Revolution in AI techniques:
In recent years, the revolution of artificial intelligence has reached the quality of various technologies. I will explain the main reasons for sales growth. Speech recognition, facial recognition, fingerprint recognition and other features work well enough thanks to in-depth learning techniques. The deep learning technique is based on artificial neural networks. Performance in this area can be assessed through its various products such as a new image recognition, object recognition and inventory forecasting technology. Advances in image recognition have broadened the boundaries of medical care. It also helps to read X-rays and predict diseases through improved services. It is also inspired by man’s natural intelligence, but now the AI revolution has changed everything. This could lead to a dismissal because in many areas it exceeds people. The chart above shows the future revenue for the next few years. This will lead to a very profitable gain for the industry.
The following implementations cause the sudden growth of IA companies:
1) Implementation of automatic learning: the recognition of objects involves the analysis of the content of photos as individual objects, faces, logos and text using a cognitive model assisted by the computer. Using object detection, the risk of an accident can be minimized by detecting the presence of another object. This can be done in the live work environment using the latest technologies. There are many objects in a single image. A good model can easily identify each object by extracting important visual characteristics from an image. The purpose of object recognition is facial biometry, motion detection, object recognition and text recognition.
Each image recognition algorithm would take an image or its input patch, an output would be the object in the image. In other words, the output will be a class name. How does an image recognition algorithm recognize the content of an image? Well, you have to train the algorithm to learn the differences between the different classes. If you want to find cats in the photos, you have to create an image recognition algorithm with thousands of images of cats and thousands of background photos that do not contain cats. Needless to say, this algorithm can only understand the objects / classes it has learned.
2) Technology has changed: today we have changed our technology from the communication and storage of analogue to digital data, making conversion a practical approach. Robotics today has many advantages in robot design. They are able to take the physical interaction of humans as useful information. You can respond to any physical interaction to complete the exit operation. This technology has made the change in robotics, which has become a beneficial element in the era of artificial intelligence.
3) Respond to consumer expectations: from time to time, the needs and expectations of customers increase. While there are industries that process digital data, these data are plentiful and sometimes bad technologies can not cope and achieve the goals of this data. This is where an AI comes into play. Highly complex Big Data can be easily managed and managed using artificial intelligence. After handling huge amounts of data, you get a better customer experience. It put customer expectations first, which led to strong demand in the industries. Facebook, Pinterest, Netflix and Google are some real-time and effective examples to demonstrate the above.
4) Decision making: the use of machine learning algorithms has increased machine performance. These algorithms allowed the machines to make their own decisions. AI has changed the scenario of corporate decision-making. In-depth learning was often used to make decisions when the data set was very large. As a demonstration, Amazon has worked with Microsoft to promote projects based on in-depth learning. This reflects the effectiveness of in-depth learning in decision making and in the development of high-level IT tasks.
With all these benefits and benefits of this technology, it has proven to be a way to overcome traditional data management and analysis problems. So, the growth of AI makes its way. From the study, we can say that the market value of AI is increasing due to advanced technologies such as the forecasting system, the recommendation system, and so on. By 2021, revenue will reach about $ 10,000 million, which will represent rapid growth for the industry. AI could increase average returns by 38% and, thanks to their innovative ideas, lead to an economic increase of $ 14 by 2035. Google explores all aspects of machine learning with classic algorithms. He overcame several research challenges and technical activities that resulted in increased demand and revenue.
Due to applications such as the referral system and the demand for predictive systems, AI is increasing day by day. Companies continue to use these services to improve their profits. Research in this area is still ongoing to maximize benefits.