Future of Computer Scienceby PRAKASH UPRETI SOCIAL MEDIA MANAGER/ CONTENT
Today there are more computing devices in the world than humans. We all have seen the evolution of computers starting from the time when one or two computers serving the world, to more than one device serving each person on this earth today. Computer science had been expanding its wings with more and more processes being automated. From this graph of evolution have you ever tried to extrapolate the future trend of this branch of technology? What would be the shape of roles in software development in the future? Will there be a necessity for software developers to write code?
“This branch of science which had sprouted along with the birth of my generation seems to end by the end of our generation”, he said. “Explaining it in a broader sense, with a burgeoning number of software developers involved in developing sophisticated software, we would soon reach a saturation point. This is due to the present trend of developing plug-and-play modules, which make the development process more flexible and easier than the process a decade ago.” This means, from near future on-wards there would be a drastic fall in the requirement for the software developers to manually code the whole thing themselves. However, this wouldn’t stay for much longer. “With all the software written in place in the field of information technology, it would be a gargantuan task to process such huge chunks of data being generated”, he explained.
Data science would bring out a major breakthrough to fulfill the requirement of analyzing the data. All the current roles of software developers would be replaced by a data analyst and data scientist roles. “The data being analyzed would help in taking decisions more accurately. The value of an organization or a product will be evaluated based on the accuracy of the decisions they make. A future employee would come to the office, evaluates the data to be analyzed from the information traffic, makes some calculations and predicts the output. Even, the data from this outcome, in case of right prediction, would add up to the value of prediction and decision-making capability. They need not write any piece of code, they only have to change the parameters available on the screen with a correct estimate on a UI which will be very similar in a stock market environment. They’ll have a cut in their value, for every wrong prediction they make”, he envisioned.
When asked whether quantum computing would take the lead in creating out new opportunities in computer science, he replied “It would at least take a decade, for Quantum Computing to make a significant impact in everyday life. Even, then it would be developed to be driven by data in contrast to today’s model of software-driven computer. Today’s computer had to face this evolution as they were developed from the Von Newmann machines”.
“On the other end, devices would play an instrumental role in generating and transmitting this data. Real-time operating systems would enable us to get the real-time updates of each and every possible measurement. There would be huge opportunities for developing the devices that can communicate and act in real-time. Efficient energy monitoring and control systems would soon replace today’s human intervention systems. These computing systems will take the real-time decisions to eliminate the errors to the maximum possible extent.”
“Only Data science and Device-related jobs in computing domain would prevail in future making all the intermediate jobs disappear due to automation in place. There are plenty of opportunities available today for students to learn and improve their skills in these domains”.
“Today every new full stack idea one has ended up creating the core of idea very quickly as the core servers/glue logic and basic libraries are all available. Cloud caused some disruption for scale but the core remains same. What I see now (will definitely happen in the next 5 years) is a trend to use data and make the business run. More and more engineers get hired by Amazon/Flipkart for data analysis. Core platform companies are hiring to make platforms to make that learning/intelligence easy. Thanks to Google which proved with search we can solve AI problems. The hope of data science on such a large scale problem restored confidence to apply to many such problems. The other aspect I do see experiences. If you see where device companies are investing is how to make life easy for the end user be it voice, finger, eye movements and slowly you will see more senses will be added to them. But we are very far. I don’t know why I have to go and select 90% of same items in grocery shop every month. we are in the initial stages of applying data inferences. Very soon we will see more advanced use cases. The world will be very different in 2030.
Created on Jan 3rd 2019 03:35. Viewed 408 times.
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