How cloud serves as the foundation of AI

As companies migrate to and run operations in the cloud, leaders are looking to the next horizon: innovating from the cloud with AI

machine learning cloud ai artifical intelligence

As companies migrate to and run operations in the cloud, leaders are looking to the next horizon: innovating from the cloud with artificial intelligence (AI).

Cloud is the underlying platform with the data storage capacity and massive processing capability that will help enable AI innovation at the speed demanded. Companies are already starting to integrate a variety of AI-driven technologies across voice, vision, language and machine learning in order to transform their businesses. Accenture research shows that 85 percent of business and IT executives anticipate making extensive investments in one or more AI-related technologies over the next three years.

In fact, AI both simplifies and improves peoples’ experiences with technology. Case in point: AI is making technology easier to use through more natural interfaces like conversation. People now commonly use their voice to ask mobile phones for directions and reminders. We are starting to drive vehicles that act and react to our instructions. And we will increasingly talk to in-home devices to complete tasks, whether it’s turning on lights, cuing a favorite playlist, paying the monthly bills or hundreds of other skills.

With a sound strategy for implementing AI technologies, companies will also be able to create hyper-personalized engagement journeys with customers and employees—increasing loyalty in the process. For example, providers in the auto insurance industry are using AI technologies to develop personalized quotes for customers based on individual risk assessments, regardless of the type of car a customer drives or where a customer lives. This is a disruptive shift with industry-wide implications. Instead of looking to third-party actuarial companies to predict probabilities of events, auto insurance providers are creating a real-time, in-house actuarial risk table for every customer.

Cloud supports innovation and packaged services across AI

Examples like this herald an exciting future in which companies and people can achieve much more by using AI capabilities. However, building and implementing AI solutions is not easy—and it must be done responsibly.

While it’s true that hyper-scale cloud providers are offering packaged AI services through application programming interfaces (APIs), they should be considered as building blocks of an AI solution, not as software-as-a-service. These APIs still require complex integration to assemble into an enterprise-ready solution. As such, a growing number of companies are turning to the cloud ecosystem, which is experienced in managing the high complexity that comes with bundling these packaged AI services into a solution to achieve faster results.

What’s more, cloud supports the massive data storage capacity, scalable compute power and embedded graphic processing units (GPUs) to handle the huge data stores and algorithms that AI systems need to work on an ongoing basis. With GPU acceleration, for example, neural network training is 10 to 20 times faster than with CPUs. Adding to this, cloud offers built-in agility and quality of performance, making it the most viable place for many of the complex AI-driven business processes that drive rapid innovation.

Choose the best-fit cloud provider and start innovating with AI now

Since cloud is the foundation of AI, every company must choose their public cloud platform provider wisely to help ensure that future innovation in AI will be supported. Hyper-scale cloud providers clearly recognize the opportunity and are stepping up with a range of AI services.

For instance, Amazon Web Services (AWS) released Amazon Lex, a conversational engine that makes it easier for companies to build chat bots; Amazon Polly, to generate voice-like output; Amazon Rekognition for building computer vision solutions; and Amazon Machine Learning, which uses well-defined algorithms to teach machines to make better predictions.

Day one is getting the platform in place to support AI innovation, then selecting a use case within your organization that would benefit from AI voice, vision, language or machine learning services. It makes sense to start with a small project that can be quickly built out, providing time to fail-fast if necessary and then to iterate, iterate, iterate to develop a truly innovative product or service.

“AWS cloud is putting AI into the hands of any company or developer looking to add intelligence to their applications. It’s early days, but this technology is moving forward quickly, and already showing success in fields as diverse as healthcare and real estate,” said Dr. Matt Wood, general manager for artificial intelligence at AWS. “There’s a huge opportunity to dive in and continue to accelerate the pace of innovation.”

Copyright © 2017 IDG Communications, Inc.

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