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Discover: Interesting Ways Netflix Relies on Big Data

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Discover: Interesting Ways Netflix Relies on Big Data

Netflix boasts of over 100 million subscribers – a humongous wealth of data is stored and analyzed to enhance user experience. Big data makes Netflix the King of Stream; it keeps the customers engaged and content.

Big data recommends Netflix a list of programs that interests the viewers and this system actually influences 80% of content that is available on Netflix. Estimates say the cutting edge algorithms save $1 billion a year in value from customer retention – undoubtedly, a whopping figure for the entertainment industry.

Big data is used extensively all through Netflix application, BUT the Holy Grail is the prediction part: what the customers want to watch and enjoy matters the most. Moreover, big data is the fuel that powers up the recommendation engines that are created to serve the purpose.

netflix-and-devices-243

Healthy prediction of viewing habits

Efforts started way back in 2006, when Netflix was primarily into DVD-mailing business. It initiated the Netflix prize, rewarding $1 million to any group, which can devise the best algorithm to predict how a customer would rate a particular movie, based on previous ratings. Today, though the algorithms are constantly updated, but the principles still remain a key characteristic of a recommendation engine.

In the beginning, analysts were left with very little data about their customers, but as soon as streaming became more mainstream, new data points about their customers became easily available. What affects a particular movie had on a viewer could be assessed, as well as models were built to predict the ‘perfect storm’ situation for customers who were served with the movies they like.

Infographic-Netflix-knows-when-youre-Hooked

Identifying the next smashing series

Of late, Netflix has broadened its scope to include content creation, instead of limiting itself to being a distribution method for movie studios and other channels. This strategy is of course backed by meaningful data – which highlighted how its viewers are hungry for content directed by David Fincher and starring Kevin Spacey.

Every minute part of the production of the series is structured on data, including the colors used on the cover image of the series to draw in subscribers.

Netflix

For a quality experience

Netflix takes the quality aspect into great consideration. It closely monitors and analyzes the various factors that affect user behavior. Even, it develops models to explore how they perform. While, a large number of shows are hosted internally on its own distributed network of servers, they are also reflected around the world by ISPs and other hosts. Along with improving the user experience, efficient content streaming reduces costs for ISPs – shielding them from the cost of downloading data from Netflix server.

Big data and analytics have positioned themselves in the right order to dictate the operations across all Netflix platforms. They surely lead the pack of data by taking over distribution and production networks and re-modifying them through constant evolution and innovation of data.

Not only this, Netflix has reduced its promotional campaign budgets by targeting only the most relevant and interested people at the same time. All possible because of big data.

So, next time, when you peruse through your favorite shows in Netflix, do think and thank the power of big data. Because, big data is much more than what you think!

DexLab Analytics, a renowned big data training institute in Gurgaon is the best place to start a big data certification endeavor. The consultants are proficient in what they teach, the course curriculum is comprehensive and flexible course modules are suitable for everyone, irrespective of professionals or students.

The article has been sourced from:                                 

https://insidebigdata.com/2018/01/20/netflix-uses-big-data-drive-success

http://dataconomy.com/2018/03/infographic-how-netflix-uses-big-data-to-drive-success

https://www.linkedin.com/pulse/amazing-ways-netflix-uses-big-data-drive-success-bernard-marr

 

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5 Steps to Reassess Your Big Data Business Strategy

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5 Steps to Reassess Your Big Data Business Strategy

Company employees at all levels need to understand the role of big data in planning business strategies. Strategic planning has to be dynamic- constantly revised and aligned with the current market trends.

As the first quarter of 2018 is nearing to its end, here are 5 domains every business needs to pay attention to:-

  • Information retention for field-based technology:

In the current tech-driven business world, a lot of information needs to be collected from field-based technologies, like drones and sensors. Owing to internet bandwidth constraints, this data has to be stored locally instead of transmitting them for collection in a central location. Bandwidth constraints affect cloud-based storage systems too. Thus, companies need to restore traditional practices of distributed data storage, which involve collecting data locally and storing them on servers or disks.

