from the principal’s desk · from siri to self-driving cars ai is progressing rapidly. ai is not...

Mount Carmel College Digitally Yours Version 18.0

Department of Computer Science

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FROM THE PRINCIPAL’S DESK

I congratulate the Department of

Computer Science and MCA for their

efforts in bringing out this newsletter

on the theme “Artificial Intelligence –

Marvel Creations Dawn of simulated

cognition. “Alexa." "Siri." "Hey,

Google." these are the names that

today’s generation call out now,

perhaps more often than we call out those of friends and family members. Artificial intelligence

(AI) isn’t part of a science-fiction future; it’s our reality. Over the past decade we’ve become

accustomed to the idea that when we call a customer service line, we must often pass through a

gauntlet of voice-activated technology before reaching a human. In some ways, it’s an evolution

of the wisdom of the crowds; only instead of having to sift through the potential options, it simply

surfaces what you are most likely to enjoy. I wish the department to grow and explore the

research directions in this current emerging area and reach greater heights.

Dr. Sr. ARPANA

MESSAGE FROM CO-ORDINATOR, DEPARTMENT OF MCA

Will machines surpass human levels of intelligence and ability? From SIRI to self-driving cars AI is

progressing rapidly. AI is not only the Marvel Hero’s with human-like characters but it's a super-

intelligence that can encompass anything and even might help us eradicate war, disease and poverty

[Some experts have expressed concern on this 'Super Intelligence' that it could be extremely powerful

possibly beyond our control]. But remember there's still an underlying level we haven't yet touched. Yes

we haven't rewritten the human brain! I congratulate the editorial team of Computer Science and MCA

department for choosing this theme for this version of 2K18 and wish them all the very best.

Ms. VIJAYALAKSHMI N



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ARTIFICIAL INTELLIGENCE, THE COMING WAVE

Since the invention of computers or machines,

their capability to perform various tasks went on

growing exponentially. Humans have developed

the power of computer systems in terms of their

diverse working domains, their increasing speed,

and reducing size with respect to time. A branch

of computer science named “Artificial

Intelligence” focuses on creating the computers

or machines as intelligent as human beings.

According to the father of Artificial Intelligence,

John McCarthy, it is “The science and

engineering of making intelligent machines,

especially intelligent computer programs”. It is a

way of making a computer, a computer-

controlled robot, or a software think

intelligently, in the similar manner the intelligent

humans think. This is accomplished by studying

how human brain thinks and how humans learn,

decide, and work while trying to solve a problem,

and then using the outcomes of this study as a

basis of developing intelligent software and

systems. While exploiting the power of the

computer systems, the curiosity of human, lead

him to wonder, “Can a machine think and

behave like humans do? “Thus, the development

of Artificial intelligence started with the

intention of creating similar intelligence in

machines that we find and regard high in

humans. Some of the goals are: To create expert

systems − The systems which exhibit intelligent

behaviour, learn, demonstrate, explain, and

advice its users. To implement human

intelligence in machines − Creating systems that

understand, think, learn, and behave like

humans. Artificial Intelligence has been

dominant in various fields such as –gaming,

natural language processing, expert systems,

vision systems, speech recognition, handwriting

recognition and intelligent robots. Hence it is

something which could also be a threat to

humanity. It should be implemented at a

moderate pace since this is a very powerful tool

and could even dominate our day to day

activities. Therefore, artificial intelligence is

something which could be a boon or a bane to

us.

Shriya Raj III MCA

Technology is the campfire around which we tell our stories



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3D PRINTING 3D printing or additive manufacturing is a

process of making three dimensional solid

objects from a digital file.

There are several ways to 3D print. All these

technologies are additive, differing mainly in the

way layers are built to create an object. Some

methods use melting or softening material to

extrude layers. Others cure a photo-reactive

resin with a UV laser (or another similar power

source) layer by layer.

Some of the processes are:

Vat Photo polymerisation

Material Jetting

Binder Jetting

Material Extrusion

Powder Bed Fusion

Sheet Lamination

Directed Energy Deposition

Applications of 3D printing

3D printing has many applications in

manufacturing, medicine, architecture, and

custom art and design.

