Cloud Computing and Artificial Intelligence

Over the last few years, cloud computing has been growing at a rapid pace. It is becoming the standard in the modern software solutions. Forrester believes that cloud computing will be a $191 billion economy by 2020. In accordance with this 2016 Condition of Cloud Survey conducted by RightScale, 96 percent of its respondents are already utilizing the cloud, using more enterprise workloads shifting towards public and private clouds. Adoption in both hybrid and DevOps have become also.


The AI-Cloud Landscape

So where could the cloud computing marketplace be headed? Would the next wave of cloud calculating involve artificial intelligence? It certainly seems that way. In a marketplace that’s largely dominated by four big companies — Google, Microsoft, Amazon, and IBM — AI could possibly interrupt the present dynamic.

In the last few years, there has become a surge of investment from AI capabilities in cloud platforms. The big four (Google, Microsoft, Amazon and IBM) are making massive strides in the AI world. Microsoft is currently offering over twenty cognitive solutions such as language understanding and assessing images. This past year, Amazon’s cloud division additional an AI service that lets people add analytical and predictive capabilities to their software.

The present AI-cloud landscape may essentially be categorized into two classes: AI cloud services and cloud machine learning programs.

AI Cloud Services

Example of AI cloud Companies involve technologies such as Microsoft Cognitive Services, Google Cloud Vision, and IBM Watson. In this kind of model, companies incorporate AI abilities in applications without having to invest in costly AI infrastructures.

Cloud Machine Learning Platforms

On the reverse slide, you will find cloud machine learning programs. Machine learning is a technique of data analysis that overlooks analytical model construction. It enables for computers to locate patterns automatically in addition to areas of importance. Azure Machine Learning and AWS Machine Learning are examples of cloud machine learning platforms.

IBM and Google Earning Enough


Lately IBM and Google having been making news from the AI kingdom and it reveals a shift within the technology sector towards learning. Just a month, IBM introduced Project DataWorks, that is allegedly an industry first. It is a cloud-based analytics and data system that could integrate various types of information and enable AI-powered decision making. The platform offers an environment for cooperation between users and information specialists. Using technologies such as Pixiedust and Brunel, users may create information visualizations with quite minimal programming, allowing everybody in the company to gain insights initially appearance.

Earlier this month at an event in San Francisco, Google introduced a family of cloud computing solutions that would allow any developer or company to use machine learning technologies that fuel a few of Google’s most powerful solutions. This movement is an effort by Google to find a bigger foothold in the cloud calculating market.

AI-First Cloud

According to Sundar Pichai, chief executive of Google, calculating is evolving by a mobile-first to a AI-first world. So what would a next-generation AI-first Cloud like? Simply put, it might be one built around AI abilities. In the upcoming years, we could possibly see AI being vital in improving cloud services such as computing and storage. The next wave of cloud computing platforms could also see integrations involving AI and the existing catalogue of cloud solutions, for example Paas or SaaS.

It remains to be seen whether AI may interrupt the present cloud computing marketplace, but it will surely influence and inspire a new wave of cloud computing platforms.

From Joya Scarlata

Joya Scarlata

Joya Scarlata is currently a senior analyst at InterraIT, also a San Jose-based tech solutions and services company, working in the areas of market research and promotion.

She loves tracking current tech and marketing trends.

Comments are closed.