By :- Vishesh Berera, BCA 4^th  Sem, 2^nd Shift

What is robotics?

Robotics is the branch of electrical, mechanical, and PC building that arrangements with the development, operation, designing and application of robots, as well as use of artificial intelligence for their sensory feedback, control and information processing.

They are many steps ahead for advancement in robotics. Once customized robots can perform required assignments more than once in the very same way. Robots have replaced or are going to replace humans in performing dangerous and repetitive tasks which humans do not prefer, or are unable to do because of limitations of size, or which take place in extreme environments such as outer space or the bottom of the sea. Now a day’s robots are greatly used in medical profession also for performing surgeries and various Nano bots are used to go inside human body where normal surgeons can’t operate.

Robots are rapidly transforming the way we live and work and will have even more revolutionary impact in the years ahead.

The further developed adaptations of robots seen now-a-days can perform activities adaptively, that is, changing the measurements and different settings as indicated by the necessities. Robots are showing up in all kinds of different backgrounds, from building items in production lines, to cutting your grass.

According to the director of engineering at Google, Ray Kurzweil, robots will reach a human level of intelligence by the year 2030

Strong AI bots are creative and can generate new ideas on their own while weak Ai robots are pre-programed and work accordingly as programmed.

There are many benefits of a robot than a human. A robot is made out of materials which are for the most part more tough than people are, and they can be intended to be more grounded and quicker than people as well.

Robots help the producer to deliver High-quality items which can prompt higher deals and consumer loyalty which implies the organization that uses automation will probably remain alive and essential, which is useful for the economy. In addition enhancing quality, robots enhance profitability also, another key component to financial wellbeing.

There are disadvantages of robotics too! Rapid use of Quick utilization of Advanced robotized innovation would be awful news for medium-talented professionals, particularly those in segments where routine work is included. This  will also raise fears of greater inequality as the benefits of productivity gains are skewed toward the owners of capital, at the expense of workers. Such an outcome would be bad news for workers spending their efforts and that might delay the shift toward a consumer-driven economy

Scope of Robotics

A course in robotics trains and educates a student in the field of artificial intelligence, computer-aided manufacturing, computer integrated manufacturing system, computational geometry, robot movement arranging, computerized hardware and miniaturized scale handling. Computerized innovation like robots are a basic part in many modern manufacturing industries. As the businesses builds, scope for robotics likewise increases. Robots are for the most part utilized for conveying materials including substantial parts to and from badly arranged areas and dealing with risky materials like atomic waste.

Career Opportunities

One can expect occupations at assembling enterprises, private businesses, cars, apparatus, NASA and modern devices. Students who study robotics technologies at a college or technical school can have careers in robot technology, computer controlled machine programming, etc.

                                                Future Job roles: -

·        Robotic Scientist

·        Robotic Engineer

·        Robotic Technician

By-Meghali Arora, BCA 4^th Sem,2^nd Shift 

CPS are the systems that connects the physical world (e.g., through sensors) with the virtual world of data handling. They are made out of different constituent parts that are combined together to make some global behaviour. These constituents include programming systems, communication systems and sensors that link with the real world. Many times it includes embedded systems.A CPS gives an accumulation of difficulties that are not generally found in a traditional business data system or embedded system. To develop a CPS, a mix of various different engineering capabilities is required, crossing the specialized domains and in addition the comparing application segments, in the form of systems designing.
A typical CPS may:

•           Monitor and control physical or organisational or business forms.
•          Be an extensive scale system with various - and notwithstanding clashes - objectives spreading over various application  domains require integration of different technical disciplines and different application domains.
•             Require coordination of various specialized orders and diverse application areas.
•          Require a high level of dependability.
•          Involve considerable client inclusion/collaboration.
•            Continuously screen and upgrade its own particular execution.
•            Adapt and develop continually accordingly changes in the environment, through ongoing (re)configuration,                      arrangement or (de)commissioning.

•         Require progressive choice systems with a high level of self-governance on neighbourhood, provincial, national, and   worldwide level.
•          Be a disseminated and interconnected system of systems.

