Revolution in AI techniques:
In recent years, the Artificial Intelligence revolution has provided the quality response for the different ranges of technologies. I will explain the main reasons for the growth of your income. Voice recognition, face detection, fingerprint recognition, and much more functions quite accurately due to deep learning techniques. The Deep Learning technique is based on Artificial Neural Networks. The achievements in this field can be judged by its various products, such as a novel technique for image recognition, object detection, and stock market prediction system. Advances in image recognition have expanded the limitations of medical treatment. In addition, it is helping to read X-rays and predict diseases through improved services. Also, it is inspired by the natural intelligence of humans, but now the AI revolution has changed everything. It could lead to dismissal as it is outperforming humans in many fields. The chart above shows the upcoming earnings for the next few years. This will lead to a highly profitable profit for the industry.
The following implementations are somehow causing the sudden growth of AI companies:
1) Implementing 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, the risk of any incident can be minimized by detecting the presence of another object. Using the latest technologies, it can be performed in the live working environment. Within a single image there are many objects within it, a good model can easily identify each object by extracting key visual features from an image. The different application areas of object detection are face biometrics, motion detection, 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 tag. How does an image recognition algorithm know 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 images, you have to train an image recognition algorithm on thousands of images of cats and thousands of images of backgrounds that do not contain cats. It goes without saying that this algorithm can only understand objects/classes that it has learned.
2) Changed technology: Today we have changed our communication and data storage technology from analog to digital, which makes the change a convenient approach. Today, robotics has made many advantages in robot design. They are able to take the physical interaction of the human being as useful information. They can react to any physical interaction to perform the output task. This technology has brought about the change in robotics that has become an advantageous component in the era of Artificial Intelligence.
3) Meet consumer expectations: From time to time, customer needs and expectations grow. While industries are there to handle digital data, this data is in vast amounts, and sometimes poor technologies can fail to handle and deliver on this data. Here an AI comes into play. Complex big data can be easily managed and handled with the help of artificial intelligence. After handling a large amount of data, it produces a better customer experience. It has made the expectations of the customers come true, which creates a high demand in the 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 it possible for machines to make decisions for themselves. AI has changed the decision-making landscape for companies. Deep Learning has been widely used for decision making when the data set is huge. As a demonstration, Amazon has partnered with Microsoft to improve projects based on Deep Learning. This reflects how effective deep learning is in making decisions and handling high computational tasks. In the current TensorFlow scenario, Keras has become an integral part from a business point of view. Fast and powerful processing using algorithm-based tasks is applied in business for better customer satisfaction.
With all these benefits and advantages of this technology, it has proven to be a trending way to overcome traditional data handling and analysis problems. Thus, the growth of AI is paving the way. From the study it can be stated that the market value of AI is growing due to advanced technology like prediction system, recommendation system, etc. Until 2021, the revenue will reach approximately $10 billion, which will be a rapid growth for the industry. AI could boost average rates of return by 38% and drive an economic increase of TN$14 by 2035 with its innovative ideas. Google is exploring all aspects of machine learning with classic algorithms. It has overcome different research challenges and technical tasks, which also leads to its increased demand and income.