Application of Machine Learning in Artificial Intelligence
Machine Learning
Machine learning (ML) allows a computer system to make predictions or take decisions using historical data without being comprehensively programmed. It utilizes large amount of structured and semi structured data so that a ML model can
generate accurate result, giving predictions based on that data.
ML capable machines to learn from past data without becoming more complex programmable that is a sub field of Artificial Intelligence.
ML works on algorithm which learns by its own using historical data. It works only for specific domains.
Ex; if we create a ML model to find pictures of dogs, it will only give result for dog images. However, if we provide a new data like cat image then it will become unresponsive. ML is being utilized in various situations.
• online recommender system
• Google search algorithms
• Email spam filter
• Facebook Auto friend tagging suggestion.
Types
1. Supervised learning
2. Reinforcement learning
3. Unsupervised learning
The improvement of ML as a part of AI is now becoming very fast and incredible. Its usage has spread to wide areas, such as learning machines, which used in smart manufacturing, medical science, pharmacology, agriculture, archaeology, games and business.
What is AI???
As everyone knows, technology is growing very fast. It is ready to generate a new revolution in the world by making intelligent machines. Artificial Intelligence (AI) has become common word. In fact, one of the incredible technologies of computer science is AI.
AI comprises of two words Artificial and Intelligence, where Artificial means "man-made," and intelligence means "thinking power". Getting both together, AI can be defined as "a man-made thinking power."
AI allows human to make intelligent machines.they can behave and think as human amd capable to make decisions. It can be considered as an aspect of computer science.
It is currently working with a variety of subfields such as,
• Self-driving cars
• Playing chess
• Proving theorems
• Playing music
• Painting
AI is one of the curious and universal fields of Computer science. AI comes when a machine have human based skills such as learning, reasoning and solving problems.With AI it is not required to pre-program a machine to do some work, despite that you can create a machine with programmed algorithms with own intelligence.
That is the awesomeness and the speciality of AI.
Types
Based on capabilities, there are,
• Weak AI
• General AI
• Strong AI
Today we are dealing with weak AI and general AI. The future of AI will Strong AI for which it is will be intelligent than humans.
Why AI?
With the help of AI,
• can be created software or devices which can solve real-world problems easily with accuracy (health issues, marketing, traffic issues)
• can be created your personal virtual Assistant-Cortana, Google Assistant, Siri,
• can be built Robots which can work in an environment where survival of humans can be at risk.
• AI creates a path for other new technologies, new devices and new Opportunities.
Goals of AI
• Replicate human intelligence
• Solve Knowledge-intensive tasks
• An intelligent connection of perception and action
• Building a machine which can perform tasks which need human intelligence.
• Proving a theorem
• Playing chess
• Plan some surgical operation
• Driving a car in traffic
What Comprises to AI?
When it comes to intelligence,it is an intangible part of our brain. It is a collection of reasoning, learning, problem solving perception and language understanding.
To achieve those following disciplines are needed.
Advantages of AI
High Accuracy with fewer errors: tending to less errors and high accuracy.
High reliability: Perform same action in various times with high accuracy.
High-Speed: are very high-speed and fast-decision making.
Digital Assistant: useful to provide digital assistant to the users. (AI is utilized by different E-commerce websites to indicate products as requirements)
Useful for risky areas: AI machines provide an advantage in risky situations like defusing a bomb, discovering the ocean floor.
Useful as a public utility: Ex; self-driving car which make our journey safer and hassle-free, facial recognition for security purpose, natural language processing to communicate with human in human-language.
Disadvantages of AI
High Cost: Requirement of hardware and software, maintenance of AI is very costly.
No feelings and emotions: It cannot make any emotional similar to human. Sometime be harmful for users if the suitable care is not taken.
Can't think out of the frame: Although they are smarter machines, cannot work out of the box. Robots only work according to their programming and training.
Increase dependency on machines: With technology, people getting more dependent on devices, losing mental capabilities.
No original creativity: cannot overcome the power of human intelligence and cannot be creative and imaginative.
The knowledge of followings is important to learning AI.
• Any computer language (C, C++, Java, Python)
• Knowledge of essential Mathematics (derivatives, probability theory)
Relationship between ML & AI
ML is an application of AI. Utilizing experience, it creates the ability to automatically learn and development, without becoming more complex programmed. Machine learning is related to the improvement of computer programs. And also, it allows to access of data and uses it to learn for themselves.
Combining machine learning with AI and advisable technologies make it more effective. AI and ML are the part of computer science which is correlated with each other. These two are the most trending technologies in the world used for creating intelligent systems.
These are two related technologies but different terms in various considerations. AI is a vast concept with the purpose of creating intelligent machines which can simulate human thinking capability and behaviour.ML is an application/subset of AI which allows machines to learn from data without being programmed comprehensively.
• AI system does not require being pre-programmed.
• They utilize algorithms which can perform with their own intelligence.
• It involves ML algorithms such as Reinforcement learning algorithm and deep learning neural networks.
• AI is used in multiple places (Siri, Google’s AlphaGo, and AI in Chess playing).
https://www.javatpoint.com/artificial-intelligence-tutorial
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