Overview

Since the inventions of machines and computers, Scientists trying their best to keep evolving the power of computers and machines regarding work, speed, size till the time.

Artificial Intelligence is a branch of computer science which trying to make computers as intelligent as humans.

Artificial Intelligence is a method of making a computer, machine or robot to think intelligently like humans. AI( artificial intelligence) work as similar as human brain. AI is made by the study of how human brain works, how we learn, how we decide, how we adapt and try to solve the problems. The development of AI is made with the intention of making machines as smart and intelligent as Humans are.

AI is combination of computer Science, Biology, Psychology, language, engineering and mathematics these are the things which contribute in the building of Artificial intelligence(AI).

Importance of AI:

source – CBS New York

Computer program without AI can answer only specific type of questions whereas a computer program with AI can answer generic questions as well.

AI techniques

It is a manner to use knowledge in such a way that it provides the people with relevant answers, be easily modified to correct errors, useful for people in many situations.

Uses of AI:-

source – Founder Institute

There is large number of fields in which AI is serving people today. AI is proposed in several fields like:-

1. Gaming: AI can play strategic games such as chess, Tic Tac Toe, etc.
2. Natural Language Processing(NLP): we can interact with machines which understands language spoken by people.
3. Speech Recognition: AI is capable of hearing and understanding language. It can understand different accents.
4. Handwriting recognition: this software reads the text written on paper. It recognizes the shape of the letter by converting it into editable text.
5. Health Cares: AI is being used in health cares for improving patients health at low cost. AI is used to held appointments, aid patients, billing process and provide basic medical feedback.
6. Manufacturing: In this section Robots which have been implanted with AI helped a lot. They can lift heavy things, manufacturing of products, they can make products and they do things just like humans.

Intelligence

source – Becoming Human: Artificial Intelligence Magazine

It is the ability to calculate, analogies, reasoning, learning store information, solve problems, complex ideas, use of language, adapt situations, generalize etc.

Composition of intelligence:-

AI is consist of following aspects:

1. Reasoning: process that helps us to provide base of judgment and decision making.
2. Learning: it is gaining or acquiring knowledge or skill by experiencing something, practicing and studying. Types of learning:-

• Auditory learning: learning something by listening and hearing.
• Episodic learning: learning something by remembering events that have been experienced.
• Motor learning: learning something by movements of muscles.
• Observational learning: learning something by watching others.

3. Problem solving: the process in which we try to come at desired solution of the situation.
4. Perception: it simply means sensing.
5. Linguistic intelligence: It is the ability to speak, write, read, or hear language. This is important to interact with AI or Robots.

Speech and Voice Recognition

source – Future of Life Institute

Speech recognition helps in understanding ‘what’ was spoken.

Voice recognition aims at ‘who’ is speaking. It is used in identifying the person by analyzing its voice. It helps in hand free computing and navigation.

AI system does not need any training for speech recognition because it is independent of human orientation but training is needed in voice recognition because it is person oriented.

Applications of AI technology

source – Coding Dojo

1. Personal assistant: Like Siri, Alexa these are the some common examples with which we are familiar now a days. These AI are present in our mobile phones to keep us updated and help us in our daily life.
2. Automation: system or function that acts automatically. For example, RPA is programed to perform high volume task that the humans normally do.
3. Machine learning: to getting a computer perform task without programming.
4. Machine vision: the technology that analyses visual information using cameras, machine vision can be programmed to see through walls, even to see in night and to do lot more.
5. NLP (natural language Processing): the ability of AI of text translation, speech recognition and voice recognition.
6. Robotics: robots are consist of AI. They used to perform task that humans can’t do. These are often used by NASA for research in space.
7. Self-driving cars: this is the automated skill of piloting a vehicle, obstructions and helps in safe Driving.

Classification of AI

source – Innoplexus

AI is mainly classified in main 3 types according to the type of work performed.

1. Formal Task: It consist of gaming and mathematics.
2. Expert Task: It consist of medical diagnosis, Scientific analysis, engineering and Financial analysis.
3. Mundane Task: It consist of perception, computer vision, speech, logic, fault finding, manufacturing, reasoning, common sense, NLP.

Human have the ability to do mundane task since the time of  birth. They have learnt this by speaking, language, perception. They learn expert and formal tasks later.

For humans ordinary task are easier to learn, the same was think true for the machines since they tried to implant mundane(ordinary) task in them. Later machines require more complex knowledge, complicated algorithms, and knowledge representation for handling these ordinary tasks. That’s why  AI is more prosper  in doing expert task, as expert task need knowledge without common sense, Which is easier to represent and handle.

