Mobile Banking Is On The Rise

Just a simple question to start. When did you last visit your bank? Most of you would be hard pressed remembering it. If today every activity is happening online then it is logical that banking can also be executed online. With the tremendous advancement in technology the mobile apps built for banking nowadays are very secure and up-to-date thus providing a hassle free banking experience.

Also the mobile banking apps have become very intuitive and easy to use compared to its earlier bulkier versions. A person who does not have any previous experience in operating a technical device can also easily transact using a mobile app. There are many other benefits of mobile apps which have drastically transformed the banking sector and made banking immensely easy. Some of them are enumerated below:

1) No waiting in queues

If you are one of those people whose first work of the day was to visit a bank, then you would whole heartedly appreciate how banking apps have changed your life. The days of large queues outside a bank are over. By just clicking on a few icons your banking work is done within seconds with the help of a mobile banking app.

2) Tremendous convenience to consumers

Most of the banks have their working hours between 9am and 5pm and that is also the time people go to offices for work. Previously if a person had some work in the bank then he would had to take the day off from work or had to leave early, but with the advent of mobile apps this scenario has completely vanished. With the help of his bank’s mobile app he can transact anywhere in the world and anytime of the day.

3) Immediate transfers

Normally in India it takes three days to clear a cheque issued from a different bank. This led to tremendous wastage of time and resources. Now with the help of a banking app, a businessman can transfer money immediately to his supplier or any other person in just few seconds.

How is technology driving this radical shift?

A well deployed banking solution needs to take care of universal UI/UX experience for all bank customers. Also a secure platform needs to be provided in order that customers get peace of mind by using banking apps on their mobile. Disruptive technologies like e-wallets, BHIM app, and UPI are further expanding the reach and coverage of banking

Additionally the servicing front too has received a fillip with technology offerings like cloud deployment, mobile apps, big data, AI, and IoT. These are largely driving the business strategy of private and public banks alike.

Banks which were thinking of opening thousands of branches and ATMs just two years back are now giving more importance to their banking websites and apps and are brainstorming to bring in new apps with innovative technologies which would rapidly alter the scenario further. The leap of technology has already created virtual banks and in the future a new physical bank would be a rarity.

Coucbase Vs MongoDb

Couchbase and MongoDB are both document situated databases. They both have a report as their stockpiling unit. That is basically where the similarities stop. 

Couchbase is a blend of couchdb + membase. It utilizes a strict HTTP convention to question and communicate with objects. Items (reports) are put away in basins. To question records in Couchbase, you characterize a view with the segments of the report you are keen on called the guide; and after that alternatively can characterize some total capacities over the information i.e the decrease step. 

In the event that you are putting away client information and need to inquiry all clients that have not purchased any products for as far back as three months; you would first need to compose a view (the guide) that channels these clients; once this view is distributed – couchbase will improve seeks on this and you can utilize this view (outline) your source on which you execute questions. 

You can make numerous perspectives over your reports and these perspectives are profoundly enhanced by the framework and are just reindexed when the basic record has noteworthy changes. MongoDB has a completely extraordinary way to deal with a similar issue. 

It has an idea of SQL-like inquiries, and databases and accumulations. In MongoDB, records live in an accumulation, and accumulations are a piece of a database. Much the same as Couchbase, you can store any subjectively settled report; and simply like Couchbase a programmed key is created for you.

Be that as it may, with MongoDB the way you recover archives is more similar to how you compose SQL inquiries; there are administrators for most boolean matches, and example coordinating and (with 3.0) full content hunt also. You can likewise characterize lists to help accelerate your outcomes.

An In Depth Analysis

Generally, MongoDB is less demanding to get acquainted with on the off chance that you are now alright with conventional SQL. MongoDB additionally gives the typical replication abilities and it is fit for ace replication (albeit such an arrangement isn’t empowered as a matter of course). It can most effortlessly supplant your customary social database needs; as it has similar ideas of keys/tables (“accumulations”) and question parameters – alongside the advantage of being without schematic heavy.

