WHAT ARE ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING?
What
are Artificial Intelligence and Machine Learning? Everybody would be curious
enough to know what these above terms represent. Now let us dig into the topic a little more.
The
purpose of this blog post is to enlighten the readers with comprehensive
knowledge of Artificial Intelligence and Machine Language and the difference
between them. Besides, their uses are
also discussed in this article to a certain limit.
Here
I shall give the definition of Artificial Intelligence and Machine Learning,
the fields in which their presence comes to play, the difference between the both, their
advantages and disadvantages, and their scope in the future, etc.
ARTIFICIAL INTELLIGENCE (AI)– in brief
Artificial
Intelligence is the field of Computer Science used for creating machines that
can do tasks that typically require human intelligence. Some actions performed by AI are Visual
perception, Speech recognition, Decision-making capacity, Processing of Natural
language, Learning, and Reasoning.
AI-empowered systems use algorithms and data based on which such machines learn,
reason, and help in decision-making to solve various problems in society
like humans.
Artificial
Intelligence empowered machines are put to use in various sectors of society like manufacturing, healthcare, transportation, businesses,
entertainment, etc.
There
are four major types of Artificial Intelligence, Reactive Machines, Limited
Memory Machines, Theory of Mind Machines, Self-aware Machines, video making
and editing and game development, etc. Also,
there are a few more types of AI systems like General AI and Narrow AI.
General
AI has the power of learning, reasoning, and understanding capabilities and can
help in finding solutions similar to humans.
Narrow
AI is the most commonly used AI system which is being currently used
widely. For performing specific tasks
like image recognition (mainly used in healthcare) or language translation like
humans narrow AI is used.
AI
can otherwise be said that it is a technology used for creating intelligent
systems that can simulate human intelligence.
You may go through my earlier
articles written on this subject.
From
the above narrative, it could be seen that each type of AI is used depending
upon the specific characteristics of AI and the desired output
required for the well-being of humans.
MACHINE LEARNING (ML) – in brief
Machine
Learning is a subset of Artificial Intelligence. Machine Learning involves the use of Algorithms
and statistical models. This would enable the
machines to learn from historical data fed into the system through various
programs, without explicitly programmed.
These
typess of algorithms can be used to learn and adapt to new data inputs, which are
scalable and more flexible when compared to traditional software.
Machine
Learning can be of three major types, viz. Supervised Learning, Unsupervised
Learning, and Reinf cement Learning.
While Supervised Learning involves training a model on labeled data,
Unsupervised Learning is associated with training of a model on unlabelled
data. Using the feedback received from
the end users to train a model to take decisions is called Reinforcement
Learning.
Major
applications that are using Machine Learning are image and speech recognition,
natural language processing, detection of fraud, predictive maintenance systems, etc.
Machine Learning systems are used in Image and Speech recognition (virtual assistants), recommendation systems, fraud detection management, Natural Language Processing, Marketing campaigns in a personalized manner, Predictimaintenancence system, medical diagnosis, recommendations for personalized treatments, optimization of supply chain management, etc.
From
the above, it could be observed that both Artificial Intelligence and Machine
Learning are correlated/interrelated with each other in accomplishing a task. However, Artificial Intelligence can be
differentiated from Machine Learning in the following aspects:
WHAT ARE THE DIFFERENCES BETWEEN AI AND ML?
- Artificial Intelligence enables the machines to simulate human behavior while Machine Learning allows machines to learn from historic data to give the output.’
- AI-empowered systems can give solutions for complex issues, while ML can learn from historic data to give accurate output.
- AIs can perform tasks like a human and MLs can give the results based on the data fed.
- Ais based on Machine Learning, but Machine Learning is based on Deep Learning technology.
- While AI can give a wide range of output, MLs can perform only to a limited extent based on the data inputs.
VARIOUS COMPONENTS OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
The above two systems work with the help of the following components that help
in the development and usage of machine learning models with a view to automating
tasks based on the relationship and patterns in the data:
Data is a vital component of any Artificial Intelligence or Machine Learning system. For any training model, the input data is considered to be essential based on which the output is derived.
The Mathematical models and statistical methods which are also called Algorithms, are used to train the machine learning model, which can enable the model to learn from the data and give the output.
Hardware
and software resources, called the Compute Infrastructure also form one of the
main components for these AIs and MLs.
This component is needed to train and run the machine learning model to
throw the output.
To
achieve efficiency in building and deploying machine learning models, Tools and
Framks like TensorFlow,
PyTorch, and Scikit-learn,
etc. are required by the Data Scientists and Developers. These Tools and Frameworks enable Data
Scientists and Developers to abstract away the fundamental complexity of
machine learning.
Also,
to have effective machine learning models, it is very much necessary to have
human expertise, without which the task cannot be performed. Therefore, it becomes absolute essentiality
to get persons with good domain knowledge and expertise in the specific
category or area of application and persons with expertise in designing and
implementing skills of machine learning models.
