Skip to main content

What is Artificial Intelligence,its type and applications


AI is a part of Computer Science.AI is anything that makes machine more intelligent. AI is a technology which can not replace human intelligence but rather it can extend human capabilities.Now a days AI is most wanted and powerful technology.Every industry wants to have its AI system because it can process very large amount of data in less time.

How does AI learn ?

The intelligence which machine having is only provided by us.So basically we provide to machine  ability to examine and create machine learning models based on inputs and desired output and we do this based on supervised learning,unsupervised learning and reinforcement learning.

Types of AI based on Strength

Weak or Narrow AI-

Narrow AI is that applied on specific domain.It can perform specific task but can not learn new things its own.It can only make decision based on programmed algorithms and trained data.For example AI powered based searches,virtual assistant,self driving cars,language translators and intelligent spam filters.

Strong and Generalized AI-

Strong is that can operate and interact wide variety and of independent and unrelated task.It can learn new task to solve new problems and can teach itself new strategies.Generalized AI is combination of many AI techniques that can perform human level of intelligence like It can learn from the past experiences as human does.

Super and conscious AI-

Super AI is that which can operate human level consciousness which would require to be self aware.
Because we are not able to define the exact level of consciousness.

Application of Artificial intelligence-

AI in Health care-
  • In last recent years AI has given lot of advantages to heath industry as diagnosis a disease faster than human.
AI in Natural Language Processing-
  • AI has enable computer to interact with human to under the Natural language of human beings.
  • Personal AI Assistant which can book a table in hotel for you and lot more.
AI in Robotics-
  • Robotics use the wide range of AI in Robot like Machine Learning,deep learning ,Natural language processing,Computer Vision,Face recognition and lot more.


Comments

  1. Hi Muzahid,
    Such an amazing article.
    It's interesting to read more about how AI can be used in the every industry.
    You would love to see my python course duration and fees in pune site as well.
    Thanks once again.

    ReplyDelete

Post a Comment

Popular posts from this blog

Can AI be dangerous

CAN AI BE DANGEROUS? Most researchers agree that a superintelligent AI is unlikely to exhibit human emotions like love or hate, and that there is no reason to expect AI to become intentionally benevolent or malevolent.  Instead, when considering how AI might become a risk, experts think two scenarios most likely: The AI is programmed to do something devastating:   Autonomous weapons are artificial intelligence systems that are programmed to kill. In the hands of the wrong person, these weapons could easily cause mass casualties. Moreover, an AI arms race could inadvertently lead to an AI war that also results in mass casualties. To avoid being thwarted by the enemy, these weapons would be designed to be extremely difficult to simply “turn off,” so humans could plausibly lose control of such a situation. This risk is one that’s present even with narrow AI, but grows as levels of AI intelligence and autonomy increase. The AI is programm...

What is deep learning and how it is improving the machine learning

While Machine Learning is a subset of Artificial Intelligence , Deep Learning is a specialized subset of Machine Learning . Deep Learning layers algorithms to create a Neural Network, an artificial replication of the structure and functionality of the brain, enabling AI systems to continuously learn on the job and improve the quality and accuracy of results. This is what enables these systems to learn from unstructured data such as photos, videos, and audio files. Deep Learning, for example, enables natural language understanding capabilities of AI systems, and allows them to work out the context and intent of what is being conveyed. Deep learning algorithms do not directly map input to output. Instead, they rely on several layers of processing units. Each layer passes its output to the next layer, which processes it and passes it to the next. The many layers is why it’s called deep learning. When creating deep learning algorithms,developers and engineers configure the number...