Couchbase and MongoDB both give business support to their databases – MongoDB’s business offering is called MongoDB Enterprise and Couchbase has Enterprise Edition (EE).

One distinction you’ll instantly discover amongst MongoDB and Couchbase is that MongoDB does not accompany a default organization reassure/GUI – in certainty a GUI and an entire facilitated administration benefit is offered as an installment choice.

You can introduce any number of outsider GUI to rapidly peruse your archives, yet having one as a matter of course would have been decent. Couchbase furnishes an astounding GUI with their free item.

Regarding simultaneousness, the Couch base server is both hopeful and in addition cynical locking while the MongoDB server is of both idealistic and skeptical bolting yet with a discretionary store machine called as the WiredTiger.

MongoDB’s work quality quickly embarrasses with developing number of clients. MongoDB can’t engage a ton of clients, the occasion the quantity of client builds, MongoDB begins performing contrarily. We have to include more devices for serving a great deal of clients through MongoDB which is truly exorbitant. Couchbase can bolster countless with the single hub without influencing its execution by any means.

The Couchbase server has the limit of putting away paired esteems till around 20 MB, yet the MongoDB server has a definitive limit of putting away gigantic records into an enormous number of archives. Despite the fact that the MongoDB server can store bigger pairs, yet one can keep on using Couchbase server with a different stockpiling administration for holding metadata on the doubles.

The Couchbase pieces the information and after that checks on a level plane by spreading hash space to every one of the hubs in the group of the information. The setting of the hash space to a specific hub is chosen by the key present in each report. For fracture of the information utilizing the MongoDB, a dividing strategy, and a key must be chosen since its information display is altogether archive base. This section key will reveal to you the correct area of the archive in the group.

The contrast between the two is that the MongoDB depends on us for picking the section key and the dividing technique, while the couchbase server does all the dividing independent from anyone else without human intercession.

In the end, it all depends on your requirements and the amount of flexibility your business can afford or needs. 

The Three Pillars Of Modern Technology

These three terms have been doing the tech rounds now for a long time, and most of us think that they are quite similar to each other. However, therein lies the basic difference between these emerging platforms.

Let us understand these platforms better to acknowledge the essential differences and their usage.

Apache Hadoop

Hadoop is an Apache open source framework written in java that allows distributed processing of large datasets across clusters of computers using simple programming models. A Hadoop frame-worked application works in an environment that provides distributed storage and computation across clusters of computers. Hadoop is designed to scale up from single server to thousands of machines, each offering local computation and storage.

Big Data

Big data means really a big data, it is a collection of large datasets that cannot be processed using traditional computing techniques. Big data is not merely a data, rather it has become a complete subject, which involves various tools, techniques and frameworks.

Data Science

Data science is a multidisciplinary blend of data inference, algorithm development, and technology in order to solve analytically complex problems.

At the core is data. Piles of raw information, streaming in and stored in enterprise data warehouses. Much to learn by mining it. Advanced capabilities we can build with it. Data science is ultimately about using this data in creative ways to generate business value.

Understanding Big Data

Big Data is a huge collection of data sets that can’t be store in a traditional system.

Big data is a complex sets of data. It’s size can be vary up to peta-bytes.

According to Gartner – Big data is huge-volume, fast-velocity, and different variety information assets that demand innovative platform for enhanced insights and decision making.

A Revolution, authors explain it as – Big Data is a way to solve all the unsolved problems related to data management and handling, an earlier industry was used to live with such problems. With Big data analytics, you can also unlock hidden patterns and know the 360-degree view of customers and better understand their needs.

Big data gets generated in multi terabyte quantities. It changes fast and comes in varieties of forms that are difficult to manage and process using RDBMS or other traditional technologies. Big Data solutions provide the tools, methodologies, and technologies that are used to capture, store, search & analyze the data in seconds to find relationships and insights for innovation and competitive gain that were previously unavailable.

