A conventional computingcould only operate within the framework that were programmed into it. It couldhave all the processor speed and memory, but the code would be what softwaredesigners and users have produced whereas an intelligent computing would, muchlike humans, make decisions solely on it`s own. It would be able to learn andin essence, constantly reprogram itself.
It would be able to make decisionsbased on a more ethical or moral, not a programmed factual manner. Conventionalcomputing can’t explain arguments and its system is made of algorithms and datastructure whereas intelligent computing systems have ability to explainarguments and compose of interrogative and assumption engine with knowledgebase. If a solution is accurate, perceived and fully optimized in an efficient time, then we can conclude that a given solution is intelligent. For example, Surveillanceis a real life example of intelligent solution.
It is one of the oldest and most common practices withininvestigative services, yet it remains the best option in cases when real-timeinformation is required. Real-time information gathered via surveillanceleads in making preventative decisions and more reliable than other methods ofinvestigation because of its accuracy and optimized solutions. Obviously, the solution provided by a learning agent is differentand intelligent to that of utility agent. Sometimes achieving the desired goal is not enough. We maylook for quicker, safer, cheaper way to reach the goal. Because of the uncertainty in theworld, a utility agent choses the action that maximizes the expected utilitybut a learning agent is responsible for selecting external actions and allowsthe agent to explore.
A learning agent perceives its environment through perceptand acts through actuators. Applications of intelligentcomputing expand across different areas, such as business, healthcare, environmental protection, security, entertainment, and social activities. The advancement of cloud computing, pervasive computing and social computing are bringing intelligent computing toa newer dimension and improving our ways of living.· Forexample, Flying drones are the best real life example of intelligent computing. The flying drones are already shipping productsto customers home – though on a test mode. It consists of a powerfulmachine learning system that can translate the environment into a 3D modelthrough sensors and video cameras.
So, after all thistechnical aspects, we came on the conclusion that intelligent computing is gaining popularity at a quicker pace; influencing the way we live, interact and improve user experience. So, intelligent computing is much more efficient and better than conventionalcomputing.
