7.1 Concept of Artificial Intelligence (AI) and Robotics
Artificial intelligence (A)
refers to the simulation of human intelligence in machines that are programmed
to think like humans and mimic their actions. The term may also be applied to
any machine that exhibits traits associated with a human mind such as learning
and problem-solving .
The ideal characteristic of
artificial intelligence is its ability to rationalize and take actions that
have the best chance of achieving a specific goal. A subset of artificial
intelligence is machine learning, which refers to the concept that computer
programs can automatically learn from and adapt to new data without being
assisted by humans. Deep learning techniques enable this automatic learning
through the absorption of huge amounts of unstructured data such as text,
images, or video.
·
Artificial intelligence refers to the simulation
of human intelligence in machines.
·
The goals of artificial intelligence include
learning, reasoning, and perception.
·
Al is being used across different industries
including finance and healthcare.
·
Weak Al tends to be simple and single-task
oriented, while strong Al carries on tasks that are more complex and
human-like.
To understand
How Artificial Intelligence actually works, one needs to deep dive into the
various sub domains of Artificial Intelligence and understand how those domains
could be applied into the various fields of the industry.
Machine
Learning: ML. teaches a machine how to make inferences and decisions based
on past experience. It identifies patterns, analyses past data to infer the
meaning of these data points to reach a possible conclusion without having to
involve human experience. This automation to reach conclusions by evaluating
data, saves a human time for businesses and helps them make a better decision.
Deep
Learning: Deep Learning is an ML. technique. Is teaches a machine to
process inputs through layers in order to classify, infer and predict the
outcome >Neural Networks: Neural Networks work on the similar principles as
of Human Neural cells. They are a series of algorithms that captures the
relationship between various underlying variables and processes the data as a
human brain does
Natural
Language Processing: NLP is a science of reading, understanding,
interpreting a language by a machine. Once a machine understands what the user
intends to communicate, it responds accordingly.
Computer
Vision: Computer vision algorithms try to understand an image by breaking down
an image and studying different parts of the objects. This helps the machine classify
and learn from a set of images, to make a better output decision based on previous
observations.
Cognitive
Computing: Cognitive computing algorithms try to mimic a human brain by
analyzing text/speech/images/objects in a manner that a human does and tries to
give the desired output.
Advantages:
·
Reduction in human error
·
Available 24×7
·
Helps in repetitive work
·
Digital assistance
·
Faster decisions
·
Rational Decision Maker
·
Medical applications
·
Improves Security
·
Efficient Communication
Disadvantages:
High Cost: The hardware
and software requirement of AI is very costly as it requires lots of
maintenance to meet current world requirements.
Can't think out of the box:
Even we are making smarter machines with Al, but still they cannot work out of
the box, as the robot will only do that work for which they its trained, or programmed.
No feelings and emotions:
At machines can be an outstanding performer, but still is does not have the
feeling so it cannot make any kind of emotional attachment with human, and may
sometime be harmful for users if the proper care is not taken.
Increase dependency on
machines: With the increment of technology, people are getting more
dependent on devices and hence they are losing their mental capabilities. No
Original Creativity: As humans are so creative and can imagine some new ideas
but still Al machines cannot beat this power of human intelligence and cannot
be creative and imaginative
Applications:
Astronomy: Artificial
Intelligence can be very useful to solve complex universe problems. Al
technology can be helpful for understanding the universe such as how it works,
origin, etc.
Healthcare: Healthcare
Industries are applying Al to make a better and faster diagnosis than humans.
Al can help doctors with diagnoses and can inform when patients are worsening
so that medical help can reach to the patient before hospitalization.
Gaming: Al can be used for
gaming purpose. The Al machines can play strategic games like chess, where the
machine needs to think of a large number of possible places.
Finance: Al and finance
industries are the best matches for each other. The finance industry is
implementing automation, Chabot, adaptive intelligence, algorithm trading. and
machine learning into financial processes.
Data Security: The
security of data is crucial for every company and cyber-attacks are growing
very rapidly in the digital world. Al can be used to make your data more safe
and secure. Some examples such as AEG bot, A12 Platform, are used to determine
software bug and cyber-attacks in a better way.
Social Media: Social Media
sites such as Facebook, Twitter, and Snap chat contain billions of user
profiles, which need to be stored and managed in a very efficient way. Al can
organize and manage massive amounts of data. Al can analyze lots of data to
identify the latest trends, hash tag, and requirement of different users.
Travel & Transport: Al
is becoming highly demanding for travel industries. Al is capable of doing
various travel related works such as from making travel arrangement to suggesting
the hotels, flights, and best routes to the customers Travel industries are using
Al-powered chat boats which can make human-like interaction with customers for
better and fast response.
Automotive Industry: Some
Automotive industries are using Al to provide virtual assistant to their user
for better performance, Such as Tesla has introduced TeslaBot, an intelligent
virtual assistant
Robotics: Artificial
Intelligence has a remarkable role in Robotics. Usually, general robots are
programmed such that they can perform some repetitive task, but with the help
of Al, we can create intelligent robots which can perform tasks with their own
experiences without pre-programmed. Humanoid Robots are best examples for Al in
robotics, recently the intelligent Humanoid robot named as Erica and Sophia has
been developed which can talk and behave like humans.
Entertainment: We are
currently using some Al based applications in our daily life with some
entertainment services such as Netflix or Amazon. With the help of MIAL
algorithms, these services show the recommendations for programs or shows.
Agriculture: Agriculture is
an area which requires various resources, labor, money, and time for best
result. Now a day's agriculture is becoming digital, and Al is emerging in this
field. Agriculture is applying Al as agriculture robotics, solid and crop
monitoring. predictive analysis. Al in agriculture can be very helpful for
farmers.
E-commerce: Al is
providing a competitive edge to the e-commerce industry, and it is becoming
more demanding in the e-commerce business. Al is helping shoppers to discover
associated products with recommended size, color, or even brand.
Education: Al can automate
grading so that the tutor can have more time to teach. Al chatbot can
communicate with students as a teaching assistant. Al in the future can be work
as a personal virtual tutor for students, which will be accessible easily at
any time and any place.
Applications in AI:
·
Google's Al-powered predictions (E.g.: Google
Maps)
·
Ride-sharing applications (E.g.: Uber, Lyft)
·
Al Autopilot in Commercial Flights Spam filters
on E-mails
·
Plagiarism checkers and tools
·
Facial Recognition
·
Search recommendations
·
Voice-to-text features
·
Smart personal assistants (E.g.: Siri, Alexa)
·
Fraud protection and prevention.
No comments:
Post a Comment