80% of the data getting generated today is unstructured and cannot be handled by our traditional technologies. Earlier, an amount of data generated was not that high. We kept archiving the data as there was just need of historical analysis of data. But today data generation is in petabytes that it is not possible to archive the data again and again and retrieve it again when needed as Data scientists need to play with data now and then for predictive analysis unlike historical as used to be done with traditional.

Understanding Hadoop

Hadoop is an open source, Scalable, and Fault tolerant framework written in Java. It efficiently processes large volumes of data on a cluster of commodity hardware. Hadoop is not only a storage system but is a platform for large data storage as well as processing.

It provides an efficient framework for running jobs on multiple nodes of clusters. Cluster means a group of systems connected via LAN. Apache Hadoop provides parallel processing of data as it works on multiple machines simultaneously.

What is Data Science?

Data Science is a field that encompasses related to data cleansing, preparation, and analysis. Data science is an umbrella term in which many scientific methods apply. For example mathematics, statistics, and many other tools scientists apply to data sets. Scientist applies the tools to extract knowledge from data.

It is a tool to tackle Big Data. And then extract information from it. First Data scientist gathers data sets from multi disciplines and compiles it. After that, apply machine learning, predictive and sentiment analysis. Then sharpen it to a point where he can derive something. At last, he extracts the useful information from it.

Data scientist understands data from a business point of view.His work is to give the most accurate prediction. He takes charge of giving his predictions. The prediction of data scientist is very accurate. It prevents a businessman from future loss.

Although, these three tech platforms are related, but there is a major difference between them. Understanding them clearly can help us exploit and appreciate them better. 

The Favorite Search Engine

If you haven’t heard the name Google then you are definitely from another planet. Today Google is synonymous with the word “search”. Nowadays, plenty of people say “Google it” instead of “search it”. For a majority of the people, no other product or service is as important as Google. Founded in the year 1998 by Larry Page and Sergey Brin, it has rapidly evolved from a simple search engine at Stanford to a modern technological giant.

Today it is working on multiple products and services including driverless cars and providing internet by floating balloons in the sky. On the cusp of its 19^th anniversary, we provide you some interesting milestones of Google.

1) July 2000

Google establishes its monopoly by becoming the world’s largest search engine with an indexes capacity of around a billion. It dethrones the current reigning champion of search engines “Yahoo” from the top spot.

2) March 2004

Most people think that Gmail was launched with Google, but the truth is it was launched six years later in March 2004. Initially the service was invitation only as the release was a beta one. The general public had to wait another 3 years to experience its advanced features. Currently Gmail is the leader in email space while the followers are lagging way far behind.

3) June 2005

The year 2005 was a major milestone for Google as it released multiple products and services that proved to be a blockbuster in the coming years. The Landmark year had seen the release of Google Maps. With the help of Google Maps you can visit any part of the planet and be sure that you won’t get lost. It has made travelling fun and an exhilarating experience. Other products also launched in the same year were Google Earth, Talk and Video. It also purchased technology company Urchin which helped to create Google Analytics.

4) July 2005

“Android” the word synonymous with Smartphones today, was purchased by Google. Based on the Linux operating system it was basically designed for the touch screen devices. Today the majority of Smartphones and tablets have android as their operating system.

5) October 2008

Today most of us think YouTube as a product created by Google. But the truth is, it was purchased by Google in the year 2008. From then to now the video sharing site has seen enormous growth. Today it’s the biggest platform for video sharing leaving its competitors way far behind.

6) March 2012

Although there were many innovations and launches of products between 2008 and 2012, the launch of the Google Play store was the biggest significant event by Google in 2012. The play store has millions of apps in various categories such as games, education, entertainment, healthcare etc. It is single handedly responsible for more than a billion download of apps and installs.