Applications in medical field

Medical applications in field of 3d printing has

evolved considerably. Recently published

reviews describe the use of 3D printing to

produce bones, ears, exoskeletons, windpipes, a

jaw bone, eyeglasses, cell cultures, stem cells,

blood vessels, vascular networks, tissues, and

organs, as well as novel dosage forms and drug

delivery devices. The current medical uses of 3D

printing can be organized into several broad

categories. There’s little question that 3D

medical advances are going to make life better

for many people. With printers, people in

remote areas or on airplanes or cruise ships will

have access to faster medical care in

emergencies. In the past, it would have been

necessary to either ship medical parts to the

injured/sick person or bring him or her to a major

hospital, now the essential part can simply be 3D

printed.

In the food industry

Bringing the food industry to the digital age is

one of the essential and revolutionary

applications of 3D printing. Using robotic

layer-based food printing systems allows the

recipe of the food to be digitized and saved in

order to prepare very repeatable and

high-quality dishes without any margin for

operator error. Also, the shape and decoration

of the food can be individualized based on the

customer or the occasion.

A company called Choc Edge is currently

marketing "The world's first commercial 3D

chocolate printer", the Choc Creator. It uses a

nozzle to dispense molten chocolate into any

pattern and shape. While the $3,500 price might

be expensive for home use, it can prove to be



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very successful for niche shops tailoring to

specific customers or events

Field of Shelter

Shelter is another basic human necessity which

can be an interesting application for 3D printing

Conventional building methods are hazardous,

time consuming, and expensive; 3D printing of

buildings can enable automated creation of

variety of buildings quickly and efficiently.

Field of Transportation

3D printers are creating parts for cars and

airplanes, transforming the aerospace and

automobile industries. It’s even possible to print

entire vehicles. Beyond this, there are

applications for using this technology for

building materials. NASA now uses 3D printed

rocket engines. In the near future, 3D printing is

likely to make transportation faster, cheaper,

and safer.

Field of Construction and Architecture

3D printers can not only print out models but

actual homes and other buildings. A company in

China, for example, has built a 3D-printed house

made to withstand powerful earthquakes. This is

another area where we are only starting to

scratch the surface of potential applications. As

this technology gets cheaper and more refined,

3D-printed homes could help address issues such

as homelessness and housing shortages.

Future of 3D printing

In the coming years, 3-D printers will be at the

heart of full-scale production capabilities in

several industries, from aerospace to

automotive to health care to fashion.

Manufacturing as we know it will never be the

same. 3D printing has countless possibilities in

many industries and areas of life. 3D-printed

items will increasingly be used to make items for

all purposes, from the frivolous to the practical

to the humanitarian. Only time will tell where

this technology will take us. 3D printing is likely

to radically change the way people purchase

many items. First, e-commerce made it possible

to order products from the comfort of your

home. 3D printing will create new possibilities,

where you choose the specifications and simply

print out what you want.

-ANNIE SIMRIN SIRISHA.DK

II BCA

The science of today is technology of tomorrow



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CROSSWORD

- SRISHTI III MCA



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WHEN CELLULAR NETWORKS MEET ARTIFICIAL INTELLIGENCE

Currently, fourth-generation (4G) cellular

networks are being globally deployed to provide

all-IP (Internet Protocol) broadband

connectivity. Recalling that second-generation

(2G) global networks for mobile communications

(GSM), debuted in 1991, just started to provide

digital voice telephony, and third-generation

(3G) cellular networks, launched in 2001, initially

provided mobile Internet solutions. Nowadays,

the landscape of the Information

Communication Technology (ICT) industry is

rapidly changing. Therefore, to enhance service

provisioning and satisfy the coming diversified

requirements, it is necessary to revolutionize the

cellular networks with cutting-edge

technologies. The standardization of next-

generation (5G) cellular networks is being

expedited, which also implies more of the

candidate technologies will be adopted.

5G cellular networks are assumed to be the key

enabler and infrastructure provider in the ICT

industry, by offering a variety of services with

diverse requirements. The standardization of 5G

cellular networks is being expedited, which also

implies more of the candidate technologies will

be adopted. Therefore, it is worthwhile to

provide insight into the candidate techniques as

a whole and examine the design philosophy

behind them. In this article, I try to highlight one

of the most fundamental features among the

revolutionary techniques in the 5G era, i.e.,

there emerges initial intelligence in nearly every

important aspect of cellular networks, including

radio resource management, mobility

management, service provisioning

management, and so on. However, faced with

ever-increasingly complicated configuration

issues and blossoming new service

requirements, it is still insufficient for 5G cellular

networks if it lacks complete AI functionalities.

