Artificial Intelligence and its Research Domains
There are five different research domains in Artificial Intelligence. Let’s go through them one by one.
1.Expert system design:
The expert systems are the computer applications developed to solve complex problems in a particular domain, at the level of extra-ordinary human intelligence and expertise. Expert system design comprises AI problem solving methods like uninformed Search, informed search and adversarial Search. It also deals with development of knowledge reasoning capability into an intelligent agent based on prepositional logic and first order logic. As discussed in SkillVille blog on “Expert System”, Pneumoconiosis X-Ray Diagnosis Expert System (PXDES) is an expert system which is used to diagnose Lung diseases. It takes our lunge picture from the upper side of the body which looks like the shadow. The shadow is used to determine the type and degree of lung cancer.
2. Machine Learning
Account record tracking, identifying account closure before occurrence of the same, tracking spending pattern of the customer and with so many other ways machine learning helping banking and finance sector with lots of potential. Machine learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. This program focuses on the development of computer programs that can access data and use it to learn for themselves.
3. Deep Learning
AI system that helps robots to learn from demonstrative actions is been developed by Nvidia researchers. Robots which works as Housekeeper and performs actions based on AI inputs from several sources are common enough. Like human brains process actions based on past experiences and sensory inputs, deep-learning infrastructures help robots execute tasks depending on varying AI opinions. Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks.
4. Natural Language Processing
All of us use Skype for long distance audio-visual communication. Skype translator uses AI for on the fly translation to interpret live speech in real time across number of languages. Without language barriers, people can communicate using the language they are comfortable with, which will in turn speed up a range of businesses processes. Natural Language Processing is a sub-field of Artificial Intelligencewhich is focused on enabling computers to understand and process human languages, to get computers closer to a human-level understanding of language. Computers don’t yet have the same intuitive understanding of natural language that humans do. They can’t really understand what the language is really trying to say. In a nutshell, a computer can’t read between the lines. NLP makes it really happen.
Google and Nest labs an alphabet owned company developed an image which shows “clustered” pattern of about 30,000 patents from 2004 to 2014 that were filled by thousands of companies containing technologies that overlap with Google and Nest. Coding is a fun but creating models through that code is even more challenging and interesting too. Data visualization uses algorithms to create images from data so humans can understand and respond to that data more effectively.
Artificial Intelligence (AI) is estimated to pave way for close to 2.3 million opportunities by the year 2020.These automated roots of robotics have grown with tremendous speed with the five branches and have produced a fruit of artificial Intelligence. The sky is the only limit of growth for this AI tree. So start climbing any of the branches and you will definitely enter into the world of opportunities.