Illumination on AI EP#5- Usefulness of Python in AI

While talking about artificial intelligence the developers of AI finds python language for programming trouble free and less complicated. All this is because python offers the smallest code out of other programming languages. It has been said that python code is 1/5 the of the codes of all languages. Also, it is a cross-platform programming language and it provides numerous applications.

The python is named after a television show Monty Python’s flying circus by its developer. Applications like software development, console, desktop GUI applications and many more. It is used for machine learning as well. Google also uses this coding language as one of its prominent programming languages. The developer of Python Guido van Rossum also worked at Google from 2005 to 2012. Doesn’t it is sound interesting how useful is python in today’s technological world? Studying python relation with AI will going to gives us more insider view of working of AI-based systems.

Origin of Python –

To know about python history, we first have to understand what is python? The answer is -It is an OOPs based, high level, interpreted programming language. Python was developed by Guido Van Rossum at CWI in Netherland in December 1989. Python is greatly influenced by ABC language and Modula-3 programming language.

Basic Programming in Python-

Programming in this language is easier to learn. Because it follows a simple and understandable syntax. To become a good programmer in any programming language, one must have to do proper practice and have to think in a more logical manner. To start learning in python we are going to demonstrate a few simple programs of python. Let’s hope you will get some understanding from them.

Here we are going to see a basic simple code in this programming language.

Here is a program for addition of two numbers. In this program below, we’ve used the arithmetic addition operator (+) to add two numbers. Changing this operator, we can get subtract (-), multiply (*), divide (/), floor divide (//) or find the remainder (%) of two numbers.

 Program of addition
Figure 1 Program of addition


Output of the code
Figure 2 Output of the code


Characteristics of Python –

1. Prebuilt Libraries-

Prebuilt libraries are the main advantage of this language; the prebuilt library is a pre-written piece of code which is used by users to perform various functions and actions in any code. This saves time because otherwise, a programmer has to write full code to perform any action.

Python has a lot of libraries for its users. There are few libraries which have crucial use in making and developing artificial intelligence-based systems.
Python Libraries for Artificial intelligence-

• pyDatalog
• SimpleAI

2. Easy community Support-

Python is an open source language which turns out to be the main point in helping beginners to learn its use. There are resources available online in different communities and forms, where every person can discuss his/her doubt and get a proper solution for it. These kinds of open communities help the programmers in the beginning period of their learning.

3. No specific working Platform-

Python is platform independent. What we want to say that it does not need any specific platform for working it can work on many platforms. Its versatility is very fruitful in making python world’s most preferred language by programmers. It can also, run on various platforms like Windows, MacOS, Linux, Unix, and others. Its platform undependability makes the process of program execution easier.

4. Flexibility-

Programming languages flexibility basically refers to the unexpectedly many ways in which utterings in the language can be used. Flexibility in the designing of a program is given through source code which means by modifying a program’s source code modify the program’s design. Flexibility is one of the main factors contributing to making it better and preferable among the other languages. Having an option to choose between whether to choose OOPs approach or scripting, it is helpful for every purpose. This programming language is beneficial for linking different data structures together.

Comparison With other Programming Languages-

The image given below shows us the comparison of a basic code in other languages to python. As you can see python code is smallest and easiest. As an amateur, you can able to understand the functioning of the code written in python just by reading it. Otherwise, in other languages, your mind has to think harder for proper understanding. That’s the beauty of python. Python provides you to write less code and to save more time and get the same output as the long code for other programming languages. Also, python has better user- friendly data structures as compared to other languages.

showing length of a code in different programming languages
Figure 3 showing the length of code in different programming languages

Popularity Among Developer’s-

According to the Tiobe Index of language popularity in 2018 Python was the highest popularity gainer language. It has the biggest rising by 3.62 percentage points from January 2018 to January 2019. Many statistics show that a developer wants to learn python as his/her first programming language. It is now frequently-taught language at various colleges and schools. The bar graph below shows the popularity of various languages in the present world. Presently python is leading the graph after the R language.

representing Popularity of python
Figure 4 Bar graph representing Popularity of python

A Chatbot- Perfect blend of AI and Python in Present Time


By looking at various features of python let’s look at the simple code  which is used in making an AI-based chatbot. By chat box we mean- A chatbot is defined as the computer program which is used to make a conversation from human to a computer system or to their mobile phones through voice commands or text chats or both.

