List of 4 critical questions on AI that can be asked in the interview.

                                                                 

This page contains the answer to the following question-related to AI, IT, Data Science, Deep Learning, 3D reservoir, and BigData

1. What are some examples of artificial intelligence that we started using in daily life?

2. What is the difference between information technology and data science?

3. What is the application of machine learning and deep learning in geostatistics for 3D reservoir property prediction?

4. Will big data change history?

1.What are some examples of artificial intelligence that we started using in daily life?

Ans:

One of the very relevant examples may be that every time you ask some questions on quora. After asking the question, after some time you will find that similar relevant questions and answers used to get popped up in your email(if you are using Gmail then you might find it very frequently). This technology is called analytics. A similar phenomenon happens when you search for some book on Amazon or search for booking flight tickets to make my trip websites. In fact, not only that eCommerce companies may build a portfolio of yours based on your frequent search topics. Data analytics may be an utter example of AI that we encounter daily, however, do we concentrate or bother on these small things that shall remain as a big question?

2. What is the difference between information technology and data science?

Ans:

As the name suggests that it is “Data Science”. That means it is a science that is applied or related to data. Now if you go by the Wikipedia definition of information technology: it says that Information technology is the use of computers to store, retrieve, transmit, and manipulate data. It is more about the usage of computers in different ways. It never says anything about the data or the nature of the data or how to find similar patterns inside the data or any kind of patterns; meaning is IT never says about the nature of the data(if the data is an image or normal data), whereas data science put emphasis on the nature of the data if it is an imbalance, prediction on data, clustering or classifying the data and many other things. Henceforth, these two terminologies are different in nature, however, one can not ignore IT also, without IT(meaning without computers) how can we work upon data?

3. What is the application of machine learning and deep learning in geostatistics for 3D  reservoir property prediction?

Ans: 

Geostatistics does improvement towards the prediction by designing variants of models that are static by nature. It uses techniques that do not average important reservoir properties to produce a better realistic geological model of the reservoir. However, doing any kind of analysis which is based on the reservoir is extremely difficult as the images such as SAR or any other hyperspectral images do not help to get a proper reflection of the water pixel from the reservoir. However, deep learning especially deep CNN seems to be a good choice for even 3D nature of the reservoir.

4. Will big data change history?

Ans: 

Yes, off course. What will happen in the future is that the significance of the conventional subjects will be meaningless as the data is getting bigger and bigger, subjects such as Data Structure and Algorithms, DBMS shall to some extent be obsolete(incoming future). So much of huge data is available now that nobody is even bothering about the time complexity or space complexity of a newly developed algorithm. Therefore, the subject like NoSql will be more popular day by day. Big data is the reality now, and dealing with a small amount of data is becoming out of the scope gradually. Computer engineers no longer finding fascinating in writing SQL queries, rather they are interested to deal with huge data i.e big data, and instead of SQL it is now NoSQL attracts them more! Thanks to the BIGDATA! Moreover, AI, ML, and DL have given more spice to this changing story of paradigm shift.

~AISavvy