10 AI ML In Cloud Computing Trends To Look Out For In 2024

Types of Cloud Computing

1. Platforms as a Service (PaaS)
2. Infrastructure as a Service (IaaS)
3. Software as a service (SaaS)
4. Everything as a service (XaaS)
5. Function as a Service (FaaS)

Let’s Know Some Numbers

• The global cloud computing market is expected to witness a compound annual growth rate of 14.1% from 2023 to 2030 to reach USD 1,554.94 billion by 2030.
• 58.7% of IT spending is still traditional but cloud-based spending will soon outpace it (Source: Gartner)
• Cloud adoption among enterprise organizations is over 94% (Source: RightScale)
• Over half of enterprises are struggling to see cloud ROI (Source: PwC)
• Over 50% of SMEs technology budget will go to cloud spend in 2023 (Source: Zesty)
• 54% of small and medium-sized businesses spend more than $1.2 million on the cloud (Source: RightScale)
• 42% of CIOs and CTOs consider cloud waste the top challenge (Source: Zesty)

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Expert Comments on The Cloud Computing Domain

Leveraging AI and ML for advanced security measures: As cyber threats evolve, becoming perpetually dangerous and complex, intelligent security measures are imperative to counter this. For example, AI-driven anomaly detection can identify unusual patterns in network behavior, thwarting potential breaches. At the same time, ML algorithms are adept at recognizing patterns, enhancing threat prediction models, and fortifying defenses against emerging risks. And with AI and ML models continuously being trained on new data, their responses and accuracy will only improve as we head into 2024. Continued improvement of cloud automation: As AI and ML become more advanced, this will, of course, enhance their capabilities, allowing for more processes to become automated and more intelligent management of resources. By providing increasingly precise insights, AI and ML can improve processes such as predictive scaling, resource provisioning, and intelligent load balancing.

In the landscape of 2024, the convergence of AI/ML and data storage is poised to bring about substantial advancements. The spotlight shines on three pivotal areas:

Anomaly Detection and Optimization: Expect a paradigm shift as AI and ML redefine data storage with advanced anomaly detection mechanisms. This innovation goes beyond traditional bounds, promising to optimize system performance with unparalleled precision.

Security & Privacy Control for Compliance: In response to ever-evolving regulatory landscapes, Explainable AI takes center stage. This technology not only fortifies storage systems but also introduces robust security and privacy controls, ensuring strict compliance with regulatory standards.

Access to Data with Human Language: Breaking barriers, natural language processing breakthroughs promise a more intuitive interaction with stored data. This trend enables users to effortlessly engage with and retrieve information using human language, creating a seamless and user-friendly experience in the data access realm.

10 AI ML In Cloud Computing Trends To Look Out For In 2024

Artificial Intelligence (AI) and Machine Learning (ML) are playing a significant role in shaping the future of cloud computing.

1. AI-Optimized Cloud Services: Cloud providers will offer specialized AI-optimized infrastructure, making it easier for businesses to deploy and scale AI and ML workloads. The intersection of cloud computing with AI and ML is one of the most exciting areas in technology right now. Since they need a large amount of storage and processing power for data collecting and training, these technologies are economical. High data security, privacy, tailored clouds, self-automation, and self-learning are some of the major themes that will continue to flourish in this industry in the next years. A lot of cloud service providers are putting money into AI and ML, including Amazon, Google, IBM, and many more. Some examples of Amazon’s machine learning products are the AWS DeepLens camera and Google Lens.

2. AI for Security: AI and ML will play a critical role in enhancing cloud security by detecting and responding to threats in real-time, with features like anomaly detection and behavior analysis. No company or group wants to take chances with their data’s safety. The safety of the company’s information is paramount. It is important to reduce the likelihood of data breaches, accidental deletion, and unauthorized changes. It is possible to adopt measures to guarantee very good data security and reduce losses to a minimum. To reduce the likelihood of data breaches, encryption and authentication are essential. Backing up data, checking privacy regulations, and using data recovery methods can all help lessen the likelihood of data loss. We will conduct comprehensive security testing to identify vulnerabilities and implement fixes. Both the storage and transport of data should be done with utmost care to ensure security. Numerous security procedures and techniques for data encryption are employed by cloud service providers to safeguard the data.