Hence presently we can command just by sitting and relaxing at our home to our smartphone’s assistant or to the hands-free speakers like amazon echo. All these are working with a mixture of artificial intelligence and python. Here is the basic sample code for the functioning of a chatbot in which a user gives the input to the program through the means of the speaker.

  code for building a chat box
Figure 5 code for building a chat box
 output of the code
Figure 6 output of the code

Also, we usually say that we don’t know what the future is holding for us, but in case of artificial intelligence, we can for sure predict that upcoming future will be all driven by the artificial intelligence. As in 2019, the world is having a different way towards their living so we have in our future.

Bill Gates founder of Microsoft in an interview said that – Google, Facebook, Apple, and Microsoft are all moving ahead at great speed in improving this artificial intelligence software, so it’s very exciting! Software is going to solve that where it will look at all the new information and present to you knowing about your interests what would be more valuable.So, making us more efficient.

The most fascinating thing about artificial intelligence in the future in autonomy. By making an autonomous car we can reduce the life threatening accident by a huge percentage . Currently, Tesla is working on Tesla’s Autopilot version 1 which have shown a reduction of 45% in highway accidents. It is said by Elon Musk (founder & CEO of Tesla and SpaceX) version 2 must be at least 2 or 3 times better than the current  version that is running now.

In the future, with the help of artificial intelligence, we will do such things which seems impossible today. We might be getting better medical care or might be able to cure diseases we haven’t able to cure them now. In the field of education, we can make our classroom fully automatic and full of educational robots which are going to make a huge difference in the quality and learning of education. But with anything which is incredible there comes criticism along with it.

People are being pessimistic and optimistic about artificial intelligence. So, it is usually said that robots are coming for us or Artificial intelligence will be going to empower humans and going to take all our working opportunities’. But as it is said that if a thing is properly harnessed, we can able to reap all its benefits out. The thought of artificial intelligence as a villain today is of no use. We should be not worrying about the future and can be more optimistic towards artificial intelligence as it is contributing to the betterment of our life.

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Illumination on AI EP#4- Artificial Neural Networks

According to Alan Turing – “What we want is a machine that can learn from experience.”

Do you ever wonder how artificial intelligence-based robots and systems work? The answer is Artificial neural networks (ANN) which are the lifeline of AI-powered systems. Artificial neural networks presently have wide applications in every field. Talking about neural networks in aerospace, speech and image recognition to military ANN’s are beating every technology. So, to understand the concept of neural networks we have to dig deep into its origin and how a neural network work. In 1943 Warren McCulloch and Walter Pitts designed a computational model for neural networks which functions on mathematics and algorithms called threshold logic. This model laid down the foundation stones for the research in the area of neural networks.

Artificial neural networks are similar to the biological neural network of the human brain. A human brain consists of neurons that process and transmit information between themselves. In the human brain, there are dendrites that receive inputs. The human brain consists of neurons or nerve cells which transmit and process the information received from senses. Similarly, in artificial neural networks, there are artificial neurons which does all work similar to the function of neurons of the human brain.

Each artificial neuron transfer information to the other neuron in a similar manner as biological neurons transmits a signal in the human brain. The connection between artificial neurons known as “edges”. Artificial neurons have different layers. These different layers have internal connections  and used to perform the desired task. Mainly Artificial Neural Networks consists of input layers, output layers and hidden layers between the input and output layers. All sounds so complex let’s understand all this in an easy manner.

Diagram of Artificial Neural Network.
Figure 1 Diagram of ANN.


Hidden layer in artificial neural networks is the layer of neurons, whose output is having a connection with the inputs of other neurons and therefore is not visible as a network output. Each hidden layer in the neural network uses the information of the features. Hidden layers capture more and more complex information with every layer by discovering relationships between features in the input. So, to understand it deeply let’s talk about it in mathematical terms.