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  • Collaboration with cloud vendors:

Cloud hosting is popular among businesses, especially in small and midsized enterprises. Onsite data activities of companies include maintenance of infrastructure and networks that ensure internal IT access. With the shift towards cloud-based applications, businesses need to revise disaster recovery plans for all kinds of data. It should be ensured that vendors adhere to corporate governance standards, implement failover if needed, and SLAs (Service Level Agreements) match business needs. It is often seen that IT strategic plans lack strong objectives pertaining to vendor management and stipulated IT service levels.

  • How a company defines ROI:

In the constantly evolving business scenario, it is necessary to periodically re-evaluate the ROI (return on investments) for a technology that was set at the time of purchasing it. Chief information officers (CIOs) should regularly evaluate ROIs of technological investments and adjust business course accordingly. ROI evaluation should be a part of IT strategic planning and needs to be revisited at least once a year. An example of changing business value that calls for ROI re-assessment is the use of IoT technology in tracking foot traffic in physical retail stores. At a point of time, this technology helped managers display the most desirable products in best positions within a store. With the shift of customer base from physical to online venues, this tech has become redundant in terms of physical merchandising.

  • How business performance is assessed:

Like shifting ROIs, KPIs (key performance indicators) for companies that are based on inferences drawn from their data, are expected to change over time. Hence, monitoring these shifting KPIs should be a part of a company’s IT strategic plan. For example, customer engagements for a business might shift from social media promotions to increased mentions of product defects. Therefore, to improve customer satisfaction, businesses should consider reducing the number of remanufacture material authorizations and IoT alerts for sensors/devices in the production processes of these goods.

  • Adoption of AI and ML:

Artificial intelligence and machine learning play major roles in the current technological overhaul. Companies need to efficiently incorporate AI-powered and ML-based technologies in their business processes. Business leaders play key roles in identifying areas of a business where these techs could add value; and then testing their effectiveness through small-scale preliminary projects. This should be an important goal in the R&D strategic planning of business houses.

Let’s Take Your Data Dreams to the Next Level

As mentioned in Harvard Business review, ‘’the problem is that, in many cases, big data is not used well. Companies are better at collecting data-about their customers, about their products, about competitors-than analyzing the data and designing strategy around it.’’

‘’Used well’’ means not only designing superior strategies but also evolving these strategies with changing market trends.

From IT to marketing- professionals in every sector are going for big data training courses to enhance their competence. Enroll for the big data Hadoop certification course in Gurgaon at DexLab Analytics– a premier data analyst training institute in Delhi.

 

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5 Examples that Show Artificial Intelligence is the Order of the Day of Daily Life

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Artificial Intelligence is no more an elusive notion from science fiction; in fact, it’s very much in use in everyday life. Whether you realize it or not, the influence of AI has grown manifold, and is likely to increase further in the coming years.

5 Examples that Show Artificial Intelligence is the Order of the Day of Daily Life

Here are a few examples of AI devices that lead you to a brighter future. Let’s have a look:

Virtual Personal Assistants

The world around you is full of smart digital personal assistants – Google Now, Siri and Cortana though available on numerous platforms, such as Android, Ios and Windows Mobile strives to seek meaningful information for you, once you ask for it using your voice.

In these apps, AI is the power giver. With the help of AI, they accumulate information and utilize that data to better understand your speech and provide you with favorable results that are tailor-made just for you.  

Smart cars

Do you fantasize about reading your favorite novel, while driving to office? Soon, it might be the reality! Google’s self-driving car project and Tesla “autopilot” characteristic are two latest innovations that have been stealing the limelight lately. In the beginning of this year, there was a report that, Google developed an algorithm that could potentially allow self-driving cars learn the basics of driving just like humans, i.e. through experience.

Fraud detection

Have you ever found mails asking if you have made any particular transaction using your credit card? Several banks send these kinds of emails to their customers to verify if they have purchased the same to avoid frauds being committed on your account. Artificial Intelligence is employed to check this sort of fraud.