7) September 2016

The year 2016 saw the launch of the smart messaging app “Allo” by Google. People were waiting for a messaging app from Google and it delivered on it. The app provides customizable emojis, stickers and doodles to make the chat interesting.

If we would put the whole list of products and services launched and offered by Google it would take plenty of pages to fill, as the innovation factory at Google continues to create exciting products year after year.

Got any other interesting Google milestone worth knowing about? Then share your views and let us know.

Which Is The Better Option React JS or React Native?

React JS is front end library developed by Facebook. It’s used for handling view layer for web and mobile apps. ReactJS allows us to create reusable UI components. It is currently one of the most popular JavaScript libraries and it has strong foundation and large community behind it.

React Native is a mobile framework that compiles to native app components, allowing you to build native mobile applications, iOS, Android, and Windows, in JavaScript that allows you to use React JS to build your components, and implements ReactJS under the hood.

Both are open sourced by Facebook.

In general the concept is the same. You write JSX on both platforms. The only difference is that the rendering mechanism that React uses is different from each other.

React JS uses react-dom implementation to render the components to the DOM. This library is actually way larger than React JS itself. React Native has their own implementation of rendering components for native platforms. 

• Both have their own rendering mechanism
• React Native has a flexbox way of styling instead of regular CSS for the web
• React Native has to be compiled to native code where ReactJS can be used directly in the DOM

The React JS Benefits

• DOM (document object model) is a viewing agreement on data inputs and outputs. React’s virtual DOM is faster than the conventional full refresh model, since the virtual DOM refreshes only parts of the page. The interesting part is, the team at Facebook wasn’t aware that partially refreshing a page would prove faster. Facebook was just looking for a way to reduce their re-build time, and partial DOM refresh was just a happy consequence. This increases performance and faster programming.
• You can reuse code components in React JS, saving you a lot of time.
• The rendering of your pages completely, from the server to the browser will improve the SEO of your web app.
• It improves the debugging speed making your developer’s life easier.
• Even to those unfamiliar with React, it is easily readable.Many frameworks require you to learn an extensive list of concepts which are only useful within the framework. React strives to do the opposite.
• You reap the benefit of all the advancements in the Java language and its ecosystem.

The React Native Benefits

• React Native comes with Native Modules and Native components that improve performance. Unlike Cordova, PhoneGap, and other cross-platform frameworks that render code via WebView, React Native renders certain code components with native API’s.
• React Native comes with all the advantages that React.js brought you. React.js focuses on a better UI, so those benefits remain.
• You don’t have to build the same application for iOS and Android, separately as React Native allows your developers to reuse the common logic layer.
• React Native’s component-based structure allows developers to build apps with a more agile, web-style approach to development than most hybrid frameworks, and without any web at all.
• If you know JavaScript, React Native will be easy to pick-up, allowing most front-end web developer to be a mobile developer. All you need to know is JavaScript, platform APIs, some native UI elements, and any other platform-specific design patterns and you’re set.
• No need to overhaul your old app. All you have to do is add React Native UI components into your existing app’s code, without having to rewrite.
• Native app development usually means inefficiency, slower time to deployment, and less developer productivity. React Native is all about bringing high speed, responsiveness, and agility of web app development along with effectual processing and best user experience to the hybrid space, to provide your users with a native app experience.

React is a framework for building applications using JavaScript. React Native is an entire platform allowing you to build native, cross-platform mobile apps, and React.js is a JavaScript library you use for constructing a high performing UI layer.

To put it in simpler terms, React is ideal for building dynamic, high performing, responsive UI for your web interfaces, while React Native is meant to give your mobile apps a truly native feel.

Python VS C++

Python and C++ are extremely different languages, and most of the differences aren’t strictly advantageous in one direction or the other. That said, for most uses, it’s easy to pick a side and make a good argument for or against particular language and implementation features. 

Python and C++ when compared with each other can lead to a lot of opinions. Each programmer will have his own opinion and we have tried to compile a few of them to give you a clear perspective. 

