storytelling
On the blockchain front, Sony Music Entertainment Japan selected Amazon Managed Blockchain to develop a system to manage digital-music rights, the press release said.
In addition, the release said, AWS said its Amazon Managed Blockchain service is now generally available to help businesses create and manage blockchain networks. The blockchain used popular open-source technologies and can scale to support “thousands of applications and millions of transactions,” the company said.
Amazon does nothing without careful consideration. The unmistakable decision to emphasize a heavy focus on ML and blockchain indicates considerable ambition for AWS to transcend its #1 spot in IaaS and continue to become a more-powerful player in the high-value PaaS segments.
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