Like humans, computers are also trained to identify fraudulent transactions based on the signs and indications a sample shows about a purchase.

Buying pattern prediction

Distinguished retailers, like Amazon do make a lot of money, as they anticipate the buyer’s needs beforehand. Their anticipatory shipping project sends you products even before you ask for them, saving you from the last-minute online shopping. If not online retailers, brick-and-mortar retailers also use the same concept to offer coupons; the kind of coupons distributed to the shoppers is decided by a predictive analytics algorithm.

Video games

Video games are one of the first consumers of AI, since the launch of the very first video games. However, over the years, the effectiveness and intricacies of AI has doubled, or even tripled, making video games more exciting, graphically and play wise. The characters have become more complex, and the nature of game-play now includes a number of objectives.

No matter, video games are framed on simple platforms, but as industry demand is burgeoning at an accelerating pace, a huge amount of money and effort are going into improving AI capabilities to make games more entertaining and downright exciting!

Fact: Artificial Intelligence is serving millions of people on earth today. Right from your smartphone to your bank account, car and even house, AI is everywhere. And it is indeed making a huge difference to all our lives.

To gain more knowledge on AI, enroll in Big Data Certification Gurgaon by DexLab Analytics. Their big data and data analytics training is of high quality and student-friendly. The prices of the course are also fairly convenient.

The blog has been sourced from – https://beebom.com/examples-of-artificial-intelligence

 

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How Data is Found Influencing Political Campaigns Online

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How Data is Found Influencing Political Campaigns Online

Data is and has always been the heart and blood of politics. In the 21st century, digital transformation has hit politics hard. Ambitious politicians and lobbyists invest hundreds of dollars on framing potential campaigns and agendas: in the past US presidential elections, as much as $5 billion dollars was spent, if not less, out of which estimated $1 billion was set aside for digital advertising alone.

Online information has already started weaving a change in perspective of people. They tend to manipulate us. Few are even of the notion that big data is being used to develop customized political advertising that challenges our rational minds and change our voting pattern. But do you think it’s true? Can data have that kind of intense impact?

Cambridge Analytica Data Breach

In the wake of Facebook and Cambridge Analytica data breach, where data of 50 million Facebook users were compromised, a compelling issue of data safety and protection has come to the forefront of our conscience. Cambridge Analytics is a British political consulting firm that works by integrating data mining, data analysis and brokerage with strategic communication for successful electoral processes.

A recent terrifying revelation suggested that this company has used Facebook users’ confidential data to predict personalities and then tailor personalized advertizing according to their psychological attributes. For years, this company has been performing data analysis services strategizing various presidential campaigns for US and UK. This March, the data analytics firm has been alleged to have harvested information from more than 50 million Facebook users without their knowledge to build a system for targeting US voters. The employees of the firm were also found boasting about using fake news, fabricated sex scandals and cheap tricks to swing electoral campaigns across the globe and this has created a big uproar in the industry.

From this, anyone can fathom the power of data in politics and framing opinions. Digital technologies have become a powerful tool for both positive and negative change. Technology remains remote, pivotal and paternalist. The political systems are changing, and so are we. That’s why it’s high time for all of us to be cautious, prudent and have a voice of our own.

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How to Enhance Online Campaign Success Legally

While social media scores high, email actually pulls the reigns, when it comes to raising funds for political campaigns online.

Mitt Romney’s 2012 campaign revealed about 70% donations came through emails.

During the Obama campaign, the figures were as high as 90% to be precise.

Besides raising funds online via email, integration of myriad digital marketing channels with smart data is crucial to rally in unconditional support on behalf of candidates.

Here are ways to boost your online campaign success:

  • Mobile ads – Increase relevancy for micro-targeted audience
  • Actionable TV – Using set-top-box information, particular demographics has to be targeted
  • Retargeting – Targeting should be focused on historical donors, interested in your policies
  • SEO decisions – Upload content suitable for the target audience and improve search rankings
  • Email messages – it would segment your lists while enhancing campaign results

To put simply, better data yields positive results for political campaigns, along with supporting fundraising, awareness and presence. However, remember, not all data is clean and safe and not all data providers are credible and honest. Watch the news, join the drive, but stay true to your opinions and insights. They will never fail you.

