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Impact of Artificial Intelligence in the IT Industry



One of the most significant events in human history is the creation of Artificial Intelligence (AI). While 15 % of enterprises are already using AI, 31 % claim they will be using it within a year. Not only AI transforms traditional computer methods but also has an impact on various industries.

The most affected industry, of course, is Information Technology. IT industry is all about systems and software, which makes Artificial Intelligence relatively more important in this sector. Before discussing the impact of AI in Information Technology, let’s first know what exactly Artificial Intelligence is?


What is Artificial Intelligence?

Artificial Intelligence is the creation of intelligent machines that act and function like humans. In this technology, the machines based perform the cognitive functions of humans like problem-solving and learning. There are three different classifications of AI: analytical, human-inspired, and humanized Artificial Intelligence.

Artificial Intelligence works on algorithms and computer-based training that help solve complicated problems develop stimulations by learning in machines. The goals of Artificial Intelligence include:

  • Reasoning

  • Planning and learning

  • Processing

  • Moving the objects based on learning

In the IT industry, Artificial Intelligence is changing the way software, and programs are developed. The software thus created not only solves a problem but also learns from the experience for future applications.


Impact of AI in Various Sectors of the IT Industry

Information Technology is using computer systems for storage, transmission, and processing of any data for any enterprise or organization. So Artificial Intelligence impacts information technology industry in many ways. Be it using voice recognition and virtual assistants or automating a work without human intervention, Artificial Intelligence is everywhere in this industry.

Here are some of the major sectors of IT and the impact of Artificial Intelligence on them:

Secure Systems

Confidential data is valuable to any organization and breach in this security system might cost a lot, especially to government organizations. Artificial Intelligence uses various algorithms to create layers of security within systems. AI defends not only the system of any potential threat but also repairs and learns from errors or vulnerabilities to protect the data from any future risk.


It is estimated that by the year 2025, AI and automation will replace 7 % of jobs in the US itself. Automation carries out any type or amount of work without human interference.

Organizations are adopting automation at a fast rate as it is cost effective. The AI algorithm based automation adjusts according to the company needs and also learns from past errors.


Coding for programmers is a tricky business and requires a lot of hit and runs. Artificial Intelligence provides suggestions to coders, ultimately increasing productivity and reduces the downtime.

Processing Power

Computers have improved and advanced since the time they first came into action. Artificial Intelligence not only increases the processing speed but also handle data like a human brain.

Quality Assurance

Quality Assurance is the use of accurate tools in the development of software. By using AI tools, the developers can fix issues and prepare them for future bugs or fixes. One such example of an Artificial Intelligence tool is ‘Bugspots’ that is effective in removing viruses without the help of humans.



Artificial Intelligence is the recent critical development in the Information Technology Industry. It helps create more reliable software and programs which are cost-efficient and error-free. Developers have used AI in carrying out the most complex operations and expand their range of vision. Both based on computer science, Artificial Intelligence and Information Technology, go hand in hand in making changes in the operation of various sectors including programming, planning, quality assurance, productivity, and automation. We can enhance machine and human capabilities using AI in Information Technology.

Here are Top 10 Reasons You Should Learn Artificial Intelligence



Artificial Intelligence has revolutionized the way people think, learn, and work in various fields, from finance to healthcare and mobile apps. What’s more interesting is that Artificial Intelligence plays more role in our daily lives than we can imagine. From Siri and Google Assistant to various virtual player games and social media apps, Artificial Intelligence is everywhere. It sure is the most happening topic in every business right now. It is the most wanted and exciting career domain right now in the market. Let us know what Artificial Intelligence is.


What is Artificial Intelligence?

Artificial Intelligence (AI) uses intelligent machines built in a way that they react like humans. The primary process involved in making these smart machines is to carry out decision making, which analysis and uses data available in an enterprise. It is similar to the human mind absorbing and synthesizing information and providing with the required decision.


Reasons for You to Learn AI

Here are ten reasons to learn Artificial Intelligence:

1. Better Career Opportunities

According to a report by Tractica Report, Services based on Artificial Intelligence were worth $1.9 billion in 2016. Every industry is trying to apply Artificial Intelligence in their company. It opens a lot of doors for aspirants who can develop and operate Artificial Intelligence. It is used in cyber security, medicine, applications, and face recognition.

In an announcement by Netflix, it was stated that they would provide with 1 million dollars to the first person who can enhance the accuracy of its ML algorithm.

2. Use in Healthcare Industry

The implementation of machines and computers has reduced the need to be in person all the time. Artificial Intelligence helps in analyzing the vitals and records of the patient and produces a personalized treatment so that the doctor can quickly review and implement it.

