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Role of Artificial Intelligence And Machine Learning in Cloud Environment

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Artificial Intelligence and Machine Learning are the two technologies that have proven to bring change in various fields. By utilizing AI and ML in the cloud, organizations will be able to enhance performance and efficiency, and drive digital transformation.

Most organizations have already started adopting the public cloud. However, with the inclusion of AI into the cloud, organizations look towards enhancing their productivity and providing better IT solutions to their consumers.

In this article, we will learn:

What is Artificial Intelligence & Machine Learning?

1. How are Artificial Intelligence & Machine Learning are related?
2. What is AI cloud?
3. Role of AI/ML in cloud computing
4. How Rapyder helps you?

At first, we will discuss:

What is Artificial Intelligence & Machine Learning?

Artificial Intelligence: Artificial Intelligence is a broad branch of computer science that involves building intelligent machines that can perform tasks which would normally require human intelligence. Through Artificial Intelligence (AI), machines can learn from experience, adjust to new inputs, and perform tasks similar to humans’.

It was coined for the first time in 1956 by John McCarthy. Over time, this terminology gained more popularity with each passing year. Today, it evolved as a mainstream technology widely used to solve complex problems various industries face.

Do You Know? By 2025, the global AI market is expected to be almost $60 billion.

It was coined for the first time in 1956 by John McCarthy and over the time this terminology gained more popularity with each passing year and today it evolved as a mainstream technology that has widely used to solve complex problems various industries are facing.

Machine Learning: Machine Learning is a subset of Artificial Intelligence that enables systems to automatically learn from its experience and improve themselves without being explicitly programmed. The objective of Machine Learning is to make computers learn themselves without any human intervention and adjust actions accordingly.

Do you know? The Global Machine Learning market is expected to expand at 42.08% CAGR during 2018-2024.

Today, machine Learning is gaining more attention because of the various advantages it provides to various industries, including healthcare, defence, financial services, marketing and many more. Some of the use cases of Machine Learning are:

1. Facial recognition/Image recognition
2. Automatic speech recognition
3. Identify trends and pattern
4. Automated stock trading
5. Recommendation engines.

How are Artificial Intelligence and Machine Learning related?

Both Artificial Intelligence and Machine Learning are the most emerging technologies of the present era that are involved in creating intelligent systems. However, although these two co-related technologies, there is still a minute difference exists between them.


Artificial Intelligence is a broader concept that creates intelligent machines that can stimulate human thinking capability and behavior, whereas, Machine Learning is an application of AI that enables machines to learn from data without doing any coding.

In simple words, we can say that, Machine Learning is a technology that helps to develop Artificial Intelligence. However, Artificial Intelligence doesn’t necessarily have to be developed using Machine Learning – even though it makes Artificial Intelligence much more convenient.

What is AI cloud computing?

AI cloud computing is a concept implemented by several enterprises combining Artificial Intelligence with cloud computing. By providing AI software-as-a-service on hybrid cloud infrastructure, AI hardware and software (including open source) can be combined to enable enterprises to access AI and leverage its capabilities. An AI-powered cloud environment learns from data, predict problems, and resolve them before the uses even notice them.

Role of AI/ML in cloud computing

Artificial Intelligence and Machine Learning have contributed significantly to the growth of the cloud computing world. AL and ML assist automating routine activities within IT infrastructure, increasing its productivity and enhancing the performance and efficiency of organizations.

Through cloud computing, AI capabilities allow businesses to become more efficient, strategic, and insight-driven, all while letting them enjoy more flexibility, agility, and cost reduction.

Let us look into some of the ways AI & ML has changed the cloud landscape:

  1. Lower costs: Adoption of the cloud enables the enterprises to only pay for what they use instead of setting up large data centers and managing them, as is the case with traditional infrastructure costs. This upfront cost can be used to set up the more strategic development of AI tools and accelerators that will generate more significant revenues and save fundamental costs for the enterprise. Further, AI applications can analyze data without human intervention using auto-scaling groups and gain insights from it.
  1. Enhanced data management: Data management is a tedious task. It is one of the huge challenges every enterprise face in this data-driven world. AL and ML applications that run over the cloud helps to manage data effectively by identifying it, updating it, cataloguing it, and providing real-time data insights to customers. Using Artificial Intelligence tools, you can also detect fraudulent activities and notice patterns in the system that looks odd. Banking institutes and financial institutes use this technology to stay relevant and secure in very risky environments.
  1. Intelligent automation: In addition to being more efficient, strategic and insight-driven, AI-driven cloud computing enables companies to automate complex and repetitive tasks to boost productivity and analyze data without human intervention. AI and ML can also be used to monitor and manage workflows within IT departments. As AI takes care of complicated tasks, IT teams can focus more on strategic operations.
  1. Availability of Advanced Infrastructure: Usually, AI applications perform extremely well when running on servers with multiple GPUs (Graphical Processing Units). These systems are extremely expensive and unaffordable for many organizations. AI as a service is thus an option for these organizations that is more affordable.
  1. Team integration: Combining artificial intelligence with cloud computing can also facilitate integration between DevOps teams since the cloud facilitates sharing of information between different sectors and enables teams to work more efficiently.

How Rapyder can help you in implementing AI & ML

Artificial Intelligence & Machine Learning assists in automating tasks within IT infrastructure. Hence, every organization considering implementing these technologies into their system. For a business to evolve and remain competent in the market, such technologies must be widely adopted.

Rapyder, a born-in cloud consulting company, works with a clear vision to help enterprises achieve their business goals, leveraging modern technologies. Rapyder has a team comprising experts that enable organizations to migrate smoothly and efficiently to the public cloud by combining AI & ML into the cloud environment.

Conclusion:

By combining, AI and the cloud, a business can offer greater efficiency, productivity, and security, both in the information handled and the accuracy of AI-structured processes and procedures. Hence, we presented this blog discussing AI/ML and its role in the cloud computing world. Hope you this information is helpful to you. We would request you to share this blog among social media circles and help others understand this subject better.