Get trained by the experts from DexLab Analytics on big data hadoop. It’s a premier data analytics training institute in Delhi NCR that offers incredible big data training to the students.

The article has been sourced from:

https://www.theguardian.com/commentisfree/2017/mar/06/big-data-cambridge-analytica-democracy

https://webbula.com/how-data-helps-political-campaigns-succeed

 

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How Big Data Will Impact E-commerce Industry in 2018?

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Whatever happens online and offline, it’s because of DATA. As the technology evolves, the ways to gather and measure data also diversifies. The best way to grasp the data world mechanisms is to study and analyze trends in behavior.

 
How Big Data Will Impact E-commerce Industry in 2018?
 

Big data is a concentrated accumulation of conventional and digital data from within and outside company operations. The inception of big data has enabled businesses to use huge amounts of data to carry out bigger and more complicated analyses.

 

However, the pressing issue that people face today is that they have “too much” data – collecting, organizing and understanding data has become quite complicated because we now are inundated with ceaseless numbers, percentages, stats, facts and perceptions.

 

To be precise, for years, Big Data has been buzzing around the digital front – let’s delve into what it actually means and what promises it holds in 2018 for ecommerce…

 

E-commerce industries are the biggest consumers of data. They can extract any information from Big Data and predict customer behavior and streamline robust operations.

Here are 4 ways in which big data will change the shape of e-commerce in 2018:

Better shopper analysis

For online success, understanding shopper’s behavior is more than important. Harness big data; it offers information on trends, customer choices and spikes in demands. It is the key to successful marketing.

 

Throughout this year and more, big data analytics will continue tracking shopper behaviors and fine-tuning your marketing strategies based on that.

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Flawless customer service

 Figures regarding dissatisfied customers and frail customer service are alarming. Truly speaking, more than 90% of unhappy customers won’t like to do business with a company that has turned their expectations down, owing to poor customer service. Therefore, for ecommerce success, utmost focus on customer service is downright important.

 

This year, expect data analytics to improve customer experience, while giving more focus to predictive monitoring. This will aid companies in identifying crucial issues and resolve them before even a customer gets involved.

More secure and easy online payment options

Since big data came into our lives, several things, like online payments got easier and more secure. How?

 

  • Big data incorporates various payment functions in a single centralized platform. It helps in making the process easier, as well as reduces fraud risks.
  • The advanced analytics are powerful enough to identify threats and structure proactive solutions to combat potent risks.
  • Big data helps in detecting money laundering transactions.
  • Productive data analytics allows e-commerce chains to cross sell and upsell.

Mobile commerce evolution

Day by day, the use of smartphones is increasing. The use of desktop computers is soon becoming obsolete. Big data is making impossible things possible, especially in the world of smartphones and ecommerce. Companies can now very easily gather data from multiple sources and analyze customer trends through mobile technology. Google has pioneered a wave of technologies, giving preference to mobile friendly and highly responsive sites. They bring in higher traffic to their pages. Hence an instant hit!

 

As closing thoughts, ecommerce companies wholeheartedly thanks Big Data for the way it has simplified the process of online shopping. For more big data inspiration and blogs, follow DexLab Analytics.

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Our advanced Big Data certification in Delhi NCR is excellent. Hone your skills with big data hadoop training and soar to success.

 
The article has been sourced from  –  http://dataconomy.com/2018/02/5-ways-big-data-analytics-will-impact-e-commerce-2018/
 

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If Big Data is the Problem, Then Hadoop is the Solution

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If Big Data is the Problem, Then Hadoop is the Solution

A lot of IT professionals and tech nerds are curious to learn about the difference between Big Data and Hadoop. A majority of them are yet to understand the subtle line of distinction between the two. And the increasing prominence and popularity of Big Data Hadoop certification has further added to the confusion.