• Memory management: C++ doesn’t have garbage collection, and encourages use of raw pointers to manage and access memory. It differentiates between heap and stack, and it requires you to attend to values versus references. C++ requires much more attention to bookkeeping and storage details, and while it allows you very fine control, it’s often just not necessary.
• Types: C++ types are explicitly declared, bound to names, checked at compile time, and strict until they’re not. Python’s types are bound to values, checked at run time, and are not so easily subverted. Python’s types are also an order of magnitude simpler. The safety and the simplicity and the lack of declarations help a lot of people move faster. Speaking of…
• Language complexity: C++ is a beast of a language. The spec is 775 pages of language legalese, and even the best C++ developers I’ve known can be caught up short by unintended consequences in complex (or not so complex) code. Python is much simpler, which leads to faster development and less mental overhead.
• Interpreted vs compiled (implementation): C++ is almost always explicitly compiled. Python is not (generally). It’s common practice to develop in the interpreter in Python, which is great for rapid testing and exploration. C++ developers almost never do this, gdb notwithstanding.

The Essential Differences 

C++ tries to give you every language feature under the sun while at the same time never abstracting anything away that could potentially affect performance. Python tries to give you only one or a few ways to do things, and those ways are designed to be simple, even at the cost of some language power or running efficiency. 

In many cases, Python’s philosophy is an advantage because it lets you get most tasks done more easily and more quickly with less mental overhead. Of course, they also share many similarities: they’re both strongly at home in the OO paradigm; they both have a generally imperative feel with some not-entirely-comfortable functional features; they both have exceptions; they both have minimal, library-based concurrency support. 

Specific advantages of Python

• Especially clean, straightforward syntax. This is a major goal of the Python language. Programmers familiar with C and C++ will find the syntax familiar yet much simpler without all the braces and semicolons.
• Duck typing. If an object supports .quack, go ahead and call .quack on it without worrying about that object’s specific type.
• Huge standard library. Just to pick some random examples, Python ships with several XML parsers, csv & zip file readers & writers, libraries for using pretty much every internet protocol and data type, etc.
• Great support for building web apps. Along with Ruby and JavaScript, Python is very popular in the web development community. There are several mature frameworks and a supportive community to get you started.

Some advantages of C++ over Python 

• runtime performance is better and more predictable
• can be used for systems programming, like an Operating System
• can target just about every known platform including embedded systems
• good way to learn low-level programming

The software development companies prefer Python language because of its versatile features and fewer programming codes. Nearly 14% of the programmers use it on the operating systems like UNIX, Linux, Windows and Mac OS. Python is a robust programming language and provides an easy usage of the code lines, maintenance can be handled in a great way, and debugging can be done easily too. It has gained importance across the globe as even computer giant Google has made it one of its official programming languages.

Are You Googled?

The Google story begins in 1995 at Stanford University. Larry Page was considering Stanford for grad school and Sergey Brin, a student there, was assigned to show him around. By some accounts, they disagreed about nearly everything during that first meeting, but by the following year they struck a partnership. Working from their dorm rooms, they built a search engine that used links to determine the importance of individual pages on the World Wide Web.

And as they say rest is history. Google has dominated our lives in the past decade or so. However, most of us are unaware of many aspects about Google.  So, today, we bring to you some amazing facts about the company that rules the world, Google.

1. Google has the largest index of websites in the world

Google has a index with more than 3 billion websites. When this index would be printed, you’d get a 130 miles high stack of paper. Google searches through all these websites in less than half a second. This also shows the importance of SEO, you’re audience will have too find you’re website between this large index of sites.

2. The original name of Google was Backrub

Later, the company wanted to change their name, that’s how the name:Google was born. After all, Google is a misspelling of the word: Googel, the mathematical term for a one with hundred zeros. This name would reflect the company’s mission to make all information accessible too the world. That worked out pretty well, don’t you think?

