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How is AI revolutionizing Cloud Computing?

  • Pragya Soni
  • Oct 25, 2021
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Ever wondered how when you login to your new device, all your data is restored back without any difficulty. How does this happen? Well, cloud computing is your answer. What is cloud computing? How does it affect your work and business? 


How does AI influence this system? In this blog, we will understand the concept of AI in Cloud Computing. 



What is Cloud Computing?


Cloud computing is based on the principle of pay-as-you-go pricing. In simple words, cloud computing may be defined as an on-demand delivery of IT resources. 


This technology helps you to access technology services, for example, computing power, storage, and databases, on an as-needed basis. This helps in reducing the unnecessary charges of buying, owning, and maintaining physical data centers and servers.


Suggested blog: Big data analytics


Who provides the access to cloud computing?


There are services like cloud providers. Such software helps in providing all cloud computing related services. Cloud providers help in providing public clouds and maintaining private clouds. Even to individuals these companies provide cloud space on the basis of demands.


Suggested Read - Private vs Private Cloud


Examples of some common cloud provider are as follows:


  1. Amazon Web Services


  1. Nerds Support Cloud.


  1. Microsoft 365


  1. Slack


  1. Google Cloud


  1. Salesforce


  1. Workplace


  1. Adobe Creative Cloud


  1. IBM Cloud


  1. Oracle Cloud


Read a brief detail of these examples, Top 10 examples of cloud computing.


What are the types of cloud Providers?


Cloud providers are classified into following categories.


  1. IaaS


IaaS helps in maintaining cloud infrastructure for users.


  1. PaaS


PaaS providers provide software and hardware required for the purpose.


  1. SaaS


SaaS services provide mobile applications or browsing services to the users.


Who uses Cloud Computing?


From a tiny startup to a multi-level organization. Everyone uses Cloud computing to store its necessary documents and information. Even nowadays, individuals also use cloud space for the purpose. 


Backup is essential for everyone despite its size and structure. Even financial services are using AI clouds for detecting fraud in their network and preventing it.


(Related blog - Blockchain in Cloud Computing)


What are the types of Cloud Computing?

Four types of cloud computing are private clouds, public clouds, multi clouds, and hybrid clouds.

Types of cloud computing

There are basically four types of Cloud Computing. Following is a brief description of all four:


  1. Public Clouds


Public clouds are basically defined as clouds created by IT infrastructure. These clouds are not generally owned by end users. In common language, these clouds are themselves cloud providers.


For example,


  1. Google Cloud


  1. Amazon Web Services


  1. IBM Cloud



  1. Private Clouds


Private Clouds may be defined as the clouds owned by an organization or institutions. They are owned by the end users. The owner company can access the entire data and control the whole structure. In simple words, these clouds are solely owned by the entity. Private clouds are further divided into two types:


  1. Dedicated clouds: Dedicated cloud is a private cloud within a public cloud. The company has the access to maintain their clouds.


  1. Managed private clouds: These are the types of clouds where the company gets its cloud created by some third party. After creation, the same party is responsible for maintaining the clouds. This is too helpful for the institutes that lack the skilled staff.


  1. Hybrid Clouds


A hybrid cloud is the cloud that comprises the clouds created from different networks like Local Area Network, Virtual Private Network, or Wide Area Network. In simple words, Hybrid Cloud is the network of clouds.



  1. Multi Clouds


Multi Clouds consist of two or more clouds but from a common network.


For example, it can either consist of clouds from a public network or clouds from a private network.


Learn more about types of clouds from the red hat experts, types of cloud computing.



How AI works in Cloud Computing?


AI and cloud computing together is often referred to as the AI cloud. AI helps in making the complex process of AI better. The entire process happens in the following ways.


Driving factors of AI Cloud


The AI cloud has the following two driving factors that help in the entire process.


  1. AI Tools


The latest AI tools help in delivering new and increased value to cloud computing. This factor not only makes the entire process more feasible, but also significant in adopting latest innovations.


  1. AI Software


AI software also helps in connecting cloud computing with recent innovations. It also helps cloud computing to fulfill the needs of emerging startups and firms.


Thus, AI cloud helps in bringing two technologies, AI hardware and AI software together. AI cloud works like a hybrid structure, combining the features of artificial intelligence and cloud computing. It helps in creating a cloud space just like the human brain. 


AI cloud delivers AI software-as-a-service providing enterprises access to AI and enabling them to harness AI capabilities. 



Advantages and Disadvantages of AI in Cloud Computing




AI has different advantages in cloud computing. AI has the ability to change the cloud landscape in following ways:

The top 5 advantages of AI in cloud computing are lower costs, intelligent automation, core floworks, insights management, and rapid data analysis.

Some advantages of AI in Cloud Computing

  1. Lower costs


AI helps to remove costs related to on site data centers such as the maintainers and hardware. The costs of AI can be prohibitive but the cloud enterprises can access these tools for a monthly fee making research and development related costs.


  1. Helps in gaining insights


AI tools can gain insights from the data without any human interference.


  1. Intelligent Automation


Enterprises use the power of artificial intelligence driven cloud computing to be more strategic, insight driven and professionally. 


AI can automate the complex and repetitive tasks to complete or to lift the productivity as well as the performance of the data analysis without any human intrusion.


  1. Manage Core Workflows


To monitor AI the IT teams, manage the core workflows. The IT teams focus more on the strategic operation where AI performs the mundane tasks.


  1. Deeper insights


AI uses the historical data and compares it with the most recent data, which provides the IT teams data back intelligence. AI also can recognize patterns and trends in data sets. These deeper insights further help in establishing a better business.


  1. Rapid Data Analysis


AI increases the normal speed of computing. It can perform data analysis very fast so enterprises can rapidly address customer issues and their queries. The advice and the observation gained from the AI results in quicker and efficient results.


  1. Increased security


IT teams use AI powered network security tools to track down the network traffic. AI Powered systems can raise a flag whenever they find an anomaly. This approach helps to prevent any damage to the crucial data.


  1. Improved data management


AI plays an important role in the processing, managing and structuring of the data. AI can boost marketing, supply chain data management and customer care with the real time data. AI tools reflect how data is ingested, managed and modified.




With so many advantages mentioned above. AI has some limitations too. The drawbacks of AI in cloud computing are as follows:


  1. Requires Skilled Labor


When AI is combined with cloud computing it provides various benefits and drawbacks also. For example- Costs of AI is less but it requires a well-trained staff.


  1. Connectivity concerns


Cloud based machine learning needs strong internet connectivity. Its teams require the internet to send the cloud service and to recover the data. Poor internet access can take the advantage of the cloud-based machine learning algorithms.


  1. Time Lag Issue


When the data is processed in the cloud it is quicker than ordinary computing, there is a time lag between transmitting data to the cloud and receiving responses. 


This is an important issue while using the machine learning algorithms for cloud servers, where prediction speed is one of the important concerns.


  1. Data privacy


AI applications need a large amount of data, which include consumer and vendor information.


AI has made almost impossible tasks pretty easy. From reducing costs to reducing the required time. AI has enhanced cloud computing in various ways. Though, the field required few improvements too.  AI and Cloud Computing together have revolved the lives of basic startups and complex firms. With some basic modifications AI can definitely lead a great name in cloud computing.

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