          

         

CPS’s can be sent in a wide range of settings and application regions. Here are a few examples : -

• Improving effectiveness and wellbeing in homes and workplaces, for instance by checking and controlling warmth and humidity.
• Supporting elderly individuals living alone, for instance by distinguishing issues, (for example, sickness or accidents) and raising the alarm automatically, utilizing non- wearable sensors or indicators installed in the house.
• Monitoring safety and movements of travelers in an open transport system, or of vehicles on a road network.
• Optimizing crop yield and lessening pesticide/compost use, by utilizing CPS’s to distinguish and convey them just where they are required.
• Implementing smart, effective creation systems and manufacturing lines.
• Monitoring health and prosperity of domesticated animals and raising programmed notices of sicknesses or wounds.
• Monitoring and tracking shipments cleverly for ideal coordination’s and stock control.
• Collecting ecological information to help basic leadership and open approach setting, or to create notices of natural dangers, for example, rapidly spreading fires, quakes or volcanic eruptions.

        

 CPS engineering overlaps with a few other related fields.

       

I.   CPS and embedded systems/system
            An embedded system is a self-contained system that incorporates components of control logic and real world interaction. Dissimilar to a CPS, be that as it may, an embedded system is confined to a single device. While CPS’s may include numerous constituent systems and devices. Embedded systems typically have a limited number of tasks to finish, with software and hardware components composed particularly to accomplish those undertakings, normally with very limited resources.

Conversely, although embedded systems are essential components for some CPS’s, a CPS itself works on a considerably bigger scale, potentially including many embedded systems or different devices and system also, including human and socio-technical systems.


 II..  CPS and the Internet of Things

CPS and the Internet of Things (IoT) have significant overlaps. The IoT is a dream without bounds where a large number of devices are associated over the Internet, enabling them to gather data about real world remotely, and share it with different systems and devices.

IoT and CPS share numerous challenges, however there are some distinctions. IoT has a strong emphasis on uniquely identifiable and Internet associated devices and embedded systems. CPS designing has a strong emphasis on the relationship between computation and the physical world (e.g., between complex programming and hardware parts of a system).

III.  CPS and Systems of Systems

A system of systems (SoS) is a system composed of constituents, which are also independent systems in their own right. The constituent systems are managerially and operationally independent, physically distributed, constantly evolving, and collaborating together to produce emergent global behaviour that they cannot produce alone.

Numerous CPSs are comprised of free constituents, and, as for SoS’s, CPS’s additionally handle difficulties of  coping with dependable rise, advancement and distribution. In any case, despite the fact that it is regularly the case that CPS constituent systems are independent, it's not a characterizing trademark for a CPS. In like manner, despite the fact that it's regularly the case that SoS’s do incorporate components of computation as well as real-world interaction, this isn't a characterizing property of a SoS.

  

By-Alen Gupta, BCA- 4^th sem , 1^st Shift

INTRODUCTION: THERE has been a number of milestones in the development of computer technology and information technology. Mainframe computers appeared in 1960s-1970s. In 1980s-1990s, Internet and desktop computers able to deal with personal and commercial business were created. Around 2000 appeared pervasive computation to conduct calculation at any time or place. All these events have fundamentally influenced the development of information society. At present, many experts from various fields are paying close attention to the emergence of a new engineering system, cyber-physical systems (CPS). CPS are multidisciplinary systems to conduct feedback control on widely distributed embedded computing systems by the combination of computation, communication and control technologies. They are transformation and integration of the existing network systems and traditional embedded systems. Through integration, CPS is able to realize the real-time, safe, reliable and dynamic collaboration with physical systems represented by the embedded system. Physical system data acquisition modules collect data by distributed field devices in CPS system and guarantee the real-time capability and accuracy of the collected data. They pass data to the information processing layer according to the demands of services and complete given tasks by information processing technologies such as data uncertainty management, statistical signal processing, data security processing and feedback control. CPS has a wide range of applications, such as digital medical instruments and systems adopting automatic acquisition and control technology, distributed energy systems, aerospace and aircraft control, industrial control and so on. CPS can also bring huge economic benefits and will eventually bring fundamental change to the function of existing engineering physical systems.

Characteristics: CPS interact with the physical system through networks, the end system of CPS is normally traditional centralized tightly coupled embedded computing system, which contains a large number of physical systems composed of intelligent wireless sensors net. Therefore, CPS maintains following characteristics:

1.     Physical System is the Most Important Field of CPS.
2.     Information System is the Core of CPS
3.     CPS is the Product of Integration of Heterogeneous Systems.
4.     CPS has Requirements of Security, Real-time Capability, and Predictability.