3. Mobile Applications

A mobile phone is not just for call and messages now. It is a combination of tasks and applications which were earlier performed in a more complex manner. From digital wallets to personal assistants like Siri and Google Assistant, mobile apps can carry out everything you ask. Siri is one of the top examples of using Artificial Intelligence in mobile applications.

4. Detecting Fraud

You must have noticed a message popping on your screen whenever you withdraw some amount from your bank account confirming that if it was you. It is a part of transaction monitoring, which is further done using Artificial Intelligence.

5. Link to Data Science

Artificial Intelligence is based on data science. With machine learning, you can choose both the engineering job and data scientist job. Mastering both increases your demand in the industry. It means you can analyze the data as well as using this information to train a model for prediction of results.

6. Online Customer Support

Nobody these days has the time and patience to wait and interact on a call with an actual person. With the introduction of Artificial Intelligence in customer support, consumers can interact with chatbots 24 * 7 without actually getting on the call.

7. Automobile Industry

The future of the automobile industry is entirely based on self-driving cars and autopilots. As surreal as it sounds, various cars have already done several test runs, and the technology is soon to hit the road.

8. Recommendations

Many applications recommend songs and movies according to your search histories and interests based on the same genre or artist. Even the ads you see on various social networking sites are based on your browsing history.

9. Lack of Skills

In a report in the New York Times, it is estimated that less than 10,000 people in the world have the skills and knowledge required to carry out Artificial Intelligence jobs. The less competition sure makes it a happening career option.

10. Rising Opportunities

Indeed reports that the number of Artificial Intelligence-related job opportunities outranked the number of searches for AI engineer jobs. In Bengaluru alone, the requirement for AI engineer exceeds 4000.

With increasing opportunities and using Artificial Intelligence in each sphere of life, the learning of this technology is more beneficial than we all think.

5-Step will Guide You to Start A Career in Artificial Intelligence In 2019



Artificial Intelligence can launch your career to the highest heights. In 2019, If you’re seeking for anything successful, then this one is worth a try, as well as counteracting your love towards the science of artificial intelligence. If you have the capability of adding information to the machines, just like humans, then you must look after choosing it as your career option. Artificial Intelligence has a huge role to play in the field of Computer Science. It advances the technology and also can ease up a lot of work as per the demand of human beings.

What trends in the year 2019 is the scope of Artificial Intelligence in mechanical, as well as in the automobile industries. You can put AI in the place of essential building blocks, while moving forward in your career, along with the jumpstart.


5 – Step Guide for Artificial Intelligence as a Career


1. Try to understand the background of AI career.

If you want to choose Artificial Intelligence over anything else, then you must check upon its background and the essential ideas before getting into its career.

Statistics show that this industry keeps on growing as the years pass by and plays a critical factor in enhancing the economy. You can explore through many types of viable opportunities in this field, which ensures growth even if it is in small amounts. No doubt that an optimistic enthusiast can scratch the best out of the career in Artificial Intelligence.

2. Learn about the excellent jobs in the field of Artificial Intelligence.

Plenty of job platforms combine to form the sector of Artificial Intelligence. The most popular ones include – Data scientist, Robotic scientist, Research Scientist, Machine Learning Engineer, and Business Intelligence Developer.

The scientists in this field require specific educational expertise, which will lead them towards a variety of developmental studies. A BI Developer’s job is to plan the solutions for the company and its data regarding the business. Whereas, a Machine Learning Engineer is someone who has proficiency in handling all the software skills and implementation of knowledge on them.

3. You must be wise about the knowledge as the prerequisites.

Before going into the profound insights of Artificial Intelligence, you must know about the subjects required for building a strong base of conceptual knowledge. The topics are that need proficiency are –

  • Engineering physics and Robotics

  • Mathematics (including all the calculus, probability, algorithms, algebra, statistics and probability)

  • Cognitive theory of science

  • Computer Science (including expertise in the widely used programming languages)

Apart from proficiency in these subjects, one requires some excellent communication skills to enter in the field of Artificial Intelligence. Excellent communication will help you in working in different industries.

4. Use online resources to learn more about AI.

Staying updated regarding your career choice is more important than learning and collecting knowledge about it. Online resources are the fastest mediums that can keep you updated about the latest technologies and more about other platforms in Artificial Intelligence.

Finding topics with the help of search engines like Google, Bing, etc. can be very useful in learning the best out of social media. There are many online courses available online that can help you in chasing your betterment in the field. You can find them free and in the paid category too.

5. Search for jobs with the help of Online job searching platforms.

After you develop all your skills and achieve a complete knowledge along with research about Artificial Intelligence, then you are all set for working in this sector.