Mathematical Model of Artificial Neural Network-


 Mathematical model of ANN
Figure 2 Mathematical model of ANN


Artificial Neural Networks graphs contain weights in which artificial neurons are called as nodes, and directed edges with weights are the connections between neuron outputs and neuron inputs.The Artificial Neural Network gathers information from the external world in the form of pattern and image in vector form. Inputs are mathematically represented by the notation x(n).
Where n= number of inputs

Each input is multiplied by its corresponding weights. Weights are used by the neural network to solve a problem. Weight represents the strength of the interconnection between neurons inside the Neural Network. The weighted inputs are all summed up inside computing unit (artificial neuron).

In case the weighted sum is zero, bias is added to make the output non- zero or to scale up the system response. Bias has the weight and input always equal to ‘1′. The sum corresponds to any numerical value ranging from 0 to infinity. To limit the response to arrive at the desired value, the threshold value is set up. There are linear as well as the nonlinear activation function.

Don’t get bored by the mathematical model we have reframed something interesting to understand the working of neural networks at simpler levels.

How does a Neural Network Learn from Experience?

Naturally, a human learns things by watching them or if someone teaches how to do a thing. Like if we draw a painting on a particular topic but as a human, we want to know how good or bad is the painting it? when other people saw it and give their comments or say feedback. Also, We use these feedbacks as a way of improvement. Similarly, in neural networks there is a phenomenon is present which is feedback. Because feedback gives an idea about the actual output and the ideal output. Ideal output is the primary need of any system.

Process of forward and backward propagation-

The learning process in a neural network as a process of “going on and coming back” by different layers of neurons.The “going on” is known as the forward propagation of the information and the “coming back” is known as a backpropagation of the information.

The forward propagation occurs when the network is given the input data and this data runs across the entire neural network for calculation of predictions (labels). After that, the input data passed through the network, in particular, a way that all the present neurons apply their transformation to the information received from all the neurons of the previous layer and processing it to the neurons of the next layer.

Finally, when the data has passed all the layers, and all its neurons have made respective calculations, the final layer will give a result of label prediction for those inputs.

Also, neural networks learn from their environment and try to make modifications as required for better results. Therefore the diagram given below explains how a neural network identifies the image of a dog and gives the output as an image of a dog.

Figure 3

Artificial neural networks (ANN) are able to learn by adjusting the strengths of their connections to better transfer input signals through multiple layers of neurons associated with general concepts. As given in the figure we can see that how a neural network works one by one in different layers. So, figure itself explains the process of internal working of neural networks. Finally that’s how the artificial neural networks work for image recognition at various level.

Types of Artificial Neural Networks-

There are different types of Artificial Neural Networks (ANN) which are classified on the basis of their features and various functions. But we are going to discuss here the most basic neural networks which are the building blocks of another advanced neural network.

I. Feedforward Artificial neural network-

The feedforward neural network was the first and simplest type of artificial neural network devised. In different layers, all the nodes in a layer is having a connection with the nodes of the previous layers. As a result the connection has different weights upon them. There is no feedback loop means the signal can only flow in one direction, from input to output.

 A three-layer Feed forward neural networks
Figure 4 A three-layer Feed forward network

II. Feedback Artificial Neural Network-

A feedback network has feedback paths, which means the signal can flow in both directions using loops. Feedback networks are more efficient than feedforward networks as they always try to achieve the best results by using

A three layers Feedback ANN
Figure 5 A three layers Feedback ANN

III. Convolutional Neural Network-

A Convolutional neural network (CNN) is one of a type of deep neural networks which uses multilayer perceptron’s. Multilayer perceptron networks is a network in which each neuron in one layer is connected to all neurons in the next layer. So, CNN’s have applications  in image processing, natural language processing and other kinds of cognitive tasks.

 convolutional network
Figure 6 Working of convolutional network
Artificial Neural Networks Applications-
Neural Networks due to their vast utility in every sector have extensive applications used to perform various task  –

I. Speech Recognition-

As voice technology is reaching new heights, ANNs are having applications like automatic telephone conversations, home automation, mobile telephony, virtual assistance, hands-free computing, video games, etc And also, with continuous learning, neural networks help you achieve great speech recognition software.