Hence, we further introduce fundamental

concepts in AI and discuss the relationship

between AI and the candidate techniques in 5G

cellular networks. Specifically, we highlight the

opportunities and challenges to exploit AI to

achieve intelligent 5G networks, and

demonstrate the effectiveness of AI to manage

and orchestrate cellular network resources. We

envision that AI-empowered 5G cellular

networks will make the acclaimed ICT enabler a

reality.’

- RINIYA BENNY

II BCA

FACTS ABOUT 5G

Design and preserve the future through advanced methods of technology



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If you've never heard of 5G wireless connections

(they barely even exist yet). And the ones that do

aren't even official 5G connections because no

one can decide on what that even means yet.

But 5G is coming, and many wireless carriers and

technology companies are already investing in

the new technology. So here are five facts to

know about 5G.

5G wireless will be available by 2020, or even a

bit earlier. Verizon Communications (NYSE: VZ),

Alphabet's (NASDAQ: GOOG) (NASDAQ: GOOGL)

Google, and AT&T (NYSE: T) are already testing

5G technologies right now. Google is testing

solar-powered drones that can stay up in the sky

for as long as five years and beam down 5G

signals to users. AT&T and Verizon are taking a

more traditional approach and are currently

using 5G signals near their respective

headquarters. Verizon says it will roll out tests in

Boston, New York and San Francisco later this

year. But there aren't any set standards for 5G

yet. The international wireless standards body,

3GPP, is still determine the specifications, along

with Ericsson, Samsung, Nokia, Cisco Systems,

and Verizon. The next generation of wave radio

transmissions standards are likely to be set by

2018.5G will be lightning fast. Verizon says that

its 5G network will likely be 200 times faster than

the 5Mbps speeds many of its users get on 4G

LTE. That means 5G speeds will hit 1 Gbps, which

is currently the fastest speed you can get from

Google Fiber. At that rate, you'll be able to

download an HD movie in seven seconds. Speeds

are expected to increase even higher than 1Gbps

as well, as 5G evolves.

5G will likely be the next major fight for wireless

carriers, and no one wants to be left out. The

major U.S. carriers are all closing the gap on their

4G LTE coverage and speeds, which means they'll

likely latch onto their 5G networks to

differentiate themselves. AT&T was dismissive

about any type of 5G talk just a few months ago,

but is now very open about its 5G plans. The

company's about-face shows just how much

carriers don't want to be seen as falling behind.

5G will cost more than 4G LTE connections, but

probably not much more. According to research

by the University of Bridgeport, carriers will likely

keep costs around the same as they are now, but

you'll get much faster speeds. That's because

carriers reduce the price of data by a little bit

each year. Huawei and Nokia believe 5G will cost

more than 4G LTE, but say that the carriers won't

be able to charge too much more than the

current rates.

Garima Singh

II B.Sc. CMS



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5G NETWORKS

5G network are the next generation of mobile

internet connectivity, offering faster speeds and

more reliable connections on smartphones and

other devices than ever before.5G is a marketing

term for some new mobile technologies.

The ITU IMT-2020 standard provides for speeds

up to 20 gigabits and has only been

demonstrated with high frequency millimetre

waves of 15 gigahertz and higher. ITU has

divided 5G network services into three

categories: enhanced Mobile Broadband (eMBB)

or handsets, Ultra-Reliable Low-Latency

Communications (URLLC), which includes

industrial applications and autonomous vehicles,

and Massive Machine Type Communications

(MMTC) or sensors.

With speeds of up to 100 gigabits per second, 5G

will be as much as 1,000 times faster than 4G, the

latest iteration of mobile data technology. 5G

will, however, make communications so fast

they become almost real-time, putting mobile

internet services on a par with office services.

5G will increase download speeds up to 10

gigabits per second. That means a full HD movie

can be downloaded in a matter of seconds. It will

also reduce latency significantly (giving people

faster load times). In short, it will give wireless

broadband the capacity it needs to power

thousands of connected devices that will reach

our homes and workplaces.