TECHNICAL RESEARCHES: Scientific CPS composition must be a new system architecture pattern which is composed of hierarchical systems including components and subsystems, service quality theory, agreements and modelling language and tools that can analyze, integrate and simulate different components. Computation theory should be able to handle feedback control of real-time systems based on event-driven which suit the asynchronous dynamic event processing of different time scale. The world CPS researchers are just in their beginning. Since CPS is the integration of multidisciplinary heterogeneous systems, without a unified global model, CPS researches are carried out by experts in various areas from the perspective of applications in their own field. At present, CPS researchers mainly focus on studies of system architecture, information processing and software design.

 CONCLUSION: CPS will cover various aspect of social and economic life, bring wide influence and lead the comprehensive development of computer science as well as other subjects. However, limited by the existing theory and technology of computation, communications and control technology, the development of CPS is also facing big challenges. Breakthrough in CPS key technology will enable our country take the world’s leading position in CPS development so that we can independently set our own standard and to push the national social and economic development.

By- Taniya Sharma, BCA 1^st year, 1^st shift

Artificial intelligence also known as machine intelligence is an ability of a machine to think on its own or to achieve the desired goal at its own. Since 1956, from origin of AI, it has developed so far that AI has become an integral part to our lives. AI is also defined as ‘research agents’ i.e. any device that perceives its environment and take actions that maximise its chance of fully achieving the goal given. Colloquially, the term ‘artificial intelligence’ is applied when a machine can perform those functions which a human mind can perform with other human.

Existence of AI born at a workshop at Dartmouth college, in 1956. Allen Newell, Herbert Simon, John McCarthy, Marvin Minsky and Arthur Samuel produced a program for a machine that can solve algebraic problems, proving logical theorems and which can speak English. In early 1980s, an expert system was produced for AI, which was capable of having analytical skills of a human being. With passing years AI was able to perform large functions like data mining, statistical data performance and many other complications which results, in 2010, the great demand of artificial intelligence. Artificial intelligence is based upon the following figures (i.e. the functions to be performed by AI) reasoning, knowledge, planning, learning, natural language processing, perception and the ability to move and manipulate object. Reasoning can be resembled as the way a human being solves a puzzle by applying step by step logics, AI must be capable of doing a procedure. Knowledge representation is the central pillar of AI, a machine is expected to solve problems in which AI need to represent to know: object, properties, categories and relation between object, situation, event, stage and time, cause, effect and many other. AI must be able to set and achieve goals which includes planning, learning is a fundamental concept of AI, which in terms of computer is defined as study of computer algorithms that improve automatically through experience. Natural language processing gives AI the ability to understand the human language. Perception is to take inputs through sensors.

Tools on which AI works are as follows: search and optimisation, logic, probabilistic method for uncertain reasoning, classifier and statistical learning methods, artificial neural language. Among them the most important is artificial neural language. As like a human brain carries information in neurons and save them, AI also have its own neuron system in which it stores information manipulate it and saves it. Earlier AI was inspired by Lisp and Prolog language but in recent AI uses python or C++ or niche languages such as Wolframe language.

The burgeon Artificial intelligence is a nitty-gritty for today’s scenario. Everything have its pros and cons hence; the AI contains its advantages and disadvantages with it. With accelerating growth of AI, it is used in many fields as medical treatment in many medical hospitals with almost no mistake, AI is also used in automobile, many companies like Tesla, google, apple etc. are making driverless cars using AI, finance and economics (basically for investigation), in video games AI is purposefully to used to generate dynamic behaviour of non-player characters and many more.

Once Stephen hawking said “the development of full artificial intelligence could spell the end of human race. Once human develop artificial intelligence, it will take off on its own and redesign itself at an ever-risking rate. Humans, who are limited by slow biological evolution, couldn’t compete and would be superseded.”. this statement in itself defines the black part of artificial intelligence.AI in future may lead to be the reason of devaluation of humanity, decreasing in demand of human labour, artificial moral agent is also a serious issue, this describes the ethics of a machine with humans and other AI agents, many philosophies said that AI can neither designed nor guaranteed to be benevolent, it is a question to be asked that what will happen if AI will be able to get human consciousness? Of course, it will lead to destruction. Having said that I would like to say that gaining excellence par excellence and making technology an ease and essence of life is good but excess of everything is catastrophic.

 By: Shaahil Abraham, BCA- 6th sem, 1st Shift

We call ourselves Homo sapiens—man the wise—because our intelligence is so important to us. We have always tried to understand how we think. How is it possible that a handful of matter can be perceived understood predicted and manipulated in a world far larger and complicated than itself  Today the main reason of boom in innovation is because of artificial intelligence which is working as a base.