Turning Test

source – SearchEnterpriseAI – TechTarget

Intelligence of a system is measured with a Turning Test. 2 person and one machine engulged in this test, from which 1 person is the tester and remaining person the machine are the contesters, both sits in different rooms the tester was unaware of which one is a machine and which one is a human. The tester questions and cross questions both. If the machine is successful in fooling tester. The machine is said to be intelligent.

NLP (Natural Language Processing )

source – ClearVoice

NLP is the method of communicating with AI using a language like English. Processing of NLP is required when you want an intelligent system  work as per your command, talk with the AI, interact with your intelligent system, etc.

NLP involves system to perform task with languages human use. Input and Output of the system may be in form of speech or in written from.

 Robotics

It is a part of AI that creates efficient and intelligent Robots.

Their objective:

Robots aims at manipulating objects by picking, moving and by  modifying the physical state of the object or destroying it, doing repetitive functions without getting bored, exhausted or distracted like Humans.

Robotics is a sub part of Artificial Intelligence(AI), which consist of electrical, mechanical engineering and computer Science for designing , construction and functioning of Robots.

Robotics aspects:

• Robots have mechanical construction and have different shape or form to achieve particular goal.
• Consist of electrical parts which gives power and control to the machinery.

• Contain certain number of computer programs which determines WHEN,WHAT and HOW a robot do things.

Difference Between Robot System and other AI programs

Artificial Intelligence Programs	Robots
1. AI operates and works in computer simulated world.	1. Robots operates and works in real physical world.
2. Input is in the form of  symbol  and rules.	2. Input is in the form of speech.
3. They need general purpose computers to operate	3. They need special hardware, sensors to operate.

Robotic locomotion

source – SlidePlayer

It is the mechanism through which a robot is  capable of moving. There are 3 types of locomotion:-

1. Legged Locomotion.

This locomotion consumes more power than the other locomotion. It is perfect for motion in rough as well as smooth terrain. This is perfect where irregularities are present. In this we face little stability issue leg coordination is very necessary for this kind of locomotion in case of more legs.

1. Wheeled Locomotion.

It requires less power than the legged locomotion. In this there is less chance of stability issue in case of more wheels but we are unable to use it on irregular land  because of wheels.

• Slip or Skid Locomotion.

In this type of locomotion robots  use tracks as used in tanks. This is steered with using it on different speeds and in same or opposite directions. It have more stability than both locomotion because of large area of contact between the ground and track.

Computer Vision

Technology of AI which helps robots to see. It plays an vita role in field of safety, security, health, etc. it helps in extracting useful information from a single or number of images. For example, Drones.

Tasks done by computer vision:-

1. Optical Character Reader (OCR)
2. Face Detector
3. Object Recognition
4. Estimating Position

Use of Robotics:

source – Universal Robots

1. Robots are used in cutting, handling materials or elements, welding, coating, etc.

2. Robots can reach inaccessible and Hazardous place in war where human can’t reach. A robot can  be functioned to destroy life threatening objects, bombs, weapons safely.

3. Robots are capable of doing many medical tests simultaneously, help a physically disabled person in recovering, doing difficult surgeries, help to recover from diseases like Brain Tumor or Cancer.

4. Robots can be used to  explore land that is beyond are reach. Used for space exploration, under water drones used for exploring oceans, etc.

5. Walt Disney have been created many number of robots for making a movie.

Artificial Neural Networking (ANN)

source – SlideShare

It is a computing system that is made up of simple and highly interconnected processing element, which process information to give response to the external input.

There  are 2 types of ANN:-

• Feed forward Artificial Neuron Networking:

The information flow is one directional. One unit sends information to another. In this feedforward there is no feedback loop. This is used in recognition and classification. They have fixed number of output and inputs.

• Feedback Artificial Neuron Network:

It consist of feedback loop. It is the response to the input which is taken by feed forward ANN. They are used as content addressable memory.

Issues with Artificial Intelligence

AI is  developing with a very fast pace now-a-days. It all looks like a magic. There is a concern among researchers and developers the AI can grow that much strong that it would be difficult for a  human to  control them. For which humans themselves seems threatened.

• Privacy Threat.

AI can understand language and recognize speeches, so they are capable of understand our conversation, can break through our accounts, do threat to our privacy and can do lot more than this.

• Human Dignity.

AI has already replaced many humans in many industries. AI make many workers jobless in few industries.

• Threat of Safety.

AI can self-improve itself it can be so much powerful that it’s become very difficult for humans to stop it from  achieving it’s goals. Which may lead to the end of human race.

• Hacking Threat.

The most important concern regarding AI was that it can hack into our systems can gain access to sensitive systems, can hack system of national security, can get to our every secret, may start world war 3 between humans and AI. This questions our security that are we ready for this.

This Article is given to us by our lead blogger Balvinder Singh

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