Artificial Intelligence

“Artificial intelligence and machine learning” refer to human intelligence and behaviors in machines and allow machines to learn from the past and work automatically through deep learning and neural network algorithms. ML is widely involved in AI, allowing machines to improve the experience from past work without automatic programming. Machine learning is divided into three segments such as supervised ML algorithm, unsupervised ML, and reinforcement algorithm of ML. ANN (Artificial neural network) is also a part of ML and uses neurons of the human brain and it is believed that machines also can do everything like humans.

Artificial Intelligence

“Artificial intelligence” is a segment of computer science and technologies that involves human intelligence to operate a machine automatically. AI includes an expert system, “natural language processor” (NLP), machine vision, voice and speech recognition ability that make this technology innovative. Artificial Intelligence focuses on three different skills such as the learning process, the reasoning process, and the self-correction process. AI reduces the time consumption to complete a complex task and increases the accuracy of automation technology in different segments. There are three types of AI available in the market such as Narrow AI, General AI, and Super AI. Narrow AI is a weak AI and the accuracy of work is less than Super AI.  

• Learning process is the first skill through which the programming of AI focuses on acquiring data, and rules how to run appropriate data that is called an algorithm. In this stage, AI programming sets instructions to run data and complete complex works with machines through human intelligence
•  Reasoning process plays an important role in finding out the right algorithm for complex work as per the instruction to get desired output
•  Self-correction processes enable AI programming to correct algorithms and increase accuracy of work

Artificial intelligence and machine learning

Machine learning is a segment of AI and algorithms of ML are improved through past experiences automatically. ML-enabled machines used sample data as well as training data to perform work automatically without any programming. Deep learning is an important part of ML that uses human intelligence, processes data to perform work without the minimal intervention of humans. ML is a dynamic network language that does not use any strict instruction and code to perform complex work. ML used four types of algorithms like Regression, classification, and clustering. Supervised learning, unsupervised learning, and the reinforcement process of learning are used by ML.

• The supervised process of ML learning is generated through a data set where all responses are known and the machine works based on the training model. Through this learning, process machines can predict future responses and data with high accuracy
• Unsupervised process of learning is improved through an unknown data set and unknown response as well as data pattern. Through the unsupervised process of learning, machines are required to recognize the data pattern for generating an accurate response
• The reinforcement process of learning in ML helps an agent to learn based on the environment by using trial feedback

Also see: Evolution of Artificial Intelligence

Artificial General Intelligence

“Artificial General Intelligence” (AGI) formulated human cognitive skills to give a solution for specific problems.  AGI systems can think, learn, and gather knowledge to apply their intelligence power for solving problems. Anthropomorphic ability converts AI technology into AGI. The system of AGI has different types of skills such as fine motor capability, “Natural language processing” (NLP), problem-solving ability, skill of navigation as well as emotional intelligence. AGI plays an important role to make decisions based on dynamic situations and give solutions for complex work with a high rate of accuracy. AI can provide different industries with developing opportunities. Through the AGI system, one can create communication with different AI platforms effectively. The demand for AGI systems is increasing gradually in different industries to use thinking ability, learning ability like humans.   

Conclusions

At the end of this article, we get a wide amount of information about Artificial intelligence and machine learning. Algorithms, types of AI as well as machine learning are described in this article. Concept of AGI is also described in this article to know its working procedures and understand the difference between AI and “Artificial General Intelligence”. ML allows machines to perform complex work in different environments through their experience and labeled data. Machine performs complex work without a known data set and labeled data is called the unsupervised learning process of ML. AI and ML both are interconnected and widely used in different industries to increase the accuracy of automation technology. AI-enabled technology can perform work automatically based on human intelligence without menial human intervention.