II. Character Recognition-

Artificial neural networks are helping us to solve real-world problems and do things quickly to get fast output. ANNs are making a mark in the field of character recognition. Hence, Character recognition includes handwriting recognition which is helpful in minimizing the fraud in banks or at every other level. Similarly, in image recognition, there are many applications like facial recognition in social media platforms, therefore on Facebook – when you upload any photo the service automatically highlights faces and prompts friends to tag this is due to ANNs.

III. Forecasting-

Forecasting about certain behaviour of things becomes crucial in present times. Also, in weather forecasting, Neural networks are doing  the real-time processing of satellite and radar images that not only detect the early formation of hurricanes and cyclones.  Hence, it helps in making business decisions in sales, in economic and monetary policy in finance and the stock market. Also , detect sudden changes in wind speed and direction that indicate any upcoming disasters.

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Illumination on AI  EP#3                                       Illumination on AI EP#5-                                                                                                    Usefulness of Python in AI

Illumination on AI EP#3- Utility of Artificial Intelligence in Education Sector

In establishing a beautiful world of a child, education is of foremost importance. And for a better education system in today’s world of technology  AI is needed to indulge in our education system. AI is creating a change globally like in U.S and China for better results in education and career opportunities. By including AI in curriculum children should able to learn and apply technology to the world.

According to Alan Perlis – “A year spent in Artificial Intelligence is enough to make one believe in God.”

To achieve requisite knowledge and to discover the highest innovative qualities in children learning of AI and robotics must be included in their system of education. By using AI in the education environment children is getting keen interest in their learning and understanding how things around them are working in the real world.AI and robotics is a procedure to exhibit students that how science can be fun and fascinating to learn.By learning through AI in school and universities people are achieving various work-life skills like problem-solving skills, time management skills, flexibility and building confidence. Lastly, robotics helps in giving fruitful outcomes of trending education policy commonly known as STEM (Science, Technology,Engineering, and Mathematics).

Also, technology is rapidly covering all the areas in the world, we need to cope  up with it in a fast and effective manner. Artificial intelligence in class is providing overall development of a child and making various tasks easier for teachers.

As there are special children who find difficulties in learning and understanding things AI-powered education is the best solutions for them. Artificial intelligence is quickly opening new doors for teachers and their students, even those with learning disabilities are becoming smart. The idea of more personalized education with the use of artificial intelligence is fascinating and gaining interest among children.

In research’s, it is found that Children having Autism Spectrum Disorder (ASD) have high levels of comfort with computers and robots. Robots and Computer programs for them are interesting, predictable, logical, and can provide an intellectual environment for children with specialized interests.

Researchers and Therapists all over the world are testing and implanting new technologies. To find methods to help children with various disorders. So,they can develop decision-making skills, adaptability, confidence, self-motivation, and social skills. A human may find difficulty in dealing with children having disorders and children may found their teaching style boring but children tend to feel more fun and comfortable in studies with AI-powered social robots. More importantly, robots and AI don’t differentiate between any kind of children and treat them equally.

AI- Based Robots used in education-

Artificial intelligence-based Robots used in education to deal with any child in a careful way and give proper knowledge to the child. Numerous companies have developed different teaching robots based on AI. Below we have discussed few of most commonly known robots in the education sector.

NAO is the first robot created by Aldebaran Robotics now known as the Softbank Robotics. The robot teacher NAO, a humanoid robot has been used as a teaching resource for kids and especially with kids having autism in schools.  NAO aims to improve their social interaction and verbal
communication skills with interactive educational games. Nao robots have been used by numerous schools to introduce children to robots and the robotics industry.