3. Google Rules Internet

On August 16, 2013, Google was not reachable for 5 minutes, in that time the global Internet usage was decreased by 40%. This fact shows how important Google is today. When people can not search for the website that they are looking for, people make less use of the internet.

4. 16% to 20% of all searches have never been searched before on Google

This means that Google gets millions of searches every day that have never been done before. SEO systems have to keep themselves informed of these new developments in order to remain up-to-date. A slight mistake or a discrepancy in a keyword can hamper your page ranks.

5. The first tweet from Google 

The very first tweet by Google was in Binary Code which literally meant ” I’m feeling lucky”. Today, Google has 12.2 million followers on Twitter. 

6. The First Google Storage Was Made From LEGO

Legend has it that the reason for the LEGO construction was that the Google guys needed an easily expandable, and cheap way to house 10 4 GB hard drives, and LEGO fit the bill. Whether the primary colors of the bricks used were the hues that went on to inspire the Google logo’s design is up for debate, but we’d guess it wasn’t just a coincidence.

7. Google domain was sold off by mistake

A guy bought “Google.com” domain for just $12 in 2015 when Google mistakenly put its own domain name on sale.

Google took the domain back and awarded the buyer about $6006.13, still a pretty small amount when you consider that IT’S GOOGLE, the most visited website on the internet. If you look at the amount, it is Google written in words.

The Impact Of Machine Learning

Fewer technologies are hotter than artificial intelligence and machine learning, which mimic the behavior of the human mind. And for companies embarking on digital transformations, AI and ML are being viewed as pivotal technologies for engaging customers in a better manner.

What Can Machine Learning Achieve?

The U.S. Bank had collected a wealth of customer data. And like most banks, the U.S. Bank has struggled to derive actionable insights from this data. After adapting to Machine Learning, the bank has been using Machine Learning technology to increase personalization across the bank’s small business, wholesale, commercial wealth and commercial banking units.

Post adaptation, if a customer searched on the U.S. Bank’s website for information about mortgage loans, a customer service agent can follow up with that customer the next time they visit a branch. It also helps U.S. Bank find patterns humans might not see.

A simple change that was observed was that the software can recommend agents to call a prospective client in a particular industry on Thursday between 10 a.m. and 12 p.m. because they are more likely to pick up the phone. It can also put a calendar invite into the agent’s calendar to remind them to call the candidate the following Thursday.

Such capabilities get to the core of what many financial services organizations are trying to do; cultivate a 360-degree view of customers to recommend relevant services in the moment.

The industry is transforming from a world that was describing what happened or what is happening to a world that is more about what will or should happen. It is all about staying a step ahead, anticipating customer needs and a suitable channel to communicate with them.

How Facebook Utilizes Machine Learning

Facebook uses Machine Learning in quite a few ways! The People You May Know feature is an implementation of ML. If you browse for a certain product in E-Commerce websites, Facebook will show an ad related to that product on your news feed. That is implemented using Machine Learning as well. The list of Suggested Friends that you see when you join Facebook is based on your current workplace or school or college. That uses Machine Learning as well.

A vivid example of Facebook using Machine Learning is mentioned below:

• Open an image in facebook and right click for Inspect Element or F12.
• Then check the Inspector tab. You can see the html code for that image. If not, search for .spotlight class.
• Check the alt element content. It will give a general description of the image: no of persons, whether they/he/she are sitting, standing, laughing etc.

Understanding Google Page Ranks

Consider all the web pages in the world as nodes of a graph. All the hyperlinks i.e mentions of a website on another website as the edges.

Now, Google Page Rank basically ranks the web pages . So, a generic score needs to be assigned to every web page upon which they’ll be ranked. This score is dependent on the web pages that point it with a factor of alpha and a constant term with a factor of beta. The computations are made and the scores are computed till no further change in scores can be obtained.

PageRank is a ranking system designed to find the best pages on the web. A webpage is good if it is endorsed by other good webpages. The more webpages link to it, and the more authoritative they are, the higher the page’s PageRank score.

