The Cloud and Artificial Intelligence

By Matthew Reeve on 12th September, 2019.

The cloud has rapidly become an essential part of business through the many benefits it offers to companies connected to, and dependent upon, the digital landscape. Its cost effectiveness and scalability are well documented, and a multitude of services are now delivered exclusively to users via the cloud; from Software as a Service (Saas), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). For the difference between these services, read our previous blog post ‘Cloud Services Explained: SaaS, PaaS and IaaS’.

This cloud adoption has seen a dramatic rise in the cloud’s global market value; last year that figure reached $325.1 billion. But hot on the cloud’s heels is Artificial Intelligence (AI). The global AI market is projected to hit $190 billion by 2025, making it one of the fastest growing industries in the world.

That being said, these industries are not mutually exclusive. Both cloud computing and artificial intelligence support each other’s growth and technological advancements. This blog post will explore the relationship between the cloud and AI and investigate the immense potential artificial intelligence has to shape future technologies.

A (Very Brief) AI History Lesson

The concept of creating an artificial brain, capable of learning and making decisions, can be traced to the 1940’s and Alan Turing’s development of the World War II machine ‘The Bombe’, used to break the German Enigma code. This kickstarted research into the newly classified term ‘artificial intelligence’ and scientists started to develop systems capable of communicating and solving equations.

However, by the 1970’s a lack of progress, largely due to computing technologies lacking the required advancements, saw the AI industry lose funding and interest dropped off. This trend continued until the 1990’s when computing technologies advanced. In 1997, IBM’s ‘Deep Blue’ beat world chess champion Gary Kasparov, generating international headlines.

Basic ‘expert systems’ were developed in the 1980’s, capable of answering questions based on catalogued data set within a defined area, such as screening for bank loans or assisting with medical advice. But as the popularity of desktop computers rose and took over these processes, the focus of AI’s purpose shifted into creating ‘intelligent agents’ capable of advanced communication. Many examples of these can be seen today, from Apple’s Siri to Amazon’s Alexa.

Through cloud computing and Big Data, AI is able to analyse and learn from human knowledge and behaviour like never before, leading to big advancements in the industry and the capabilities of its technology. Its decision-making abilities and ways in which it can assist us are constantly evolving and progressing.

Narrow AI vs General AI

It’s important to understand the differences between the two commonly divided categories of AI to understand why it still has a long way to go.

Narrow AI refers to systems which perform a particular task, generally based upon large amounts of data to which an algorithm is applied, such as a self-driving car.

General AI refers to systems that are capable of thinking and learning for themselves, without any input or pre-planned training from humans.

Although Narrow AI is making considerable progress, General AI is reliant on our understanding of how our own brains work, and currently that level of knowledge simply isn’t deep enough. However, that’s not to say General AI and the idea of creating an artificial human brain isn’t possible; but most experts agree this is many years away. In terms of raw brain power and unfocussed intelligence, robots are behind rats. So don’t worry, the possibility of a machine uprising is still a long way off!

The Cloud and AI

As mentioned earlier, the cloud serves as a fundamental component of AI’s usability. The data required for AI to function and make real-time decisions would not be available, at least not quickly enough, if not for cloud technology. IDG network contributor, Gary Eastwood, nicely summarises the relationship between cloud and AI, “the many, disparate servers which are part of cloud technology hold the data which an AI can access and use to make decisions and learn things like how to hold a conversation. But as the AI learns this, it can impart this new data back to the cloud, which can thus help other AIs learn as well.”

In this regard, cloud computing is really one of the cores of anything that artificial intelligence achieves; at least for the time being, anyway. In the future, it’s predicted the two will eventually merge into one seamless technology, complimenting and supporting each other. One thing is for certain, though. As technology around artificial intelligence advances, we will see a prolific increase in streamlined, automised processes, removing the possibilities of human error. As all of these AI-based solutions are supported by the cloud, AI will help grow and strengthen cloud computing’s status throughout industries and the connected digital world.

We hope you’ve enjoyed this blog post. As always, if you have any questions about anything on the blog or any of Secura’s services, please feel free to get in touch.

Image credit: bygermina/

Matthew Reeve

Content Executive

Matthew is Secura's content specialist, producing gripping, emotionally complex, edge of your seat, cloud hosting articles and videos.

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