Start searching for appropriate and desired jobs of your choice with the help of online job searching platforms and extract the best out of them. You should deal with patience at this step, as you’re still a newbie and need proficiency in your job. Try to learn more in every step further, and stay aware of fraud websites and stuff that employ you. Extensive research is highly essential.


A robust knowledge is a key to success if you choose your career in Artificial Intelligence. Having good hold in the required subjects and lead you towards strong conceptual understanding and research along with self-induced practice will lead you towards vast practical knowledge. There is no shortage of highly recognized jobs in AI. It is undoubtedly one among the plenty of career options that can give you immense growth and success in 2019.

Know About Automation of Artificial Intelligence & AI Revolution

Know About Automation of Artificial Intelligence & AI Revolution


Since last year, Artificial Intelligence (AI) has expanded and improved various technologies. AI has transformed multiple industries with a vast variety of applications. Artificial Intelligence also contributes to economic growth and productivity of multiple enterprises. The technology has removed the gap between machines and domain knowledge.

While the demand for skills of production of such machines from scratch is high, there is comparatively less number of businesses that are capable of building these models.

Ruchir Puri, in his keynote, discussed the automation of Artificial Intelligence, which means automating the tasks to build, deploy, and manage and the revolution of Artificial Intelligence, which is accelerating with each passing moment.


What is Automation of Artificial Intelligence?

While Artificial Intelligence has changed the way a lot of work is done in various industries through automation, there are still some functions that require human touch for their operation and learning.

Automated Artificial Intelligence changes the way we need various data scientists and professionals to sought day to day actions and makes it easier to use machines.

The building and handling of these machines are systematically carried out on raw data and makes the accessibility of data science across the organization easy.


Why do we need Automated Artificial Intelligence?

Construction of an Artificial Intelligence model requires domain knowledge, expertise in mathematics and computer and coding skills, which is way more than to expect from a single organization.

Apart from this, there is a constant chance of human errors, which affects the accuracy of the model. Automated AI uses the knowledge of various data scientists and helps improvise data science investments.

Artificial Intelligence and automation combines the mathematics and computer coding areas of the model and combines to form a single unit.

Automation of Artificial Intelligence helps the use of this technology in various industries, including banking, healthcare, marketing, fintech, and many more, which was earlier constricted to big enterprises with large amounts of resources.

Automation of these tasks helps organizations to deploy and manage the solutions quickly and help free up precious time of data scientists which they can use for more complex tasks.


Artificial Intelligence Automation includes three things:

  • AI designing AI

  • AI Optimizing AI

  • AI correcting AI

Let’s know about each one in detail.

AI Designing AI

Many highly skilled data scientists are needed to build these custom neural networks, which is both time-consuming and can cause errors. So the new area is the designing of neural networks automatically, which are more accurate and does not require any coding. With this, you can also optimize the model to evaluate its neural network accordingly.

AI Optimizing AI

The optimization of AI needs not just expertise in the field and knowledge of coding but also a significant amount of time spend on trial and error. The technology of AI optimizing AI, however, is based on learning patterns between data classification and transformation, exploration and combining intelligent enumeration and selection of features. It helps in automation of the task of trial and error, which is the most time consuming of all.

AI Correcting AI

This best can be explained through an example. Suppose you prepared a dish using all the right ingredients but forgot one or used the wrong one. Now, in the long run, you’ve to remake the whole meal to get the required results. But the situation can also be handled by just putting in the forgotten ingredient without compromising the taste. AI correcting AI works on the same principle. It fixes the problem without compromising with accuracy.


Automation of Artificial Intelligence has helped in a lot of ways from making the model error free to freeing up data scientists time. It has also helped carry out the most challenging task of trial and error by optimization. Through the automation of AI, real-time models can also be corrected without compromising with accuracy. So automation of AI sure is a trigger in revolutionizing the technology.


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The World Wide Influence of AI Technology Across Various Industries

The World Wide Influence of AI Technology Across Various Industries

Artificial intelligence (AI) is now having a transformative effect over each industry. From helping organizations predict issues that may occur in advance. There is a great opportunity for AI to expand human abilities across industries while benefiting on unique human capacities for creativity and quickness.

Let us interact with some interesting facts where AI is applied and used on a day-to-day basis.



AI can be utilized to examine electronic health records for patients and after that distinguish patients with high risk. These patients can then be organized to give palliative care services.

Another section is in the field of determination of different diseases. Despite the fact that this may not be a perfect replacement to the trained doctor/radiologist.AI can help to define threat in analytic reports thereby assisting in the treatment.

