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The Role of Artificial Intelligence in Cloud Computing- B-AIM PICK SELECTS

Updated: Dec 28, 2021





Introduction:


Cloud computing services have morphed from platforms such as Google App Engine and Azure to Infrastructure which involves the provision of machines for computing and storage. In addition to this, cloud providers also offer data platform services which span the different available databases. This chain of development points in the direction of the growth of Artificial Intelligence and Cloud Computing.



What is Artificial Intelligence?


Artificial Intelligence, popularly referred to as AI, refers to the simulated intelligence in machines. The term refers to the end result of endowing machines with the intellectual prowess peculiar to humans, the ability to reason, learn from the past, discover meaning, or generalize.


It is hinged on the ideology that human intelligence can be defined in such exact terms that a machine can mimic it. These machines are therefore programmed to “think” just like a human would and mimic the actions and reactions of humans to certain circumstances.


The cloud and AI blend perfectly in diverse ways and according to experts, AI might just be the technology to revolutionize cloud computing solutions. AI as a service improves the existing cloud computing solutions and engenders new paths to development.



What are the Existing Types of Cloud Application Development Services?


Infrastructure-as-a-Service (IaaS):

This is the cloud app development service which is most employed by users. It allows you to pay based on the usage of the services provided, a truly flexible plan. The services provided include renting storage, networks, operating systems, servers and virtual machines (VMs).


Platform-as-a-Service (PaaS):

This service was designed to make web creation and mobile app design easier by having an inbuilt infrastructure of servers, networks, databases and storage that eliminates the need to constantly update them or manage them.


Software-as-a-Service (SaaS):

With this, the cloud provider and not the user is tasked with management and maintenance and all the user has to do to gain access is connected to the application over the internet with a web browser on his phone, tablet or P.C. The SaaS is available over the internet on demand or on a subscription basis.



Types of Cloud Deployment:


Public Cloud:

For public clouds like the Microsoft Azure, the cloud provider owns and manages all hardware, software and other supporting infrastructures and is responsible for delivering computing resources – servers, storage – over the internet. As a user, you gain access to these services and manage your account through the web browser.


Private Cloud:

Just as the name implies, a private cloud’s services and infrastructure are maintained on a private network either by the providing company or a hired third-party service provider. It is used by a single organization and is sometimes located in the company’s on-site data center itself.


Hybrid Cloud:

This is a fusion of both the public and the private cloud services. How is this made possible? It is made available by the integration of the personalized data and applications shared by both platforms. Clients looking for more flexible cloud app development solutions and a wide range of deployment options are advised to embrace this technology.



What are the results so far from the merger between AI and cloud computing?


AI Infrastructure for Cloud Computing:


We can generate Machine Learning (ML) models when a large set of data is applied to certain algorithms, and it becomes important to leverage the cloud for this. The models are able to learn from the different patterns which are gleaned from the available data.


As we provide more data for this model, the prediction gets better and the accuracy is improved. For instance, for ML models which identify tumors, thousands of radiology reports are used to train the system. This pattern can be used by any industry since it can be customized based on the project needs. The data is the required input and this comes in different forms - raw data, unstructured data, etc.


Because of the advanced computation techniques which require a combination of CPUs and GPUs, cloud providers now provide virtual machines with incredibly powerful GPUs. Also, machine learning tasks are now being automated using services which include batch processing, serverless computing, and orchestration of containers. IaaS also helps in handling predictive analytics.



AI Services for Cloud Computing:


Even without creating a unique ML model, it is possible to enjoy services which parallel that provided by the AI systems. For instance, text analytics, speech, vision, and machine language translation are accessible to developers. They can simply integrate this into their development projects.


Although these services are generic and are not tailored to specific uses, cloud computing vendors are taking steps to ensure that this is constantly improved. Cognitive computing is a model which allows users to provide their personalized data which can be trained to deliver well-defined services. This way, the problem of finding the appropriate algorithm or the correct training model is eliminated.



Benefits of Leveraging AI and Cloud Computing:


Cost-Effectiveness:

By being accessible through the internet, the cloud application development eliminates the need for expenses on-site hardware and software purchases and setup. It also eliminates the need for on-site data centers and the expenses that come with it – IT experts to manage the centers, servers and round the clock electricity to power and cool the servers.


Increased Productivity:

Unlike a hard drive or local storage device which requires a lot of IT management chores – hardware setup, software patching, racking and stacking – cloud computing is all internet based and as such has no need for this. This gives room for the IT team to focus on achieving other business goals.


Reliability:

With a hard drive or physically accessible infrastructures, the risk of damage is heightened. One faces the risk of the crash, lost files, backup failure and so much more. However, cloud computing solutions ensure business continuity, faster and easier disaster recovery and easier data backup.



Availability of Advanced Infrastructure:


AI applications are generally high performance when on servers with multiple and very fast Graphics Processing Units (GPUs). These systems are however extremely expensive and unaffordable for many organizations. AI as a service in cloud application development becomes accessible to these organizations at a more affordable price.


Conclusion:


The top cloud computing companies listed on GoodFirms strongly believe that the fusion of cloud computing services and AI technology will bring a significant change in the technology industry. Public cloud providers keep on investing in the growth of AI and this will continue to attract the right set of clients to this technology. Even though the technology is still in its early stage, the evolution to come is inevitable and we can expect phenomenal advancements in the future.

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