COMPARISON OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING WITH HUMAN LEARNING
ARTIFICIAL
INTELLIGENCE / MACHINE LEARNING |
HUMAN
LEARNING |
AI/ML
learns from a specific dataset or task by way of designed Algorithms, which
have limited knowledge depending upon the data contained. |
Human
learning covers a wide range of tasks and situations, depending upon the
knowledge, skills, expertise, and experience. |
AI/ML
algorithms are consistent, can deal with larger volumes of data, are speedy, and are accurate. |
Slower,
probability of containing errors, and more particularly influenced by various
factors like fatigue, emotion, sentiments, etc. |
The
outputs depend upon the data inputs and hence, quality and quantity are limited. |
More
adaptable based on contextual factors and acquired knowledge, expertise
and experiences. |
IMPORTANCE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
Machines
empowered with AI and ML can improve efficiency and bring out more
production output with speed and precision.
They also reduce the cost of production in a way by necessitating reduced
deployment of human force.
AI
and ML-enabled machines can know the preferences of various types of consumers
and can yield an optimum out of products in a personalized manner.
AI
and ML-empowered machines can enable better decision-making in an organization purely
based on the data inputs without any second thought.
AI
and ML enabled machines play a major role in the healthcare industry transformation to get the most accurate
diagnosis, chalking out a personalized treatment plan, saving time, etc.
Both
AI and ML help in reducing the crime rate, by giving predictions and prevention
of crimes, and identifying areas of weakness towards potential threats.
Climatic
challenges are well predicted by AI and ML-empowered machines to give advance
predictions on weather, water, and other natural resources so that appropriate
steps could be initiated.
AI
and ML-powered machines can do proper budgeting which helps in the growth of
economic conditions and prosperity of the nation.
WHAT
ARE THE ADVANTAGES AND DISADVANTAGES OF AI AND ML?
ADVANTAGES
OF AI AND ML |
DISADVANTAGES
OF AI AND ML |
Help
in the automation of tasks and processes |
Difficult
to interpret and understand.
Therefore, it becomes difficult to identify the errors in decision
making. |
Reduces
the dependency on human sources |
Can
be prone to security risks like cyber attacks, thereby posing a threat to
saving vital data. |
Can
analyze larger volumes to get the most accurate outputs. |
Poor
quality data inputs can make the output inaccurate and biased results. |
Can
be used for the personalization of experiences and recommendations |
Automation
by way of deployment of AIs/MLs is posed with the risk of increasing
unemployment and indirectly impacts the economic conditions
of individuals. |
Help
in effective cost reduction because of automation and maximum output in a
smaller time. |
Cause
ethical concerns on privacy issues and use of sensitive data. |
Can
be customized depending on the data volume in accordance with the changing
business requirements. |
Cannot
be relied upon in case of corruption of data due to human error or misuse that
require rebuilding, which costs heavily. |
Though
I have listed only a few examples of advantages and disadvantages above,
there are some more including advancement in natural language processing, the requirement of additional talented Data Scientists and Developments, a requirement
of individuals with experience, expertise, and knowledge, etc. are considered to
be good signs of prosperity.
FUTURE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
Various
reports that we come across on the researches, developments, and innovations taking
place in these fields of Computer Science, suggest that there is a bright
future for Artificial Intelligence and Machine Learning.
AI
and ML market has got high potential to grow further rapidly in the days to
come attracting a high volume of investments.
With
the development of AI and ML and widespread usage, almost all sectors of any
country are switching over to adopt this innovative practice of automating
complex tasks, and decision-making processes, to increase effective, efficient, and speedy
outputs.
Due
to the advancement of Natual Language Processing, the communication between humans and machines is expected to grow multifold in the future, which may make
life easier.
Though
most of the sectors of the nation like manufacturing, healthcare, transportation,
finance, entertainment, weather predictions, etc. are already engaging the
services of Artificial Intelligence and Machine Learning, it is expected to
expand in other parameters of the economy also in the near future.
To
cope up with the present and future requirements of evolution, the expansion of
applications backed with Artificial Intelligence and Machine Learning will
augment emerging employment opportunities.
With
an aim to get more transparency and accountability of AI and ML systems, the inclusion
of Explainable Artificial Intelligence, which helps to understand the
predictions made, system emerged.
Quantum computing technology helps in the processing of larger amounts of data
in parallel to get improvement in speed and efficiency.
AI
and ML-empowered systems are used to provide recommendations to help humans in
taking better decisions through Augmented Intelligence.
WRAPPING UP
Use
of Artificial Intelligence and Machine Learning systems have become an essential
part of our daily life. They are benefitting mankind by transforming many aspects of our life, be it – finance,
manufacturing, healthcare, transportation, weather predictions, entertainment,
etc.
Keeping
the advantages on the one side, there are some adverse impacts such as breaching
of security, privacy, etc. also. However, it is our hope that we shall overcome
these disadvantages over a period of time by finding adequate solutions.
It
is essential to accept that any innovation that we come across in our life shall
have both advantages and disadvantages.
However, the development and advancement of AI and ML cannot be
contained because they have become a vital aspect of our life to give make our
life easier.
It is everyone’s aspiration and ambition that we should start living with the day-to-day developments and current situations instead of regretting the past or future and hoping for the best in the future. We shall make every endeavor to grab the best opportunities arising out of such innovations.
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