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.