Machine learning-Is artificial intelligence restricted to processing information or can it also allow machines to acquire knowledge?

 

Artificial intelligence allows machines to acquire knowledge and there are machines existing which processes and acquires knowledge. Machine learning is one modern innovation that has made industrial and expert procedures easy and efficient. It has also made everyday life simpler. First let’s see what is machine learning. As the name suggests Machine learning is an application of artificial intelligence that provides machines the ability to mechanically acquire and progress from experience without being directly programmed. Machine learning emphases on the growth of system programs that can obtain data and utilize it to learn for themselves. The main target for this invention is to allow the machines to learn automatically without human interference. Currently, this application is being used in various fields. For instance, medical diagnosis, classification, image processing, prediction, regression and etc. Image processing is one of the most common uses of machine learning. It can recognize an object as a digital image, built on the intensity of the pixels in black and white or color images. Labeling an X-ray as cancerous or not and assigning a name to a photographed face are works of Image processing.  Machine learning can be used for face detection in an image as well. There is a discrete category for a specific person in a catalogue of several people. Machine learning is also used for character recognition to distinguish handwritten and printed letters.  We can divide a work of writing into minute images, each containing a solitary character. Similarly, speech recognition is another application which makes use of machine learning algorithm. Speech recognition is the translation of oral words into text. Here, a software application can identify the words articulated in an audio clip, and then consequently convert the audio into a text file. Machine learning can be used in the methods and tools that can help with medical diagnosis. Many doctors use chatbots with speech recognition capabilities to discern patterns in symptoms. Here, Machine learning can sense patterns of certain diseases within patient electronic healthcare annals and inform doctors of any irregularities. Machine learning is also used in Statistical arbitrage. In finance, arbitrage refers to the automated trading strategies that are of a short-term and involve a large number of securities. The strategy uses a trading algorithm to scrutinize a set of securities using economic variables and correlations. Machine learning enhances the arbitrage strategy to improve results. Predictive analytics is one of the many propitious examples of machine learning. Machine learning can categorize accessible data into groups, which are then demarcated by rules set by analysts. When the sorting is over, the analysts can calculate the likelihood of a fault. Machine learning can also extract structured information from unstructured data. Establishments accumulate enormous capacities of data from clients. A machine learning algorithm mechanizes the process of interpreting datasets for predictive analytics tools. Machine learning can also provide financial services such as making smart decisions, spots an account closure before it occurs, Tracks the spending pattern of the customers, performs market analysis and etc. Atlas we can say that machine learning is a groundbreaking creation in the turf of artificial intelligence. Finally, it is proved that artificial intelligence allows machines to acquire knowledge.

 Sources:

https://www.salesforce.com/eu/blog/2020/06/real-world-examples-of-machine-learning.html

 https://bigdata-madesimple.com/top-10-real-life-examples-of-machine-learning/