How Cloud Computing Can Provide Solid Support for AI?

How can cloud computing support artificial intelligence

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Artificial Intelligence (AI) has seen a rapid evolution in recent years. It has managed to take over various tasks that were often left for humans to handle. Artificial intelligence is even closer to us than most people think; this can be supported by the fact that AI is now present in the automated phone systems that we use in our daily activities.
It can be seen in our Google map that helps us navigate traffic and in GPS for getting real-time updates on the traffic conditions of a particular area.
AI is a rapidly growing industry with its projected growth rate expected to reach about US$89 billion per year by 2025, according to information from Statista. However, a huge percentage of this projected growth is expected to be fueled by the integrated application of cloud computing and Artificial Intelligence technology.
The application of cloud computing has evolved from platforms like Microsoft Azure and App Engine by Google to frameworks that provide virtual machines for various computing and storage activities on the cloud.
A lot of these cloud computing services have also decided to provide data platform services, which include various kinds of databases. The features that accompany the evolution of cloud computing has made the integration of AI and Cloud computing easier.
Furthermore, the applications of the integrated version of Cloud Computing and AI can be seen in Virtual assistants like Alexa from Amazon, Siri from Apple, and Google Home. These entire Al powered technologies have been designed to help make your daily activities easier to carry out.
Moreover, these technologies can carry out commands on verbal cues. These commands can range from playing music through a connected sound system, buying something online, or changing the settings of the smart home thermostat. Besides, all of this is made possible with the seamless integration of Artificial Intelligence and cloud computing in these pieces of technology. This might come as news to a lot of people, but it is the customized integration of AI and Cloud computing that created the intuitive experience we get from these technologies.
How can cloud computing support artificial intelligence

How Cloud Computing is supporting Artificial Intelligence?

Here are a few ways that cloud computing has been supporting Artificial Intelligence;

Scalability

Thinking about the big picture, the perfect integration of cloud computing and AI has helped make many organizational systems to be more efficient, perceptive, and focused. It provides organizations with greater versatility, efficiency, and affordability by enabling them to host their databases and data in the cloud instead of getting the physical hardware components to store them.
Besides, adding AI to cloud computing has now enabled businesses to monitor their data and analyze it for patterns and insights to improve customer experience and enhance the flow of operations.
Furthermore, the aspects of scalability, makes cloud computing capable of handling a high volume of data. So, for instance, you want to make use of the huge volume of data gotten from IoT sensors, you can forward them to ML (Machine Learning) algorithms or the IBM Watson Cloud to help manage the data and analyze it for patterns and insights to help improve your products and revenue.

Resources

If you use Artificial Intelligence without cloud computing, you might find it to be a bit challenging and process-intensive. Without proper resources, you will probably struggle with it, but with Cloud Computing, you can get all the resources you need for your AI needs and more. With Cloud Computing, you can get as many resources as you need on your virtual machine. Also, you can even get virtual hardware components of various capabilities.
By integrating Artificial Intelligence with cloud computing, you will be enhancing both your AI and cloud computing experience.

Cost

Without the integration of cloud computing, most artificial intelligence projects would be isolated, and therefore, they would attract greater costs as a result of the huge amounts of resources needed to operate them. AI projects often require data, hardware, and software components for the algorithms to work, all of which can be provided by cloud computing.
However, that is not all; cloud computing will also provide easy access to ML attributes, including language translation, facial recognition, and so on.

Memory and Storage

Like we have already mentioned, Artificial Intelligence is very complex and process-intensive, so it requires great memory and data storage capacity to handle its algorithms. Cloud computing can meet these requirements easily and at an affordable price as well. One of the main components of cloud computing that will help in this is the GPU (Graphics Processing Unit), which has been replacing the Central Processing Unit (CPU) in the past few years.
The GPU features enhanced computing power that allows it to handle huge amounts of data and algorithms easily. This is exactly what Artificial Intelligence needs.
A recent study has shown that GPU helps enhance the speed of neural network training by 10 to 20 times the speed when using CPU. This enhanced speed and quality of performance are one of the best ways cloud computing can support artificial intelligence to improve technologies.

Data Management

Now let us discuss ML algorithms, or more specifically, Data Science. While cloud computing is widely used by companies all over the world, these companies are mainly interested in the automation and scalability benefits it provides and tends to ignore the ability of the cloud to help enhance customer experience, that is, optimizing all customer interactions.
There are situations when customer data from one part of a company is not the same as the one in another part of the same company. This might be as a result of a recent change in the organizational structure like a merger or acquisition. Apart from customer data, this kind of situation can affect digital transformation as a whole due to the existence of isolated data.
With many isolated data sources on our devices, including emails, social media, online store, SMS, and in-store sales, it has become increasingly difficult to manage data. However, this can be made easier with Cloud Computing.
Big data solutions can be applied with cloud computing to deal with issues related to data quality and real-time data management. This allows companies to efficiently manage their customer data and analyze it for insights. And customer demand can also be predicted with data aggregation. This information can be used to form customer-centric marketing strategies and customized products.

Accessibility

We can thank cloud computing for the fact that Artificial Intelligence is available around the world. Artificial Intelligence services can be accessed anywhere around through the cloud. However, this involves a complex integration procedure.
Artificial intelligence can be added to the cloud through APIs, which need to be properly integrated with AI to ensure it is ready for the public.
Moreover, Cloud computing is capable of handling huge amounts of Artificial Intelligence services while enhancing its results.

AI Service Deployment

There are a lot of companies out there that are deploying AI integrated cloud services with the help of PaaS (Platform as a Service) and SaaS(Software as a Service). Based on the current applications of the integration of Artificial Intelligence and cloud computing, there are two main groups;
  • Cloud Machine Learning (CML): Tools that aid the development of machine learning models like Azure ML, Google Cloud ML (TensorFlow), and AWS ML.
  • Artificial Intelligence Cloud Service: These are tools that provide users with abstract complex Artificial Intelligence features through an API (Application Programming Interface) call. These tools include Google Cloud Vision, Natural Language API, IBM Watson, and Microsoft Cognitive Services.

Application Of Dynamic Cloud Services

The complex integration of Artificial Intelligence and Cloud Computing has provided companies with a lot of game-changing tools. For example, adding a cloud-based retail AI Module will make it easier for companies to market their goods and services. This tool comes with a cost feature that is automated to modify the cost of a product in case of various levels of demand, inventory, market trend, and competitor sales. Besides, this is done with the help of complex analysis based on a model that uses advanced neural networks to give these companies greater control of their data with real-time results.
Artificial Intelligence modules like the one discussed above will help an organization optimize its pricing for varying situations. This means that it does not just provide data analysis but also implements strategies to respond to certain patterns without any intervention from the company’s personnel.
Both Artificial Intelligence and Cloud Computing have already found their way to almost every industry in the world because of their wide range of applications, but the integration of both of them offers an even wider range of applications.
These applications can be seen everywhere, ranging from our mobile devices, GPS, digital assistants to process automation. If you read the article above, you will understand just how cloud computing can support artificial intelligence. It is recommended that you look into Artificial Intelligence and Cloud Computing for your business if you want to optimize your work processes, collect customer data, and analyze it to gain insights on the market.

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