DEVELOPING INTELLIGENT CLOUD WITH ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
Source – analyticsinsight.net
Digital transformation is bringing the world closer and is highly responsible for driving all activities within an enterprise. It is bringing agility into businesses and reducing the overall cost of some kind of ownership also. If we closely look into this phase of transformation, cloud technologies are the highest adopted technology stream in the digital enterprises. The very reason for this being is, clouds empower teams to provision new application servers and infrastructure whenever required on the go. Furthermore, with the latest cloud platforms coming up, any digital business can now easily make things work for their IT infrastructure in minutes rather than months.
From the past few years, machine learning is taking over the discussions for digital transformation. Efforts are being made to develop machine learning to a certain stage where without any human help or intervention things go smooth. The data science has been building future on these stepping stones: machine learning and artificial intelligence. Next, when coupled with cloud computing, these can do wonders. This amalgamation of machine learning and cloud computing is what we call “The Intelligent Cloud”. Cloud computing is generally seen as cloud providing storage and networking services. But beyond this, all exists capabilities we need to infuse ourselves in. The intelligent cloud carries with it the ability to learn from the huge amount of data, build up predictions and thus end up analyzing situations. This seems to be an excellent platform to perform tasks with greater efficiency and speed.
The next big innovation we can think of building together using cloud computing and machine learning helps organizations enhance the way they look at machine learning. Earlier needing more storage for your developing application was fulfilled by driving to a data center and then inserting physical disks into a rack of machines. But now this has been transformed into developing production machine learning systems. Further taking advantage of cloud computing, this step could be enhanced in competitive directions as well. What the native methods could not help in months, can now be achieved in minutes. This is how machine learning is revolutionizing the IT industry.
If we have a simple look through the concept of cloud computing, we can understand it basically provides two functionalities which are prerequisites for running any artificial intelligence system- scalable and low-cost resources (storage & computing) and processing power. Firstly, it provides scalable and low-cost computing and secondly it provides a great way to store and process large volumes of data. Thus, together these two can combine to present any organization a platform that could work far better than scrolling through manual algorithms. There are infinite areas and various aspects where this combination could prove beneficial.
The two most talked areas today are cognitive computing and personal assistance. With the massive amounts of data stored in the clouds, learning through it has become easy as it comes as a repository for the learning. With millions of people who access stored data in the cloud, there comes a huge list of processes to be done, which further act as a source of information for the machine to learn from. This entire process thus provides applications in the cloud, the ability to carry on functions. The applications thus developed are capable of performing cognitive functions and make decisions. IBM Watson, AWS IA, and certain other Microsoft APIs have been a part of this cognitive computing in some notable cases. But today the cognitive systems in the market are still in the experimental stage. It would further take more time for the technology to be capable of handling major tasks in multi-national giants.
If we look at the personal assistance side, then personal assistants like Apple Siri, Microsoft Cortana or Google Allo are nothing but pre-coded voice recognition systems. Taking up the data from the cloud, enabling cognitive functions to the applications, any chatbot can excel in replacing any human interaction. Implementing machine learning in these chatbots can further polish their capabilities and give them a human touch. The chatbots can learn from the past conversations and assist better.