Importantly, Big Data and Hadoop, the most popular open-source Hadoop program actually ends up complementing each other, in every way. If you think of Big Data as a problem then Hadoop acts like a solution for that problem – yes, they are that much compatible and complementary to each other. While big data is a dubious and complex concept, Hadoop being a simple, open source program that helps in fulfilling a certain creed of objectives of asset, in this case Big Data.

The best way to explain this issue would be by talking about the challenges associated with Big Data and how Hadoop efficiently resolves them – this would be the best way to know the differences between the two.

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Challenges with Big Data

Big Data is best defined with 5 characteristics: Volume, Variety, Velocity, Value and Veracity. Here, volume depicts the quantity of data, variety means the kind of data, velocity is the rate at which data is being generated, value points at the usefulness of the data and veracity is the amount of inconsistent data.

Now, let’s talk about two of the emerging problems with Big Data:

  • Storage – The archaic storage solutions are not adept enough to store such mammoth amount of data that is being generated every day. Moreover, the variety of data is different, thus the data needs to be stored separately for effective use.
  • Speed of accessing and processing data – Though the hard disk capacities have increased manifold, not much development has been done on the front of the speed of accessing or processing data.

But no more, you have to worry about all these issues, as Hadoop is here. It has effectively mitigated all the above-mentioned challenges and made big data powerful as a rock!

What is Hadoop?

Generally speaking, Hadoop is an open source programming platform – it helped big data to get stored in distributed environments so as to be processed in a parallel way. It is composed of two important elements – Hadoop Distributed File System (HDFS) and YARN (Yet Another Resource Negotiator), Hadoop’s processing unit.

Now, let’s see how Hadoop resolves the emerging big data challenges:

  • Storage – With the help of HDFS, Big Data can now be stored in a proper distributed manner. For that, datanode block is used, it’s an efficient storage solution and allows you to specify the size of every block in use. Additionally, it doesn’t only divides the data across different blocks but also replicated all the blocks on the data nodes, thus making way for better storage solution.
  • The speed of accessing and processing data – Instead of relying on traditional methodologies, Hadoop prefers moving processing to the data, which means the processing dynamo is moved across different slave nodes and parallel processing of data is carried on throughout the slave nodes. And the processed results are then shifted into a master node, where a mixing of data takes place and the response arising out of it is sent to the client.

Hence, you can see how big data and hadoop are related to each other, not like alternatives but like complements. So, to climb the ladder of success and be an ace developer or data scientist, Big Data Hadoop certification in Gurgaon is your go-to option. Get Big Data Hadoop certification today from DexLab Analytics.

 

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Incorporating Hadoop into Adobe Campaign for Advanced Segmentation and Personalization

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Big data is the new CRAZE. Reports suggest that investments in big data have surpassed $57 billion in 2017, and are expected to rise by 10% for the next three years.

Incorporating Hadoop into Adobe Campaign for Advanced Segmentation and Personalization

Customers are happy – those who have applied advanced capabilities to predictive analytics, machine learning, customer analytics, customer profiles, inventory management and tracking, and more – as big data implementation across many verticals has resulted in measurable positive results.

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10 Frequently-asked Hadoop Interview Questions with Answers

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10 Frequently-asked Hadoop Interview Questions with Answers

A substantial part of the Apache project, Hadoop is an open source, Java-based programming software framework that is used for storing data and running applications on different clusters of commodity hardware. Be it any kind of data, Hadoop acts as a massive storage unit backed by gargantuan processing power and an ability to tackle virtually countless tasks and jobs, simultaneously.

In this blogpost, we are going to discuss top 10 Hadoop interview questions – cracking these questions may help you bag the sexiest job of this decade.

What are the components of Hadoop?