5G technology is driven by 8 specification

requirements

Up to 10Gbps data rate - > 10 to 100x

improvement over 4G and 4.5G networks

1-millisecond latency

1000x bandwidth per unit area

Up to 100x number of connected devices per

unit area (compared with 4G LTE)

99.999% availability

100% coverage

90% reduction in network energy usage

Up to 10-year battery life for low power IoT

devices

-Kritika. R Jain

II BCA

Any sufficiently advanced technology is indistinguishable from magic



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INTRODUCTION TO DEEP LEARNING

Deep learning is a subfield of machine learning it

is concerned with algorithms inspired by the

structure and function of the brain called

artificial neural networks. Deep learning was

introduced with the objective of moving

Machine Learning closer to one of its original

goals: Artificial Intelligence.

Machine learning: It is an application of AI that

provides systems the ability to automatically

learn and improve from experience without

being programmed. Its primary aim is to allow

computers to learn automatically.

The 2 main types of machine learning can be

supervised and unsupervised. Under supervised

machine learning the data scientist acts as a

guide to teach the algorithm what conclusions it

should come up with, while unsupervised

machine learning is more closely aligned with

what some call true artificial intelligence — the

idea that a computer can learn to identify

complex processes and patterns without a

human to provide guidance along the way.

Artificial Neural Networks (ANN)

The inventor of the first neurocomputer, Dr.

Robert Hecht-Nielsen, defines a neural network

as −"...a computing system made up of a number

of simple, highly interconnected processing

elements, which process information by their

dynamic state response to external inputs.”

The ANN is like an artificial human nervous

system for receiving, processing, and

transmitting information in terms of Computer

Science.

The idea of ANNs is based on the belief that

working of human brain by making the right

connections can be imitated using silicon and

wires as living neurons and dendrites.

Why Deep Learning

Deep Learning has enabled many practical

applications of Machine Learning and by

extension the overall field of AI. Deep Learning

breaks down tasks in ways that makes all kinds

of machine assists seem possible, even likely.

Driverless cars, better preventive healthcare,

even better movie recommendations, are all

here today or on the horizon.



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Deep Learning identifies defects that would

otherwise be difficult to detect. When consistent

images are challenging due to ambient

conditions, product reflection, or lens distortion,

Deep Learning can account for these types of

variations and learn interesting features to make

your inspection robust.

It has the best-in-class performance on problems

that significantly outperforms other solutions in

multiple domains. This includes speech,

language, vision, playing games like Go etc. This

isn’t by a little bit, but by a significant amount.

Reduces the need for feature engineering, one of

the most time-consuming parts of machine

learning practice.

Is an architecture that can be adapted to new

problems relatively easily (e.g. Vision, time

series, language etc.) using techniques like

convolutional neural networks, recurrent neural

networks, long short-term memory etc.

- Tanya

II BCA

ITS RIDDLES TIME….

1.What is an alien’s favourite place on the

computer?

2.Why did the computer get glasses?

3.What does a computer do when it's tired?

4.How do you know when a computer monitor

is sad?

5.What do the cookie and the computer have in

common?

Nihad Afza III MCA

Simplicity is about subtracting the obvious and adding the meaningful.



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HOW AI IS DRIVING THE FUTURE OF AUTONOMOUS CARS

Over the past decade, the United States has seen

an explosion of autonomous vehicle technology

that has swept across the auto industry. This

wave of progress encompasses all aspects of

computer technology, software engineering, and

thought-leaders from major automakers like

Tesla, BMW, Ford, Audi, and even Google. While

many have only started hearing about

autonomous technology recently, self-driving

car research has been going on now for over 45

years. One of the earliest research publications

on autonomous vehicle technology can be found

in an article IEEE Spectrum from 1969. In the

featured article, lead engineers Robert E. Fenton

and Karl W. Olson hypothesized that the future

of automated vehicles would rely on “smart

infrastructure” that would guide the cars on

roadways. As a result, autonomous vehicles now

rely on onboard technologies and state of the art

computers to observe and process their

environment.

While the technology used has made leaps and

bounds, the ability for computers to understand

their surrounding and make decisions based on

relevant information has also improved. Artificial

Intelligence (AI) plays an integral role in the

progression of self-driving vehicles on public

roads.