3. Serverless AI: The integration of AI with serverless computing will enable efficient, event-driven AI and ML applications in the cloud, reducing infrastructure management overhead. Per-user backend services are provided via serverless computing. Developers don’t need to handle servers while coding. The cloud provider executes code. Instead of paying for a set server, cloud customers will pay as they go. No need to buy servers—a third party will handle the cost. This will lower infrastructure expenses and improve scalability. This trend scales automatically as needed. Serverless architecture has several benefits, including no system administration, reduced cost and responsibility, easier operation management, and improved user experience even without the Internet.

4. Hybrid and Multi-Cloud AI: AI will help manage and orchestrate AI workloads across hybrid and multi-cloud environments, ensuring seamless integration and resource allocation. Companies are increasingly using the strengths of each cloud provider by spreading their workload over several providers, allowing them more control over their data and resources. With multi-cloud, you may save money while reducing risks and failure points. Instead of deploying your complete application to a single cloud, multi-cloud allows you to select a specific service from many providers until you find one that suits your needs. As a result, cloud service providers will be even more motivated to include new services.
5. Virtual desktops will become widespread: VDI streams desktop images remotely without attaching the desktop to the client device. VDI helps remote workers be productive by deploying apps and services to distant clients without extensive installation or configuration. VDI will become more popular for non-tech use cases while WFH remains the standard in some regions. It lets companies scale workstations up or down with little cost, which is why Microsoft is developing a Cloud PC solution, an accessible VDI experience for corporate users.

6. AI for Data Management: AI will assist in data categorization, tagging, and data lifecycle management in the cloud, making data more accessible and usable. Storage of vast amounts of data on GPUs, which can massively parallelize computing, will be a major advance. This trend is well started and expected to expand in the future years. Data computation, storage, and consumption, as well as future business system development, are all affected by this transition. It will also require new computer architectures. As data grows, it will be dispersed among numerous data center servers running old and novel computing models. Due to its inability to process many nodes, the traditional CPU will become obsolete.

7. Cost Optimization in the Cloud: With the exponential growth of cloud users, cost management has emerged as a top priority for companies. Consequently, cloud service providers are putting resources into creating new services and solutions to assist their clients in cost management. Instance sizing suggestions, reserved instance options, and cost monitoring and budgeting tools are all part of cost management tools that customers may utilize to optimize expenditure.

8. Automated Cloud Management: AI-driven automation will streamline cloud management tasks, such as provisioning, scaling, and monitoring, reducing manual intervention. The possibility of automation is Cloud’s secret ingredient. When implemented correctly, automation may boost the productivity of your delivery team, enhance the reliability of your networks and systems, and lessen the likelihood of slowdowns or outages. Automating processes is not a picnic. More and more money is going into AI and citizen developer tools, thus there will be more devices available to make automation easier for cloud companies.

9. AI-powered DevOps: AI and ML will optimize DevOps processes in the cloud, automating code testing, deployment, and infrastructure provisioning. Cloud computing helps clients manage their data, but users can confront security challenges. Network intrusion, DoS assaults, virtualization difficulties, illegal data usage, etc. This can be reduced via DevSecOps.

10. Citizen Developer Introduction: One of the earliest developments in cloud computing is the rise of the citizen developer. With the Citizen Developer idea, even non-coders may tap into the potential of interconnected systems. If This Then That and similar tools made it possible for regular people (those of us who didn’t spend four years obtaining a degree in computer science) to link popular APIs and build individualized automation. By the end of 2024, a plethora of firms will have released tools that simplify the process of creating sophisticated programs using a drag-and-drop interface. This includes Microsoft, AWS, Google, and countless more. Among these platforms, Microsoft’s Power Platform—which includes Power Flow, Power AI, Power Builder, and Power Apps—is perhaps the most prominent. If you combine the four of them, you can create sophisticated apps for mobile and web that communicate with other technologies your company uses. Additionally, with the release of HoneyCode, AWS is showing no signs of stopping either.

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Conclusion

These trends represent the ongoing evolution of AI and ML in the cloud, with a focus on improving efficiency, security, and the management of cloud resources. Staying informed about these developments will be crucial for businesses to leverage the power of AI and ML in their cloud computing strategies in 2024 and beyond.

IT changed drastically with cloud computing. The future of the cloud will improve product and service development, customer service, and discovery. In this evolving context, corporate leaders who embrace cloud computing will have an edge in their tools and software, cultures, and strategy.

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