Artificial Intelligence As a Service: AI Meets the Cloud

To put it like it is, entrepreneurs now see artificial intelligence as the most effective competitive edge one can install in their business. However initially, not many establishments could afford its cost -but now, thank goodness that AI can be served from the clouds as a service.

Yes, the cloud is making sharing of top technologies easier than ever, in fact, the platform has made available amazing computing powers and software possibilities to customers with low financial strength, worldwide. AI software being the most sought of all technologies.

Growth Rate of AI Systems

IDC puts it clear that going by the current demand in cognitive and AI systems which has raised to 50% according to Compound Annual Growth Rate, spending on these techs will shoot to 57 billion come 2021, from the current state of $12 amount.

Current trends show that most of that outlay will rest on cloud served artificial intelligence services in relation to product and big data analytics. RightScale a cloud survey website revealed that machine learning to be particular is the area of AI with the most traction in businesses. Out of the surveyed volunteers, 12% claimed they are already using ML, while 46% said they’ve either started or are interested in investing in the technology.

In simple words, AI as a service is slowly becoming a hot business even with all the threats from the late Stephen Hawking, Elon Musk and the rest. And you know what? Vendors are now serving the soft power as a variety of products; below are some:

Types of AI as a Service

It’s now dawning on most people that artificial intelligence has more branches than earlier thought. It’s a wide technology with interesting applications but its core is nothing more than building machines that can reason -to perform tasks like the human brain.

As of now, this revolves around computer vision technologies that make agents see like humans, machine-learning technologies which empower systems to learn on their own without human necessary, and natural language processing techs which make computers interact with man using text and voice chats. Summarized, below are the currently offered products of AI as a service:

Cognitive Computing APIs

From its name you already depict that this is refereeing to a machine’s ability to recognize, objects and sounds. Through an application programming interface, the product makes it easy for developers to use already set software, for example, set up a photo-sharing app -which they wanted it to have the capability to master individual’s images.

In other words, with the API the developer will not have to design his own facial recognition code as they can cheaply tap the functionality from the cloud. The same case applies to those applications that would require natural language processing, emotional detection, computer vision, knowledge mapping and so on…

Bots and Digital Assistants

Research shows that worldwide, over 56 percent of people who access the internet for information or services have interacted with chatbots, and they liked the experience. On a different account, findings point out that close to 40 million Americans now own a voice assistant speaker. What most of us don’t know is that these agents tap their AI capability from the clouds.

Ideally, it’s unimaginably expensive for an enterprise to create its own bot from scratch, but thanks to vendors who offer bot platform as a service. That is, now, businesses can tap the “raw AI” and train it to fit into their set up. This is literary what happens with voice speakers -whether Amazon’s Alexa or Apple’s Siri, the user have to train his or her digital assistant to fit in their environment.

Machine Learning Frameworks

As stated earlier this is the currently most sought after AI as a service product by both businesses and machine intelligence researchers. The tools in this docket allow developers to design their custom apps that can improve as the environment adjusts. To be particular big data analysts are the biggest users of ML, but the technology can also be used to build other amazing applications like social robots, which could learn to improve a workplace experience.

Also worth mentioning is that setting up your own machine learning frameworks can be the most expensive endeavor when investing in AI because it requires hardware, software and the most costly of all aspects: skilled workforce.

Pre-Managed Machine Learning Services

For customers with less or no knowledge of machine learning, or they don’t want to employ developers or data scientists altogether, they can source for fully managed ML as a service. This can come as pre-designed models, where all one needs to do is drag and drop functions in a template.

Regarding how one can access these services that’s a no-brainer because almost all major cloud computing vendors now serve AI as a service. These include Amazon Web Service, Google Cloud, Microsoft Azure, IBM Cloud, Haptik, and others.

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Saito is a born writer with a passion for crafting “how-to” articles, and sharing tech and innovation news hitting our universe. He’s been doing it for over 5 years now. Besides working as a freelancer -handling several clients, he’s a loving husband to a gorgeous wife.

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