AI: the brain of autonomous vehicles

Just like a human, self-driving cars need to have

sensors to understand the world around them

and a brain that collects processes and chooses

specific actions based on information gathered.

The same goes for self-driving cars, and each

autonomous vehicle is outfitted with advanced

tools to gather information, including long-range

radar, LIDAR, cameras, short/medium-range

radar, and ultrasound. Each of these

technologies is used in different capacities, and

each collects different information. However,

this information is useless unless it is processed

and some form of action is taken based on the

gathered information.

This is where Artificial Intelligence comes into

play and can be compared to the human brain,

and the actual goal of Artificial Intelligence is for

a self-driving car to conduct in-depth learning.

In a recent interview, Sameep Tandon, CEO and

co-founder of Drive.ai, explains “deep learning is

the best enabling technology for self-driving

cars.” He goes on to explain that “you hear a lot



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about all these things on a car: the sensors, the

cameras, the radar, and LIDAR. What you need

are the brains to make an autonomous car work

safely and understand its environment.”

Artificial Intelligence has many applications for

these vehicles; among the more immediate and

obvious functions:

Directing the car to a gas station or recharge

station when it is running low on fuel.

Adjust the trip’s directions based on known

traffic conditions to find the quickest route.

Incorporate speech recognition for advanced

communication with passengers.

Eye tracking for improved driver monitoring.

Natural language interfaces and virtual

assistance technologies.

RINIYA BENNY

II BCA

Puzzle

Part of a family of machine learning

methods.

Big and complex data set.

Ai that conducts conversion via textual

method.

Makes enterprise software.

Software testing framework for web

application across.

Data structures used in ai.

High level programming language.

List of records using cryptography.

Field of study where machine acts like

human.

Interpretation of meaningful pattern in

data.

Set of rules followed in calculation by

computers.

Faiza Rahaman

III BSc CMS



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INDUSTRIAL VISIT

Philips Innovation Campus, Bengaluru

Date : 30Th January 2017

IT CLUB ACTIVITY

CUL-WEEK

On 20th and 21st July 2017

Organised by

TALK ON ARTIFICIAL

INTELIGENCE

By Hemant Pawar

Service Delivery

Manager at IBM

Global Business

Services

On 31st January 2018

III sem MCA - SUR-SANGRAM-SURANA

COLLEGE INTERCOLLEGIATE FEST

Overall Runners.

I place in digital collage & II place in digital

marketing.



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DRIVERLESS CAR

Driverless car seems like a thing in sci-fi movies

but this is changing into reality in 2018.

Driverless cars are closer to becoming an

everyday part of world.

What does Driverless Car mean?

A driverless car is a vehicle that can guide itself

without human conduction. This kind of vehicle

has become a concrete reality and may pave the

way for future systems where computers take

over the art of driving. It is also known as a

autonomous car, robot car or self-driving car. It

is developed in companies like BMW, Mercedes,

Tesla, etc.

A driverless car uses an artificial intelligence

system that senses its surroundings, processes

the visual data to determine how to avoid

collisions, operates car machinery like the

steering and brake, and also uses GPS to track

the car's current location and destination. To

perceive visual surroundings, most self-driving

cars have some combination of visual systems

like video cameras, deep learning software to

interpret objects like street lights and stop signs,

and while radar catches most obstacles instantly,

it’s not as good as spotting smaller obstacles as

lidar.

Fully driverless tech is still at an advanced testing

stage, but partially automated technology has

been around for the last few years. Executive

saloons like the BMW 7 Series feature

automated parking, and can even be controlled

remotely.

Although autonomous car functions efficiently, it

still face problems like the unpredictable

behaviour of humans which represent challenge

for the technology. The Google Car is one of the

most experienced autonomous vehicles, and its

interaction with human drivers has exposed one

of driverless cars’ main weaknesses. The first

injury involving the Google Car wasn’t due to a

fault in its system, but human-error.

For example, if I move in front of driverless car

then I have no idea how the car will behave. But

driverless car is designed and programmed in

such a way that it will predict how a human being

is going to react. At this stage the programming

is at risk if there is any serious injure to human

or human property. Hence concluding that

autonomous cars are at risk when surrounded by

human road users.