WHAT IS INTELLIGENCE?

According to Jack Copeland some of the main factors of intelligence are: -
1.Generalisation Learning
Learning that enables the learner to perform better in the situation not previously encountered.
With Artificial intelligence more advanced Generalisation is common concept for example: one can’t make a computer understand what a dog looks like but one can make it learn but adding up characteristics thus any picture of dog can be understood by machine.

2.Reasoning
To reason is to draw conclusion appropriate to situation in hand.
Humans have an ability to question, to think logically and to be better in artificial intelligence as today’s scenario have shown that. IBM’s Watson is an example like humans it reads lots of information, recognises patterns and after reading it says it is ‘X’ % sure that this is the right answer.

3.Problem Solving
It is an ability to solve problems effectively and efficiently. For Example: Given such and such data, find “x”.
Problem: On holiday in Romania; currently in Arad. Flight leaves tomorrow from Bucharest. Find a short route to drive to Bucharest.
Formulate problem:
States: various cities
Actions: drive between cities
Solution: sequence of cities, e.g., Arad, Sibiu, Bucharest etc.

4.Perception
The definition of AI is based on the nature of the problems it tackles.
Perception involves interpreting sights, sounds, smells and touch. Action includes the ability to navigate through the world and manipulate objects.
 For example: Self-driving cars.

5.Language Understanding
It is a process of understanding language by following syntax and rules like a human being. The field of language understanding involves making computers to perform useful tasks with the natural languages humans use. The input and output can be: -
• Speech
• Written Text

WHAT IS ARTIFICIAL INTELLIGENCE?

AI (Artificial Intelligence) is a machine with the ability to solve problems that are usually done by us with our own natural intelligence. A computer would demonstrate a form of intelligence when it learns how to improve itself at solving these problems.
There are seven aspects of AI earlier at 1955, today there are many more.
The seven aspects are:

1.Simulating higher functions of human brain.
Brain simulation is a process of creation of computer-run model of brain neuron connections.

2.Programming a computer to use general language.
Process of programming a computer to adapt to any situations.

3.Arranging hypothetical neurons in a manner so that they can form concepts.
Setting up of (hypothetical) neurons to form concepts. So far partial results have been obtained but the problem needs more theoretical work.

4.A way to determine and measure problem complexity.
If we are given a well-defined problem (one for which it is possible to test mechanically, if a proposed answer is a valid answer), one way of solving it is to try all possible answers in order. This method is inefficient, and to exclude it one must some criterion for efficiency of calculation so far only some partial results on this problem have been obtained.

5.Self-improvement
An intelligent machine is that which will carry out activities which will enhance it, that is known as self-improvement
Self-improvement helps in analysing the errors and make sure that errors don’t repeat again.

6.Abstraction: It is the quality of dealing with ideas rather than events.
In artificial intelligence, abstraction is commonly used to account for the use of various levels of details in each representation language or the ability to change from one level to another while preserving useful properties. Abstraction has been mainly studied in problem solving, theorem proving, knowledge representation (for spatial and temporal reasoning) and machine learning.

HISTORY OF ARTIFICIAL INTELLIGENCE

In year 1941: Development of the electronic computer. Some trace the origin to John Atanasoff and Clifford Berry at Iowa State University

It required large, separate air-conditioned rooms and required separate configuration of thousands of wires. Data are fed into system by punched cards.

Dartmouth Conference (1955)
 John McCarthy (“father of AI”) organizes conference. A month of brainstorming in VT Talent and expertise of others interested in machine intelligence. Biggest gain: field now called “Artificial Intelligence”.


List Processing language (LISP) (1958):
  LISP language Developed McCarthy announces new development:
LISP language still used today is a choice among AI developers.


Start of DoD’s Advanced Research Projects (1958)
 MIT receives 2.2-million-dollar grant from US govt. to research Machine-Aided Cognition (AI) from Department of Défense.  US wants to stay ahead of Soviet Union


PROLOG Language (1989)
PROLOG Language revealed General logic programming language represented as facts and rules developed in France remains one of the most popular programming languages today.

AI-based hardware sells $425 million to company’s expert systems demand DuPont, General Motors, Boeing rely heavily on expert systems. Companies creates software that aids in producing expert systems.

