Surprise! AWS Leads In ‘Cloud AI Services’ Ranking

Everyone reading this article knows that the cloud space is hot. And it's comprised of many different types of services and platforms to complete a full stack. Ten years ago, it was sufficient to just call the space “cloud”, as it was primarily infrastructure as a service for virtualized workloads. But given the fractalization of the offerings, one must now be very specific about which part of the cloud you're talking about.

One of the most important segments of the cloud space is artificial intelligence, which encompasses machine learning and deep learning, as I believe it will transform almost every business outcome more than any other set of technologies in recent history. As with all aspects of enterprise IT, there are various rankings and assessments available, which my company Moor Insights & Strategy participates in as enterprises are looking for fair and balanced advice on where, when and what they should be spending their money on.

Artificial intelligence is an area that requires a double click, as there are so many different layers to it. While I don't normally cite other analyst assessments. I did want to comment on Gartner's latest Magic Quadrant for AI Developer Services, In this space, it’s not unreasonable to posit that when most people think of AI developer services, most would probably think of Google, closely followed by Microsoft and IBM as well, for different reasons. But what about AWS Machine Learning?

Well, Gartner's Magic Quadrant, showed that AWS is the highest ranked leader in terms of both vision and ability to execute. Yes, let that sink in for second, Gartner says that AWS AI outperforms Google, IBM and Microsoft for AI Developer Services. I know this will surprise many, but I think it is entirely merited as I have closely followed AWS for many years, and thought this day would come, even if this is sooner than I would have predicted.

The AWS ML Stack

I think what you'll see is that AWS has one of the broadest, if not deepest service capabilities in this space. What I applaud about AWS’s approach is that it is truly democratizing AI by delivering tools and services today that enable all developers, even those with no prior experience of ML to join the party. This is super important due to the industry shortage of qualified and experienced machine learning and data science experts. Other cloud services make claims and AWS is delivering the goods.

To look a bit deeper at the stack, let’s start at the bottom layer. Here, AWS offers services that are tailored to developers with machine learning and data science expertise. This includes the most popular frameworks and infrastructures, a multitude of ways to train and infer models, including CPUs and GPUs, custom ASICs, FPGAs even elastic inference capabilities. I see no holes in this layer and am confident based on prior action that when the next framework du jour or better way to do that compute, AWS will be there. This is just what the company does.

The middle layer which AWS calls Machine Learning Services, is all about SageMaker. And at last years’ re:Invent, this layer introduced SageMaker Studio, an end to end integrated developer environment (IDE)  that manages the ML workflow all the way from preparing the data, to training that data to managing and sharing those elements with other developers, to hosting those models, and to deploying and measuring the effectiveness of those models. I wrote about it here. This layer is really targeted at those folks who don't have underlying machine learning experience but do have data experience.

The top layer which AWS calls AI services, will come as the biggest surprise for those people who pigeon-hole AWS in the bucket of infrastructure as a service only. Here they have some very impressive API's for vision, speech, text search, chat bots, and even moving up one level, to capabilities that include Personalization, Forecasting and Fraud detection (all of which are based on Amazon's own internally developed capabilities), They also recently announced Contact Lens which provides ML-powered Contact center analytics for Amazon Connect.

In summary, although the market is still very much evolving, it's encouraging to see that some companies are investing in tools and services for developers at many different levels.

I don’t agree always with Gartner, but its Leader category makes sense based on our research. I have considered AWS a leader in many categories for some years, and I’m pleasantly surprised that Gartner also views them as “the” leader for AI services.

Here’s a link to the report at AWS.

Note: Moor Insights & Strategy writers and editors may have contributed to this article. 

Patrick Moorhead

Patrick founded the firm based on his real-world world technology experiences with the understanding of what he wasn’t getting from analysts and consultants. Ten years later, Patrick is ranked #1 among technology industry analysts in terms of “power” (ARInsights)  in “press citations” (Apollo Research). Moorhead is a contributor at Forbes and frequently appears on CNBC. He is a broad-based analyst covering a wide variety of topics including the cloud, enterprise SaaS, collaboration, client computing, and semiconductors. He has 30 years of experience including 15 years of executive experience at high tech companies (NCR, AT&T, Compaq, now HP, and AMD) leading strategy, product management, product marketing, and corporate marketing, including three industry board appointments.