Why I'm planning to pursue research and studies

The future of digital environment is shifting towards inducing the intelligence to the hardware and transforming the inducted algorithm to newer levels. The evolution of technology has influence on the growth of the learning models. Defining intelligence for machine is an interesting problem.

Problem solving with reasoning is the logical capacity of individual that defines the intelligence. With the events in life, human learns and builds the self-awareness. Using the same context, for machines, the events that are happening while processing an algorithm must be recorded for further analysis and learning purpose. These events produce data and with time, the data grows enormously. To process this huge quantity of data, it is important to have high computational capacity for the machine. Along with this, the storage capacity should also be spanning to exponential levels. This solves the purpose of processing power and the storage, but, not the logical learning and collective processing of multiple algorithms at parallel.

Humans explore unknown horizons. This kind of ability is not yet base-lined by scientists. Hence, the abilities that were base-lined were given attention towards inducting to machines for better results. Scientists have produced algorithm for detecting deadly cancer with 86% accuracy is a example for such limited scope of related data.

Thus, we need a baseline data set and the characteristics exposed by these data elements within. It is very much important to categorize these characteristics and identify the algorithms, that get influenced by them. Hence, the need of the situation is to build the bridge between the inception of the data point and the collection of the data points that are continuously exposing a similar characteristic behavior.


With this thought process, I would like to pursue my research in algorithms as well as the evolving learning mechanisms.
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