There are 3 layers in Hadoop and they are as follows:

  • Storage layer (HDFS) – Also known as Hadoop Distributed File System, HDFS is responsible for storing various forms of data as blocks of information. It includes NameNode and DataNode.
  • Batch processing engine (MapReduce) – For parallel processing of large data sets across a standard Hadoop cluster, MapReduce is the key.
  • Resource management layer (YARN) – Yet Another Resource Negotiator is the powerful processing framework in Hadoop system that keeps a check on the resources.

Why is Hadoop streaming?

Hadoop distribution includes a generic application programming interface for drawing MapReduce jobs in programming languages like Ruby, Python, Perl, etc. and this is known as Hadoop streaming.

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What are the different modes to run Hadoop?

  • Local (standalone) Mode
  • Pseudo-Distributed Mode
  • Fully-Distributed Mode

How to restart Namenode?

Begin by clicking on stop-all.sh and then on start-all.sh

OR

Write sudo hdfs (then press enter), su-hdfs (then press enter), /etc/init.d/ha (then press enter) and finally /etc/init.d/Hadoop-0.20-name node start (then press enter).

How can you copy files between HDFS clusters?

Use multiple nodes and the distcp command to ensure smooth copying of files between HDFS clusters.

What do you mean by speculative execution in Hadoop?

In case, a node executes a task slower, the master node has the ability to start the same task on another node. As a result, the task that finishes off first will be accepted and the other one will be rejected. This entire procedure is known as “speculative execution”.

What is “WAL” in HBase?

Here, WAL stands for “Write Ahead Log (WAL)”, which is a file located in every Region Server across the distributed environment. It is mostly used to recover data sets in case of mishaps.

How to do a file system check in HDFS?

FSCK command is your to-go option to do file system check in HDFS. This command is extensively used to block locations or names or check overall health of any files.

Follow

hdfs fsck /dir/hadoop-test -files -blocks –locations

What sets apart an InputSplit from a Block?

A block divides the data, physically without taking into account the logical equations. This signifies you can posses a record that originated in one block and stretches over to another. On the other hand, InputSplit includes the logical boundaries of records, which are crucial too.

Why should you use Storm for Real-Time Processing?

  • Easy to operate – simple operating system makes it easy
  • Fast processing – it can process around 100 messages per second per node
  • Fault detection – it can easily detect faults and restarts functional attributes
  • Scores high on reliability – expect execution of each data unit at least for once
  • High scalability – it operates throughout clusters of machines


The article has been sourced from – www.besthadooptraining.in/blog/top-100-hadoop-interview-questions

 

Learn how Big Data Hadoop can help you manage your business data decisions from DexLab Analytics. We are a leading Big Data Hadoop training institute in Delhi NCR region offering industry standard big data related courses for data-aspiring candidates. 

 

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Flipkart Launches a New Internal Wing AIforIndia to Bet Big on Artificial Intelligence

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Flipkart is strengthening its base in the field of Artificial Intelligence, and so far, this year has been treating them well. After pegging fresh influx of funds, appointing a new CEO at the helm of affairs and reportedly thwarting its tailing rival, Amazon in September, Flipkart is all set to enter the most promising arena of artificial intelligence and machine learning, NOW.

 

Flipkart Launches a New Internal Wing AIforIndia to Bet Big on Artificial Intelligence

 

In an interview to a leading daily journal, Sachin Bansal, the notable co-founder and Chairman of Flipkart is found saying – “we ready to invest hundreds of millions of dollars” in the AI gambit over the next few years. “This is the next big thing for us, where we are betting big on the use of AI and machine learning to solve problems at Flipkart. India’s problems are unique and we need to apply AI in the ecosystem to solve Indian problems. We believe that some of the focus areas for AI in developed countries cannot be applied for India. At Flipkart, we will solve problems differently because the underlying problems (in India) are different,” he states, adding that they has already started building the needed infrastructure, recruiting a dozen AI buffs and establishing partnerships with crème de la crème educational institutions, including the IITs to give a robust push to its inspiring AI initiative.

Continue reading “Flipkart Launches a New Internal Wing AIforIndia to Bet Big on Artificial Intelligence”

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