Another case where AI is widely adopted is in diagnosing diabetic retinopathy. In these situations, the AI system analyses retina images and after that decides the possibility of having diabetic retinopathy. This can especially be helpful in remote regions where medical service is missing.

One interesting aspect is anticipating health risks by looking at separate signals. This was specially grown recently in which a new algorithm can predict heart disease chance by looking at retina pictures.



In the manufacturing field, AI can accelerate tasks and improve productivity. Where this is currently done with people at a very slow rate. Example of this is checking the circuit board for errors manually. AI can be prepared such as it automatically execute verification and then detect broken circuit boards.

Usually, in the manufacturing process, there might be different steps before a final product is designed. In order to find any wrong step, we need to wait for the finished product and it has to be tested. This might be an awkward procedure and there may be wastage. AI can be trained to predict the wrong step in the complete manufacturing process before, which helps in saving time and decreasing wastage.



AI systems are rapidly utilized in ridesharing administrations and other transportation systems to analyze and predict the formation of vehicles, estimate trip price, determine optimized route etc. For customers.

AI systems are extremely used in self-driving vehicles. These systems are widely used in object detection, lane detection, building models of the surroundings from sensor signals among others.


Retail & Ecommerce:

In retail systems, AI systems are generally used to enhance the area of various products, anticipate customer conduct for obtaining products among others to improve the business.

AI systems are broadly utilized in guiding various products in E-commerce stages. These are additionally used to anticipate customer beat and in this way determine customer engagement in various E-commerce platforms.


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What is the difference between Big Data and Hadoop

What is the difference between Big Data and Hadoop

Many of Informational Technology professionals and technical school nerds are unit curious to gain knowledge on differencebetween Hadoop and Big Data. Majority of them area unit nonetheless to grasp the delicate line of distinction between the 2 and also theincreasing prominence and recognition of big data Hadoop certification has more additional to the confusion.

Importantly, big data and Hadoop, the foremost in style ASCII text file Hadoop program really winds up complementing one another, in each manner. If you’re thinking that of big data as drawbackthen Hadoop acts sort of a resolution for that problem – affirmative, they’re that abundant compatible and complementary to every different. Whereas big data could be a dubious and complicated thought, Hadoop being a straightforward, open computer programme that helps in fulfilling a precise creed of objectives of quality, during this case big data.

The best thanks to justify this issue would be by talking regarding the challenges related to big data and the way Hadoop with efficiency resolves them – this is able to be the simplest thanks to recognize the variations ;between the 2.

Challenges with Big Data

Big Data is best characterized with 5 attributes: Volume, Variety, Velocity, Value and Veracity. Here, volume portrays the amount of data, assortment implies the sort of data, and speed is the rate at which data is being created, esteem focuses at the handiness of the data and veracity is the measure of conflicting data.

Presently, we should discuss two of the rising issues with Big Data:

  • Storage – The ancient stockpiling arrangements are not sufficiently proficient to store such mammoth measure of data that is being created each day. Also, the assortment of data is extraordinary, along these lines the data should be put away independently for powerful utilize.
  • Speed of getting to and handling data – Though the hard plate limits have expanded complex, very little improvement has been done on the front of the speed of getting to or preparing data.

Be that as it may, no more, you need to stress over every one of these issues, as Hadoop is here. It has adequately relieved all the previously mentioned challenges and made big data ground-breaking as a stone!

What is Hadoop?

Hadoop is an open source programming stage – it helped big data to get put away in conveyed situations in order to be handled parallelly. It is made out of two vital components – Hadoop Distributed File System (HDFS) and YARN (Yet another Resource Negotiator), Hadoop’s handling unit.

Presently, how about we perceive how Hadoop settle the rising big data challenges:

  • Storage – With the assistance of HDFS, Big Data would now be able to be put away in a legitimate circulated way. For that, data node square is utilized, it’s an effective stockpiling arrangement and enables you to indicate the extent of each square being used. Furthermore, it doesn’t just partitions the data crosswise over various squares yet additionally repeated every one of the squares on the data hubs, in this way clearing a path for better stockpiling arrangement.
  • The speed of getting to and handling data – Instead of depending on customary philosophies, Hadoopfavors moving preparing to the data, which implies the preparing dynamo is moved crosswise over various slave hubs and parallel handling of data is carried on all through the slave hubs. What’s more, the prepared outcomes are then moved into an ace hub, where a blending of data happens and the reaction emerging out of it is sent to the customer.

Consequently, you can perceive how big data and hadoop are identified with each, dislike options but rather like supplements. Along these lines, to climb the step of progress and be a pro engineer or data researcher, Big Data Hadoop accreditation in Gurgaon is your go-to alternative. Get Big Data Hadoop confirmation today from DexLab Analytics.