Cognitive Computing At a Glance
Cognitive computing is a buzz which is being discussed among the IT industry for withholding the potential for a myriad of technical approaches related to data and open to self learn by understanding the meaning of it. The concept necessitates a computational model trained to learn a problem to simulate human thinking with the help of machine learning and deep learning. Relevant data in abundant amount is fed to the model with labeled output based on which the network learns a set of parameters. Neural networks which are the building blocks of deep learning act as the brain for the AI based cognitive computing; enabling it to extract valuable insights from data and resolve a problem. It utilizes voice recognition, natural language processing, data mining, sentiment analysis, visual recognition, and others to achieve the optimal human level of thinking.
Currently, cognitive computing has emerged and apart from software frameworks, structured and unstructured data toolkits, it requires high-performance hardware, flexible frameworks, cloud, and big data to burgeon in the industry.
High interest and investment in the technology is no sudden change, in fact, it is the need of the current era that is resulting in the constant evolution of the technology.
• Data Abundance and Internet: Availability of data in abundance plays a critical factor in making the AI smart. Enormous strewn data is available on the internet in the form of text, speech, visuals, and videos that are put to use for training the computing model. More the data, better the output is the main principle behind the training of the model. It also utilizes web tracking, cookies, online footprints, and massive databases for self-learning.
• Parallel Computing and Cheap Hardware: With the advancement, computing hardware has become cheaper, and parallel computing came into existence, proving to be boon for AI. Newly formulated chips specially designed to carry out heavy computational jobs are also acting as a helping hand to the same.
• Advanced Algorithms: Continuous research has made it possible to develop robust networks over which new algorithms could operate to tackle the data avalanche. Efforts in the direction are resulting in enhanced accuracy and performance of the neural networks.
In a nutshell, cognitive computing is an advanced layer of application of AI enabling machines to self learns and resolves problems based on their experiences. The ongoing technological ameliorations have made the rapid evolution of the technology possible.