How Cloud Computing Influences Artificial Intelligence

By Special Guest
Anna Martyushev
  |  July 16, 2020

Cloud computing refers to the availability of computing power and cloud storage without the active management of the user. Some people define it as online data centers that many users can use at a time. Information Technology (IT) operation and on-premises data centers have evolved in the recent past. Renowned companies like Amazon and Microsoft are adopting artificial intelligence (AI) and cloud to integrate intelligent software automation. In this article, we discuss how cloud computing influences artificial intelligence.

Cloud Computing Features which Run Artificial Intelligence Systems

Two cloud-computing features help in operating AI systems effectively. They process high power and are low resources that handle a lot of data. These systems include:

  • Chatbots: Two decades ago, few people believed that human beings could have conversations with computers. Now, chatbots perform different tasks. They use artificial intelligence to communicate with humans. You can make requests or ask chatbots questions. Besides, you can feed them with audio input and text input. As AI shapes online roulette, chatbots provide pundits with unlimited online casino customer support.

  • Cognitive Cloud Computing: Millions of people use the cloud to compute, network, and store processes daily. They offer sufficient information for machine learning. Also, this process provides applications with high-end capabilities in the cloud. The applications make good decisions and perform cognitive functions.

Three Ways that Could Computing Influences Artificial Intelligence

Cloud computing influences AI in the following ways:

1.Availability of High-End GPU

Graphical Processing Units (GPUs) are less flexible than Central Processing Units (CPUs). They follow the same instructions to enumerate in parallel. Deep Neural Networks have a uniform structure with different layers of the network. Each layer has thousands of neurons that perform a specific computation. So, the structure of deep neural networks suits the computations that GPUs perform. They are necessary for deep learning.

GPUs have a high processing power. They are the computational engine for artificial intelligence. AI and GPU-accelerated deep learning create many possibilities in the cloud. The cloud makes AI popular as most hardware lack the required computing power to proficiently run most artificial intelligence applications. Moreover, cloud technology provides machines with sophisticated graphical processing units that are payable on an hourly basis.

2.Cloud Computing Increases Productivity

Many businesses have shifted from storing data in hard disks to keeping it in the cloud. Artificial intelligence has increased the application of IT infrastructure automation. Soon, complex algorithms using deep learning and machine learning will power intelligent infrastructure. Machine learning will promote the use of intelligent CI/CD pipeline. Some applications of artificial intelligence in IT infrastructure include self-healing systems, metric forecasts; AI-based devops analytics, and cost optimization.

3.Infrastructure Optimization Tools

AI workloads consume a lot of IT infrastructure resources. Artificial intelligence is important in controlling, monitoring, and securing IT infrastructure. It has caused a gradual increase in self-managing, self-healing, self-optimizing, self-repairing, and self-securing applications. Some of these tools will be fully developed in a few years. Soon, it might be difficult for many companies to manage sophisticated multi-clouds because AI can perform anomaly detection, log analysis, predictive maintenance, and root cause analysis.

Many current software solutions include cloud computing. Amazon, Google (News - Alert), IBM, and Microsoft dominate the cloud computing market. Even so, it is tricky for the cloud to transform present dynamics. Cloud computing programmers will bring more changes as they adopt artificial intelligence.

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