Until these problems are solved, fully

autonomous cars will pose a dangerous risk to

other road users. At the moment, driverless cars

are only truly safe when tested and operated

around other driverless cars in a controlled

environment. But in nearing years we'll benefit

from driverless car by improving in technology

by avoiding accidents.

Jyothi Khati

II B.Sc. CME



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AI ALGORITHM CAN TEACH CARS SELF-DRIVING IN 20 MINUTES

A start-up founded by two researchers from

the Cambridge University, has developed an

artificial intelligence (AI) algorithm that can

learn how to drive a car from scratch in 20

minutes. Instead of relying on external sensors

and custom-built hardware, the start-up wants

to create autonomous vehicles which are

entirely software-based. It was hooked up with

a learning program to intelligently analyse the

camera's data in real-time. Then the car was

given full autonomous control.

Every time it off-roader, a human driver

corrected it. The algorithm accordingly kept

tweaking itself, and within 20 minutes learned

how to drive

The AI algorithm powering self-driving system

doesn't require any cloud connectivity or pre-

loaded maps. It is a four-layer convolutional

neural network that processes everything on a

GPU.

"The missing piece of the self-driving puzzle is

intelligent algorithms, not more sensors, rules,

and maps," co-founder and CEO Amar Shah

said.

MEGHA BALIYAN

III PMC

The great growling engine of change – technology



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BIG DATA

Training the many layers of virtual neurons in

the experiment took 16,000 computer

processors—the kind of computing

infrastructure that Google has developed for

its search engine and other services. At least 80

percent of the recent advances in AI can be

attributed to the availability of more computer

power, reckons Dileep George, cofounder of

the machine-learning start-up Vicarious.

There is more to it than the sheer size of

Google’s data centres, though. Deep learning

has also benefited from the company’s

method of splitting computing tasks among

many machines so they can be done much

more quickly. That is a technology Dean helped

develop earlier in his 14-year career at Google.

It vastly speeds up the training of deep-

learning neural networks as well, enabling

Google to run larger networks and feed a lot

more data to them.

Already, deep learning has improved voice

search on smartphones. Until last year,

Google’s Android software used a method that

misunderstood many words. However, in

preparation for a new release of Android last

July, Dean and his team helped replace part of

the speech system with one based on deep

learning. Because the multiple layers of

neurons allow for more precise training on the

many variants of a sound, the system can

recognize scraps of sound more reliably,

especially in noisy environments such as

subway platforms. Since it is likelier to

understand what was actually uttered, the

result it returns is likelier to be accurate as

well. Almost overnight, the number of errors

fell by up to 25 percent—results so good that

many reviewers now deem Android’s voice

search smarter than Apple’s more famous Siri

voice assistant.

For all the advances, not everyone thinks deep

learning can move artificial intelligence toward

something rivalling human intelligence. Some

critics say deep learning and AI in general

ignore too much of the brain’s biology in

favour of brute-force computing.

One such critic is Jeff Hawkins, founder of Palm

Computing, whose latest venture, Numenta, is

developing a machine-learning system that is

biologically inspired but does not use deep

learning. Numenta’s system can help predict

energy consumption patterns and the

likelihood that a machine such as a windmill is

about to fail. Hawkins, author of On

Intelligence, a 2004 book on how the brain

works and how it might provide a guide to

building intelligent machines, says deep

learning fails to account for the concept of

time. Brains process streams of sensory data,

he says, and human learning depends on our

ability to recall sequences of patterns: when

you watch a video of a cat doing something

funny, it is the motion that matters, not a

series of still images like those Google used in



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its experiment. “Google’s attitude is: lots of

data makes up for everything,” Hawkins says.

However, if it does not make up for everything,

the computing resources a company like

Google throws at these problems cannot be

dismissed. They are crucial, say deep-learning

advocates, because the brain itself is still so

much more complex than any of today’s neural

networks. “You need lots of computational

resources to make the ideas work at all,” says

Hinton.

RINIYA BENNY

II BCA

BITCOINS

Bit coin is a new currency that was created in

2009 by an unknown person Satoshi

Nakamoto. Bit coin is the first decentralized

digital currency. Bit coins are digital coins you

can send through the internet. Compared to

other alternatives bit coins have a number of

advantages. Bit coins are transferred directly

from person to person via the net without

going through a bank or clearing outs.