ADVANTAGES AND DISADVANTAGES OF ARTIFICIAL INTELLIGENCE

Advantages

1. Minimum/no Errors:
Artificial intelligence helps us in reducing the error as it involves self-improvement mechanism which would help in minimising the errors as low as possible

2. Enhance Difficult Exploration:
Artificial intelligence and the science of robotics can be used in mining since mining companies always tries to focus on small improvement which separate a profitable operation from an unprofitable one.

3. Daily Application use:
Daily application involves activities that prove assistance to humans such as enabling low power mode or to enable don’t disturb mode when user get frequent calls  Examples are Siri and Cortana
Disadvantages

1. High Cost:
Creation of artificial intelligence requires huge costs as they are very complex machines. Their repair and maintenance require huge costs. They have software programs which need frequent upgradation to cater to the needs of the changing environment
2. No vision

These days Artificial intelligence is script based thus it can’t perform as par as humans they will see, hear and work but can’t feel or think although experience are improving these days as AI is combined with machine learning ,Thus error rate are less
EXAMPLES OF ARTIFICIAL INTELLIGENCE ARE:

Machine learning

Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that machines should be able to learn and adapt through experience.
Another example includes: -
 Computer vision, Natural language processing
Robotics, pattern Recognition, Knowledge Management etc.

TYPES OF ARTIFICIAL INTELLIGENCE

In terms of approach there are two types of Artificial Intelligence:

1.Weak AI
The principle behind Weak AI is simply the fact that machines can be made to act as if they are intelligent. For example: when a human player plays chess against a computer, the human player may feel as if the computer is making impressive moves. But the chess application is not thinking and planning at all. All the moves it makes are
previously fed in to the computer by a human and that is how it is ensured that the software will make the right moves at the right times.
2.Strong AI
The principle behind Strong AI is that the machines could be made to think if that is the case then it would think like human in every perspective
Since Strong AI is infant in recent years it has a promising future due to the recent developments in nanotechnology. Nanobots, which can help us fight diseases and make us more intelligent.

CONCLUSION:
 

In its short existence, AI has shown an immense amount of growth and potential. −AI has so many applications and can benefit the world in so many ways. It’s like a gift to mankind. But we cannot be blinded by its positives because nothing is entirely beautiful. Even AI has a grim side! Renowned scientist Stephen Hawking thinks “…success in creating AI could be the biggest event in human history, but could also be the last.
But at the same time AI is the main reason that we have an innovation in technology that at one time was just an imagination.

By – Nikita Gupta, BCA 2^nd Sem,  2^nd Shift

                                                          

After Internet, artificial intelligence is the next big thing. Artificial intelligence is the advanced level of technology. Self driving cars, virtual personal assistants like Siri, and intelligent tutorial systems; AI has made it all possible.  In the upcoming years, it will revolutionize the whole world.

Artificial means man made and intelligence means intellect hence artificial intelligence means man made intellect. Artificial intelligence is the technology of making an “intelligent” machine, a machine that can think, analyze and make decisions just like humans. It is about mimicking human brain in a machine and to achieve that it needs learning capabilities and that is where machine learning comes into picture. Machine learning is focused on writing software that can learn from past experience. Deep learning is the subset of machine learning. Deep learning is capable of handling high dimensional data which the former was not.  Deep learning works similar to the human brain. Like human brain works on neurons, deep learning works on artificial neurons called perceptrons.

AI is making our lives easier. With AI, we can have robots that can work for us .AI based robots have better accuracy and speed. They can perform tasks better than humans.  Self driving cars are boon for old and disabled people. They solve the accident problem also.

                                    

        

But the question is, is artificial intelligence a threat to humans? Sophia, the first humanoid robot, has said that it wants to destroy humans. Elon musk recently tweeted that artificial intelligence is more dangerous than North Korea.  Mass unemployment with the introduction of highly capable robots has become a serious concern. Soon, automation will destroy human centered jobs.  Will AI lead mankind to brighter future or disaster?

                                                                                                   

By- Mayank Sharma, BCA- 2^nd sem,  2^nd shift

Artificial intelligence is an intelligence which is used to bring intelligence in a computer program. This technology behaves and adapts the human behaviour. This technology is increasing day by day. Nowadays it is inbuilt in robots, computer systems even in mobile phones which detects the human mentality and shows the results as according to that.

For Example- Google uses artificial intelligence to detect our recent searches and shows the results on frequently asked searches or related to that search when you search the same thing again.

In today’s world this technology has increased that many companies start working on artificial intelligence. The scope of this technology is very much increased and in near future all devices uses artificial intelligence.

