INTRODUCTION:

Definition: Cloud computing is the distribution of computer services over the Internet (“the cloud”), including servers, storage, databases, networking, software, analytics, and intelligence.

Cloud computing and its technologies have greatly advanced artificial intelligence, despite the fact that it was developed much earlier than cloud computing. John McCarthy coined the phrase “artificial intelligence” (AI) for the first time in a workshop at Dartmouth College in 1956. In 1951, the first artificial intelligence (AI) chess and checkers programmers were created.

Role of AI in Cloud Computing:

Cloud computing enables businesses to become more agile, flexible, and cost-effective because it significantly lowers the cost of infrastructure management for businesses. Artificial intelligence (AI) manages enormous data repositories, streamlines data, optimizes workflows, and generates real-time insights to change daily operations.
The SaaS approach is now successfully using AI in the cloud. Many SaaS providers are including an AI layer in their solutions, which provides users and clients with remarkable capabilities. This is especially true for CRM software, which uses customer data to generate tailored, useful insights. Additionally, one of the ways businesses are utilizing AI to enhance their present cloud infrastructure is through AI as a service.AI provides process efficiency, which helps to reduce errors and increase production. AI also makes things more nimble.

Need of Cloud Computing in AI:

The convenience of accessing and editing files is the  primary benefit of  cloud storage. Files are accessible from any device, anywhere with an internet connection.Cloud storage comes in a variety of forms, including block, file, and object storage. Each of them is appropriate for a distinct use case, including block-based volumes, backup and archiving systems, and shared file systems.

Safe access and scalability can be implemented to add or decrease storage based on your demands and budget with cloud computing storage services like Amazon S3, DropBox, or OneDrive. Because of this, this kind of storage is not only very safe but also quite cheap.

Benefits of AI in Cloud Computing:

1. Enhanced data management: Effective data management can be aided by cloud-based AI tools and programmers that recognize, update, and classify data as well as offer users real-time data insights. AI tools also assist in the discovery of aberrant patterns in the system and the detection of dishonest activity. This technology is widely used by banks and other financial institutions, allowing them to stay safe and effective in incredibly risky environments.
2. Automation: Productiveness is added since algorithmic models provide timely insights based on data trends, historicity, etc. By pushing the limits of efficient infrastructure management and introducing cognitive automation to semi-structured and unstructured documents, using AI and cloud computing solutions can enable forces of hyper-automation for enterprises, ensuring minimal disruption.
3. Cost Savings: Businesses can now only pay for what they use by embracing the cloud. This implies a considerable cost savings over the traditional infrastructure costs of constructing huge data centers and managing them. The savings from this arrangement can be utilized to strategically create AI tools and accelerators, which can be used to increase revenue and lower necessary expenditures for the organization.

Types of  Cloud Computing:

1. Public Clouds: Developed from hardware owned and maintained by a third-party company, a public cloud is a set of virtual resources that are automatically provisioned and distributed among numerous clients via a self-service interface. Scaling out workloads that undergo unforeseen demand swings is a simple process.
   Popular Public Cloud Providers are: Alibaba Cloud, Amazon Web Services (AWS), Google Cloud, IBM Cloud, and Microsoft AzureWhat makes a cloud public?
   (i)Resource allocation: Clouds are shared by clients beyond the provider’s firewall. services and online assets that are part of the provider’s collection platforms, infrastructure, and software.
   (ii)Use agreements: Resources are allocated according to demand, although pay-as-you-go approaches are not essential. Some clients use public clouds for free, such as the few research institutes that use the Massachusetts Open Cloud.
   (iii) Management: The provider, at a minimum, oversees the virtualization software, the network, and the gear that enables the cloud.
2. Private Clouds: Private clouds are cloud infrastructures that are only used by the end user and are typically protected by the user’s firewall. Even though private clouds have historically operated on-site, businesses are now constructing them in off-site data centers that are rented from vendors.
   When the underlying IT infrastructure is devoted to a single client with totally segregated access, all clouds become private clouds.How do private clouds work?
   A private cloud combines resources obtained from physical hardware into shared pools using virtualization technology. In this way, the cloud may develop environments without having to virtualized resources from a wide range of physical systems one at a time.By assisting cloud administrators in tracking and optimizing use, managing integration points, and retaining or recovering data, the addition of a layer of management software grants administrative control over the infrastructure, platforms, applications, and data that will be utilized in the cloud. The self-service portion of the cloud is finished when the final automation layer is implemented, replacing or reducing human interaction with repeated instructions and processes, and that collection of technologies becomes a private cloud.
3. Hybrid Clouds: The self-service portion of the cloud is finished when the final automation layer is implemented, replacing or reducing human interaction with repeated instructions and processes, and that collection of technologies becomes a private cloud.
   How to build a hybrid cloud?
   Your hybrid cloud’s organization of its resources will be as distinctive as your fingerprint. However, there are a few fundamental ideas that correspond to the two main strategies for creating a hybrid cloud system.
   (i) Traditional hybrid cloud architecture: Hybrid clouds used to be the result of literally connecting a private cloud environment to a public cloud environment using massive, complex iterations of middle ware. One can build Private cloud on their own.
   (ii) Modern hybrid cloud architecture: A cloud of shared resources is created by combining a number of interconnected components, such as software tools, applications, networking, and server storage, according to a modern hybrid cloud architecture.
4. Multi Clouds: Multi cloud is a cloud approach made up of more than 1 cloud service, from more than 1 cloud vendor—public or private.
   A enterprise might, for instance, utilize Microsoft Azure for disaster recovery, AWS for data storage, and Google Cloud Platform for development and testing.Why multiple clouds?
   (i) Shadow IT: Shadow IT is becoming a reality and helps make Multi cloud possible. Independently developed hardware or software may grow to be large enough to require further supervision. Shadow IT deployment is only combined with the company’s current clouds to form a Multi cloud.
   (ii) Proximity: Some workloads could be hosted by local cloud providers that are located closer to the users in order to improve response times for cloud users who are located thousands of miles away from a company’s headquarters. This approach enables the business to uphold data sovereignty laws—protocols that subject data to the laws of the country in which it is located—while also maintaining high availability.

Companies offering Cloud Computing Services:

1. Amazon Web Services: Hybrid clouds used to be the result of literally connecting a private cloud environment to a public cloud environment using massive, complex iterations of middle ware. One can build Private cloud on their own.
2. Modern hybrid cloud architecture: A cloud of shared resources is created by combining a number of interconnected components, such as software tools, applications, networking, and server storage, according to a modern hybrid cloud architecture.
3. Google Cloud Platform: The infrastructure as a service capabilities and strong technical foundation of the Google cloud platform, or GCP, allow it to rule the search business. When it comes to data analytics, machine learning, and AI, GCP is a pioneer. Open source and open systems are of interest to the cloud provider.
4. IBM’s Blue Cloud: The service promises an extensive and highly developed enterprise solution for the technology industry. Favored by major and mid-sized industries, IBM currently has a presence around the world. It has made a commitment to developing its open, hybrid methodology and cloud infrastructure. In the rapidly developing multi-cloud market, IBM is also positioned fairly well.
5. Systems Applications and Products: The legacy vendor SAP is now making a significant cloud-based impact. The company’s powered in-memory database has a business following that precedes the cloud. It uses the same architecture as the cloud service providers. SAP’s cloud revenue has recently experienced tremendous growth.

Conclusion:

Cloud computing has the potential to change the world significantly. It offers its users and businesses a wide range of advantages. Future AI applications are predicted by a variety of analysts and tech firms across a range of industries and use cases. Effective AI use cases will be greatly shaped by cloud computing and delivery strategies. Edge computing, which extends cloud capabilities to on-premises devices with low latency and offline capabilities, will also offer more use cases (such as video analytics), since businesses will have more data to analyze on-site. Additionally, it is anticipated that quantum computing would boost AI, particularly in machine learning.