AI For Cloud Services

AI Infrastructure for Cloud Computing

We can generate Machine Learning (ML) models when a large set of data is applied to certain algorithms, and it becomes important to leverage the cloud for this. The models are able to learn from the different patterns which are gleaned from the available data.

As we provide more data for this model, the prediction gets better and the accuracy is improved. For instance, for ML models which identify tumors, thousands of radiology reports are used to train the system. This pattern can be used by any industry since it can be customized based on the project needs. The data is the required input and this comes in different forms - raw data, unstructured data, etc.

Because of the advanced computation techniques which require a combination of CPUs and GPUs, cloud providers now provide virtual machines with incredibly powerful GPUs. Also, machine learning tasks are now being automated using services which include batch processing, serverless computing, and orchestration of containers. IaaS also helps in handling predictive analytics.


AI Services for Cloud Computing

Even without creating a unique ML model, it is possible to enjoy services which parallel that provided by the AI systems. For instance, text analytics, speech, vision, and machine language translation are accessible to developers. They can simply integrate this into their development projects.

Although these services are generic and are not tailored to specific uses, cloud computing vendors are taking steps to ensure that this is constantly improved. Cognitive computing is a model which allows users to provide their personalized data which can be trained to deliver well-defined services. This way, the problem of finding the appropriate algorithm or the correct training model is eliminated.


Benefits of Leveraging AI and Cloud Computing


By being accessible through the internet, the cloud application development eliminates the need for expenses on-site hardware and software purchases and setup. It also eliminates the need for on-site data centers and the expenses that come with it – IT experts to manage the centers, servers and round the clock electricity to power and cool the servers.

Increased Productivity

Unlike a hard drive or local storage device which requires a lot of IT management chores – hardware setup, software patching, racking and stacking – cloud computing is all internet based and as such has no need for this. This gives room for the IT team to focus on achieving other business goals.


With a hard drive or physically accessible infrastructures, the risk of damage is heightened. One faces the risk of the crash, lost files, backup failure and so much more. However, cloud computing solutions ensure business continuity, faster and easier disaster recovery and easier data backup.

Availability of Advanced Infrastructure

AI applications are generally high performance when on servers with multiple and very fast Graphics Processing Units (GPUs). These systems are however extremely expensive and unaffordable for many organizations. AI as a service in cloud application development becomes accessible to these organizations at a more affordable price.