What Are the Reasons Behind the Growth in AI Revenue?

By Gunjan Dogra

Revolution in AI Techniques:

Over the past many years, Artificial Intelligence revolution has provided the quality response for the different range of technologies. I am going to explain main reasons for the growth in its revenue. Functions of speech recognition, face detection, fingerprint recognition and much more are operating quite accurate because of Deep learning techniques. Deep Learning technique is based on the Artificial Neural Networks. Achievement in this field can be judged by its different products like a novel technique for Image Recognition, Object Detection and Prediction System for the stock market. Advances in image recognition have extended the limitations of medical treatment. Moreover, it is helping in reading X-rays, and predicting disease through improved services. Also, it is inspired by the natural intelligence of humans but now AI revolution has changed everything. It could lead to layoff, as it is overtaking human in many fields. The above graph shows the upcoming revenue for the next coming years. This will lead to highly profitable gain for the industry.

The following implementations are somehow causing the sudden growth in AI companies:

1) Implementation of Machine Learning: Object detection means analyzing the content of photos such as individual objects, faces, logos and text on them using a computer-aided cognition model. With the help of object detection, one can minimize the risk of any incident by detecting the presence of another object. Using latest technologies it can be performed in the live work environment. Within a single image, there are a lot of objects inside it, a good model can easily identify each object by extracting key visual features from an image. Different application area of object detection is Facial Biometrics, Motion Detector, Object Recognition and Text Recognition.

Any image recognition algorithm would take an image or its patch as input, an output will be the object in the image. In other words, the output will be a class label. How does an image recognition algorithm know the contents of an image? Well, you have to train the algorithm to learn the differences between different classes. If you want to find cats in images, you need to train an image recognition algorithm with thousands of images of cats and thousands of images of backgrounds that do not contain cats. Needless to say, this algorithm can only understand objects/classes it has learned.

2) Changed Technology: Today we have shifted our technology from analog to digital data communication and storage, which makes the change a convinient approach. Nowadays, robotics has made many advantages in the robots designing. They are able to take physical interaction of human being as a useful information. They can react to any physical interaction to perform the output task. This technology has made the change in robotics which has become an advantageous component in the era of Artificial Intelligence.

3) Meet Consumer's Expectations: From time to time, customer's need and expectation grow. Though industries are there to deal with digital data, this data is in huge amount and sometimes poor technologies may fail to handle and accomplish the goals with this data. Here comes an AI into play. High complex big data can be easily managed and handled with the aid of Artificial Intelligence. After dealing with huge data it produces better customer experience. It has brought customer's expectations into reality which leads to great demand in industries. Facebook, Pinterest, Netflix and Google are some of the real time and effective examples to demonstrate the above fact.

4) Decision Making: By applying machine learning algorithms the power of machines has increased. These algorithms made machines able to make decisions by itself. AI has changed the scenario of decision making for business. Deep Learning has been widely used for decision making when the dataset is huge. As a demonstration Amazon has done the partnership with Microsoft to uplift projects based on Deep Learning. This reflects how effective Deep Learning is in Decision Making and handling high computation task. In today's scenario TensorFlow, Keras has become an integral part from the business point of view. Fast and powerful processing using algorithm based tasks are applied in business for better customer satisfaction.

With all these benefits and advantages of this technology, it has proved itself a trending way for overcoming traditional issues of data handling and analytics. Thus, the growth of AI is making a path. From the study, it can be stated that market value of AI is growing due to advanced technology like Prediction System, Recommendation System etc. Up to 2021, the revenue will reach approximately $10000 Million which will be a rapid growth for the industry. AI could boost average profitability rates by 38% and lead to an economic increase of US $14 TN by 2035 with its innovative ideas. Google is exploring all aspects of machine learning with classical algorithms. It has overcome different challenges of research and technical tasks which leads to its greater demand and revenue as well.

Due to applications like Recommendation System and   Prediction System demand for AI is increasing day by day. Enterprises are moving further for such services to improve their profit. Research work is still continued in this area to get the peak of benefits from it.