AI – What It Can Do For You ?

Artificial Intelligence is that crucial category of computer science which relates to the technocracy of programming the computers to be as intelligent and as intuitive as humans are. AI is popularly defined as “Systems that think and act like humans”.

AI currently encompasses a huge variety of sub fields, ranging from general-purpose areas, such as learning and perception to such specific tasks as playing chess, proving mathematical theorems, writing poetry, and diagnosing diseases. AI systematizes and automates intellectual tasks and is therefore potentially relevant to any sphere of human intellectual activity. In this sense, it is truly a universal field.

  • We are doing the intelligent system engineering.
  • Designing the intelligence for best behavior, rational thinking, thought processes/ reasoning behavior.
  • Intelligent behavior includes the following.
  1. Perception
  2. Reasoning
  3. Learning
  4. Understanding languages
  5. Solving problems

Besides, from being phenomenal virtual assistants to fraud detection prerogatives to automation guides to a plethora of new utility avtars, Artificial Intelligence has been evolving for a range of useful solutions and reasons, at length.

Associated Risks And Limitations:

Clearly, machines are simply the machines and they are being instructed and programmed by humans about what to do and how to do and how to pass through the if-then statements and other loops. The range of applications which can be implemented with deep learning process is pretty vast and still data scientists argue that considerable number of them, are still uncovered by this method.

  • Unlike humans, machines are not (yet!) good storytellers
  • Machines know more than they can tell us
  • Machines may have hidden biases, derived not from any intent of the designer but from the data provided to train the system

While all the risks of AI and Machine Learning are very real, the appropriate benchmark is not perfection but the best available alternative.

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Clearly, machines are simply the machines and they are being instructed and programmed by humans about what to do and how to do and how to pass through the if-then statements and other loops. The range of applications which can be implemented with deep learning process is pretty vast and still data scientists argue that considerable number of them, are still uncovered by this method.

  • Unlike humans, machines are not (yet!) good storytellers
  • Machines know more than they can tell us
  • Machines may have hidden biases, derived not from any intent of the designer but from the data provided to train the system

While all the risks of AI and Machine Learning are very real, the appropriate benchmark is not perfection but the best available alternative.

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