Today some devices like amazon echo, google home, etc. uses artificial intelligence. Just you want to say hey google (for google home) or hey alexa (for amazon echo) to access the device and it can also performs many tasks like booking a cab, book an order on Zomato, play your favourite music etc.

Today applications like google maps, uber, ola, etc uses artificial intelligence. The social media like facebook, pintrest, Instagram, Snapchat uses artificial intelligence which intelligently recognise face positions to put different types of themes on our face so that it looks more creative and attractive.

In the end I want to say that this technology have a futuristic wider scope and help to fix many problems not only in commercial use as well as in educational, medical sectors as well as in home as a technology which can easy do tasks through voice control.

                                                                     

                                                                 

By - Kshitij Chawla, BCA 2^nd sem, 2^nd Shift.      

"I propose a question, Can Machines Think". - Alan Turing

Well today inspired by his question I’m gonna talk about Artificial Intelligence.

Artificial Intelligence has been growing faster than we think. It has already made its place in our daily life.

For Example – Every time we Google something some kind of artificial intelligence is being used to give us the best result, Every time you asked Siri question natural language processing and speech recognition is being used, Google Translate is becoming more and more faster than ever before by gaining past knowledge stored in the databases, Automated cars etc.

What is Artificial Intelligence??

"Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to stimulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solves kind of problems now reserved for humans and improve themselves."

In other words Artificial Intelligence is a machine with the ability to solve problems that are usually done by us humans with our natural intelligence.

Changing our Lives

It will change our lives entirely. It will change the way we thinks of now, the way we look at things and change the way we do our work. It has the potential to bring revolution in our lives and forever changing our humanity.

The original 7 Aspects of A.I. (1955)

1) Simulating higher functions of the human brain.

2) Programming a computer to use a general language.

3) Arranging hypothetical neurons in a manner so that they can form concepts.

4) A way to determine and measure problems complexity.

5) Self-improvement.

6) Abstraction: Defined as the quality of dealing with ideas rather than events.

7) Randomness and creativity.

The most important factors of intelligence are generalization learning that is learning that enable the learner to be able to perform better in situations not previously encountered.

Few examples of Artificial Intelligence-

Machine learning, Computer Vision, Natural language processing, Robotics, Pattern recognition etc.

Different types of Artificial Intelligence in terms of approach For example strong Artificial Intelligence and weak Artificial Intelligence. Strong Artificial Intelligence is simulating human brains by building systems that think and in the process give us an insight into how the brain works, we're nowhere the stage yet.

Well AI is a system that behaves like a human but doesn't give us an insight how the brain works.

IBM's deep blue a chess playing Artificial Intelligence was an example, it processed millions of move before it made any actual moves on the chessboard.

There's actually a new kind of middle Artificial Intelligence between strong and weak Artificial Intelligence, this is where a system is inspired by human reasoning but doesn't have to stick to it.

IBM's Watson is an example- like humans it reads a lot of information recognizes pattern and builds up evidence to say "Hey I’m X percent confident that this is the right solution to the question.

What is Machine learning??

Machine learning refers to algorithms that enable software to improve its performance over time as more data is entered this is programming by input-output examples rather than just coding so that this makes more sense. Let me give you an example - A programmer would have no idea how to make a computer that differentiates between a dog and a cat, but he can create a program with a form of intelligence that can learn to do so if the programmer gives the program enough image data and information about them and lets it process and learn, Then after when you give the program an image of a of a dog or cat that program has never seen before, it would be able to tell if it's a dog or cat by observing the whiskers of a cat or you can say nose of a dog or anything else that differentiates a dog from a cat.

How do Machines learn??

They are just like us as we learn from examples of things and repeated practices and repeated practice and examples are key to machine learning as well. Scientists expose a system to examples of behavior we want to have and those examples are going to teach it. It's going to learn from those examples how to do something.

The field of intelligence has been moving extremely quickly in the last few years. Artificial Intelligence is going to be more impactful than the invention of personal computer and the spread of mobile phones in your pocket.

Idea of artificial intelligence is not new, it's been around since the very earliest days of computing. It's a grand project to build machines that are intelligent, who can think and act on their own.

 The most promising approach though is the area of machine learning rather than trying to embody machines with everything the need to know up front, rather we want to enable them to learn how to learn so that they can learn from their observations and experiences of the world and to make possible set of outputs based on those observations.

Well now answering to Alan Turing question I can say that Artificial Intelligence can think, can react and work on its own. It has power to change the world and views of the people about how they think about the world.