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Research Areas Of AI


Shortly, how AI we use in daily life?
Artificial intelligence is the development of computer systems that are able to perform tasks that would require human intelligence.
Due to artificial intelligence, we had achieved success to solve the complex problems also by using intelligent machines. These machines can think, behave and act like humans. 
            AI making all life easy. There are many real life examples of AI that are we using daily, like self driving cars, Boston dynamics, navigation system, ASIMO, chatbots, computer games and many more.
        The brief study will we discuss about the research areas of AI. 

Gaming

AI plays crucial role in strategic games such as chess, poker, tic-tac-toe, etc., where 
machine can think of large number of possible positions based on heuristic knowledge. 




Natural Language Processing

It is possible to interact with the computer that understands natural language spoken 
by humans. 





Expert Systems

There are some applications which integrate machine, software, and special 
information to impart reasoning and advising. They provide explanation and advice to 
the users. 





Vision Systems

These systems understand, interpret, and comprehend visual input on the computer.
For example, 
1) spying aeroplane takes photographs which are used to figure out spatial 
information or map of the areas.
2)  Doctors use clinical expert system to diagnose the patient.
3) policeu computer software that can recognize the face of criminal with the
stored portrait made by forensic artist.




Speech Recognition

Intelligent Systems are capable of hearing and comprehending the language in 
terms of sentences and their meanings while a human talks to it. It can handle different 
accents, slang words, noise in the background, change in human’s noise due to cold,
etc. 




 Handwriting Recognition

handwriting recognition software reads the text written on paper by a pen or on 
screen by a stylus. It can recognize the shapes of the letters and convert it into editable 
text.





Intelligent Robots

Robots are able to perform the tasks given by a human. They have sensors to detect 
physical data from the real world such as light, heat, temperature, movement, sound, 
bump, and pressure. They have efficient processors, multiple sensors and huge 
memory, to exhibit intelligence. In addition, they are capable of learning from their 
mistakes and they can adapt to the new environment





Artificial Intelligence in movies 

In movies, robots are able to talk, think, have emotions, and make decisions just like humans.





Real Life A.I. Examples



❏ Self Driving Cars
❏ Boston Dynamics
❏ Navigation 
Systems
❏ ASIMO
❏ Chatbots
❏ Human vs 
Computer Games
❏ Many More!


ARTIFICIAL INTELLIGENCE EXAMPLES

  • Smart assistants (like Siri  and Alexa)
  • Disease mapping and prediction tools
  • Manufacturing and drone robots
  • Optimized, personalized healthcare treatment recommendations
  • Conversational bots for marketing and customer service
  • Robo-advisors for stock trading
  • Spam filters on email
  • Social media monitoring tools for dangerous content or false news
  • Song or TV show recommendations from Spotify and Netflix


Health Care 
AI applications can provide personalized medicine and X-ray readings. Personal health care assistants can act as life coaches, reminding you to take your pills, exercise or eat healthier.




Retail 

AI provides virtual shopping capabilities that offer personalized recommendations and discuss purchase options with the consumer. Stock management and site layout technologies will also be improved with AI.



Manufacturing

AI can analyze factory IoT data as it streams from connected equipment to forecast expected load and demand using recurrent networks, a specific type of deep learning network used with sequence data.   



Banking

Artificial intelligence enhances the speed, precision and effectiveness of human efforts. In financial institutions, AI techniques can be used to identify which transactions are likely to be fraudulent, adopt fast and accurate credit scoring, as well as automate manually intense data management tasks.



Cancer Screening

Artificial intelligence, powered by deep learning algorithms is already in use in healthcare. Specifically, AI’s imaging capabilities are promising for cancer identification and screening, including breast cancer. Artificial intelligence is also used to predict the development of diseases across a healthcare network. A group at Mount Sinai used deep learning-based AI algorithms to predict the development of diseases with 94% accuracy, including cancers of liver, rectum, and prostate. Thanks to published cancer research, clinical trials, and drug development.





Machine Learning

Machine learning involves the use of Artificial Intelligence to enable machines to learn a task from experience without programming them specifically about that task. (In short, Machines learn automatically without human hand holding!!!) This process starts with feeding them good quality data and then training the machines by building various machine learning models using the data and different algorithms. The choice of algorithms depends on what type of data do we have and what kind of task we are trying to automate.




Internet of Things

Artificial intelligence deals with the creation of systems that can learn to emulate human tasks using their prior experience and without any manual intervention. Internet of things, on the other hand, is a network of various devices that are connected over the internet and they can collect and exchange data with each other.

Now, all these IoT devices generate a lot of data that needs to be collected and mined for actionable results. This is where Artificial Intelligence comes into the picture.





 Computer vision

 Computer Vision uses Artificial Intelligence to extract information from images. This information can be object detection in the image, identification of image content to group various images together, etc. An application of computer vision is navigation for autonomous vehicles by analyzing images of surroundings





Deep Learning.

Deep Learning uses artificial neural networks to implement machine learning. These neural networks are connected in a web-like structure like the networks in the human brain (Basically a simplified version of our brain!).
This web-like structure of artificial neural networks means that they are able to process data in a nonlinear approach which is a significant advantage over traditional algorithms that can only process data in a linear approach.









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