This means that the fees are much lower.

You can use them in every country.

Your count cannot be frozen.

There are no prerequisites or arbitrary limits.

How are they created?

Bit coins are generated all over the internet

by anybody running a free application called a

Bit coin miner. Mining requires a certain

Technology like art is a soaring exercise of the human imagination



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amount of work for each block of coins. This

amount is automatically adjusted by the

network such that the Bit coins are always

created at a predictable and limited rate.

Your bit coins are stored in your digital wallet

which might look familiar if you use online

banking. When you transfer Bit coins, an

electronic signature is added and after few

minutes the transaction is verified by a minor

and permanently and anonymously stored in

the network on a ledger called block chain.

After a certain amount of transactions have

been verified by the miner, that miner will

receive newly minted bit coins for their work.

The Bit coin software completely open source

and anybody can review the code. Bit coin is

changing finance the same way the web

change publishing. When everyone has access

to the Global market great ideas flourish.

Some examples to how Bit coins are already

used today:

You can purchase video games gifts, books

and servers.

Several currency exchanges exist where you

can trade your Bit coins for dollar, euro and

more.

Bit coins a great pay for small businesses and

freelancers to get noticed. It doesn't cost

anything to start accepting them.

There are no charge banks or fees. And you'll

get additional business from the bit coin

economy.

VINDHYA.H II BCA

5 THINGS YOU SHOULD KNOW ABOUT BITCOIN AND DIGITAL

CURRENCIES

The difference between virtual, digital,

and cryptocurrencies

Virtual currency was defined in 2012 by the

European Central Bank as "a type of

unregulated, digital money, which is issued

and usually controlled by its developers, and

used and accepted among the members of a

specific virtual community." Last year, the US

Department of Treasury said that digital

currency operates like traditional currency, but

does not have all the same attributes — as in,

it does not have legal tender.

Digital currency, however, is a form of virtual

currency that is electronically created and

stored. Some types of digital currencies are

cryptocurrencies, but not all of them are.

So that leads us to the more specific definition

of a cryptocurrency, which is a subset of digital

currencies that uses cryptography for security

so that it is extremely difficult to counterfeit. A



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defining feature of these is the fact they are

not issued by any central authority.

The origin of Bitcoin

Bitcoin is a cryptocurrency, a number

associated with a Bitcoin address. In 2008, a

programmer (or group of programmers) under

the pseudonym Satoshi Nakamoto published a

paper describing digital currencies. Then in

2009, it launched software that created the

first Bitcoin network and cryptocurrency.

Bitcoin was created to take power out of the

hands of the government and central bankers,

and put it back into the hands of the people.

The origin of Dogecoin

Dogecoin is a form of cryptocurrency that was

created in December 2013. It features Doge,

the Shiba Inu that has turned into a famous

internet meme. It was created by Billy Markus

from Portland, Oregon, who wanted to reach a

broader demographic than Bitcoin did. As of

March, more than 65 billion Dogecoins have

been mined, and the production schedule of

this cryptocurrency is in production faster than

most.

Other types of digital currencies

There are other types of digital currencies,

though we don't hear much about them. The

next most popular is probably Litecoin, which

is accepted by some online retailers. It was

inspired by Bitcoin and is nearly identical, but

it was created to improve upon Bitcoin by

using open source design.

There are many other types of

cryptocurrencies, such

as Peercoin, Ripple, Master coin, and Name

coin. Cryptocurrencies get some dissension

because they are often replicating of other

versions, with no real improvements.

Where you can use Bitcoin

There are many places you can use Bitcoin to

purchase products or services. There is no real

rhyme or reason to the list, which includes big

corporations and smaller, independent

retailers including bakeries and restaurants.

You can also use the currencies to buy flights,

train tickets, and hotels on Cheap Air;

upgrades to your OK Cupid profile; products

on Overstock.com; gift cards on eGifter.

There's a list on Spend Bitcoins that shows all

the places that accept the cryptocurrency.

RINIYA BENNY

II BCA

It’s not that we use technology, we live technology



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ANSWERS

CROSSWORD

RIDDLES: CROSSWORD

1.Space

2.To improve its web sight

3.It crashes

4.When it breaks down

5.They both have chips

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