If one webpage links to a lot of webpages, each of its endorsements count less than if it had only linked to one webpage. That is, when calculating PageRank, the strength of a website’s endorsement gets divided by the number of endorsements it makes.

Note that this ranking is recursive, to put it more simply, the PageRank score of one webpage depends only on the structure of the network and the PageRank scores of other webpages.

Page Rank algorithm gives weight to every incoming link a web page gets, every incoming link increases Page rank, while links from pages with high page rank have high weight and matter more, links from pages with just a few outgoing links matter more.

Page Rank does not include relevance information, so incoming links from pages that have nothing to do with the page will increase page rank. However, Page Rank is only a very small portion of what determines search results. Trust rank algorithm influences search results more, since it takes into consideration how likely the site is to be trustworthy and not give irrelevant outgoing links.

In layman’s terms, all this enabled through Machine Learning, where in Google utilises its capabilities and build up a database and ranks it accordingly which enables users to access the better websites rather than the mediocre ones.

Machine Learning Is A Huge Asset 

Thinking about the future, machine learning will make its biggest mark in helping workers and businesses to more efficiently use time and gain a deeper understanding of their data. There is so much industry knowledge locked away in PDFs, medical files ,and even cookbooks. Tapping into this data, being able to organize, process and assimilate years of unstructured data points will accelerate the acquisition of knowledge, reducing the time to innovation and unearthing of new ideas. 

Adapt Machine Learning In Your Business Or Fall Behind.

Youtube – The Internet Leader

Youtube has been Internet’s favorite since a long time. It rakes in a lot of money and a lot of us underestimate the power of Youtube when it comes to advertisement and making money. A good understanding will make you realize the power of Youtube.

To begin off, we bring some amazing Youtube Facts that you might be unaware of.

1. PayPal’s Role in YouTube’s Creation

YouTube was created by Chad Hurley, Steve Chen, and Jawed Karim in 2005. The three founders knew each other from working together at another Internet start up, PayPal. In fact, Hurley designed the PayPal logo after reading a Wired article about the online payment company and e-mailing the startup in search of a job. YouTube was initially funded by bonuses received following the eBay buy-out of PayPal. You could argue that if there was no PayPal, there would be no YouTube.

2. YouTube’s Origins as a Dating Site

The founding trio didn’t come up with the YouTube concept straight away. Legend has it that YouTube began life as a video dating site dubbed “Tune In Hook Up,” said to be influenced by HotorNot. The three ultimately decided not to go that route. The inspiration for YouTube as we know it today is credited to two different events. The first was Karim’s inability to find footage online of Janet Jackson’s “wardrobe malfunction,” and the second when Hurley and Chen were unable to share video footage of a dinner party due to e-mail attachment limitations.

3. The First Ever YouTube Video

The first video to ever be uploaded to YouTube isn’t a classic by any means. Shot by Yakov Lapitsky at the San Diego Zoo it shows co-founder Jawed Karim in front of the elephant enclosure going on about long trunks. It has, nonetheless, racked up a very healthy 4,282,497 views since its online debut on April 23, 2005.

4. Statistics

We spend around 2.9 billion hours on YouTube in a month — over 325,000 years. And those stats are just for the main YouTube website , they don’t incorporate embedded videos or video watched on mobile devices.

5. Mobility

YouTube has over a billion users and a majority of them are watching videos on their mobile device, a testament to the rising popularity of smartphones as internet connectivity on cellular networks is improving.

6. The Code For Gangnam Style

Psy’s Gangnam Style is the definition of viral in practical terms and currently sits north of 2.8 billion views on YouTube, making it the highest watched YouTube video ever.

YouTube had a 2, 147, 483, 647 view counter limit in its code and Gangnam Style was going viral and looked like it’ll cross that threshold. The coder’s at the company quickly changed the code before Psy broke YouTube’s counter.