 Nao the Robot

Figure 1 Nao the Robot

II.Tega: A Social Robot-

This robot is designed by Personal Robots’ group. Tega is a social robot which interacts with children in a fun manner. Tega unique and small appearance make it more friendly and attractive. Its physical expressions and furry design loved by the children of smaller age group. Tega has applications like storytelling, building up vocabulary and to do other educational activities.It has specification like wireless camera, 5 degrees of freedom, ability to expand and contract rapidly.

Tega also has powerful motors which make it move fast or slow according to the condition. Also,Tega uses mobile computing for central processing, physical motions, and audio-video inputs/outputs. If a kid enjoys the learning at school, he/she will gain more from the teaching and also desire to learn more.So, educational robots like Tega is making a revolution in the education sector by engaging kids in a fun learning environment.

 Tega robot with a kid
Figure 2 Tega robot with a kid

II. Solbit the Educational Robot-

This robot was developed by a company called 7 senses lab which works majorly in STEM initiatives for educational purposes. Solbit is an AI-based robot providing a personalized learning experience and can do many things as it listens, it recognises voices, words, and images, it follows, it asks, it teaches and track progress.

Through its algorithm, Solbit identifies kids’ unique talents and builds on the creative strengths and accelerates skill development. Above all, it grows together with the children. It provides features which are helpful for parents by which parents can participate in the learning experience of their children. Solbit in schools allows educators to use its cloud-based library and network of learning apps. As robots are making positive effects on children robots like Solbit are helpful for proper learning.

 Solbit robot working explanation
Figure 3 Solbit robot working explanation

Also, Various researches have shown that the use of artificial intelligence in the classroom is going to increase by 47.5% from 2017 to 2021. So, Educational robotics can be a useful tool in early and special education. There are several other robots are as well in education sector which is contributing to a better learning environment.

In the educational sector,  artificial intelligence tools are also providing automation in the work of the teachers. By using AI in classroom teachers can save their time and improve their teaching methodology. Let us look at different advantages of AI in the classroom.


AI is making education more fun –

Ordinary teaching in school and colleges makes the environment monotonous and students do not show any kind of interest in learning something new. AI in classrooms is making learning more fun and interesting by providing a technological environment.Because this will keep children engaged in class and understand all concepts that are being taught in class by the educators. Using robot technology and various AI-based software are developing a keen interest in learning and using the theoretical knowledge.

Artificial intelligence helps educators and organization in complex and time-consuming work-

A teacher spends a lot of time in checking and giving grades to the students by going through their answer sheets. AI makes this easier by using various AI-powered software’s and saves time. Also, can-do admission process more quickly. This will make educators spend more time and give more attention to each and every child individually.

Teaching and learning are boundless with AI

If you are feeling sick or facing problems because of which you’re not able to attend the classroom. Also, with the help of the AI,  you can attend and learn from class by sitting at any place. Students globally connect to educators and their friends by being online. They can ask any questions and interact with them without any hesitation.

Analysis of student’s performance –

With artificial intelligence, educators can rapidly analyse students’ performance in the classroom. Educators have more access to data than before that can assist them in identifying classroom weaknesses. This data may give an idea about various areas where teaching isn’t effective. So,the subjects where the majority of students are struggling. It also gives educators a better glimpse of how students with learning disabilities are doing in comparison to others.

AI for improvement –
So, AI can improve quality and flaws of educators and students in colleges or schools. AI based technology in some schools, which offers online classes are using AI systems for analysis of students’ progress. And notify educators in area do the students are lacking and how to improve these areas. These kinds of AI systems allow students to get the support they need. Also,for professors to find areas where they can improve their way of teaching for students who struggle in different areas.

Hence,by using all the benefits from artificial intelligence in classroom we can reshape the teaching world. Also, AI is not only reducing the load from the shoulders of educators but it is also recreating the best teaching experience. Institutes are trying to present education “Learn education with fun ” to get maximum output. Therefore, if we include AI in our daily education life in correct form, we will be standing in a far better place than others.

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Illumination on AI  EP#2                                    Illumination on AI EP#4-                                                                                                          Artificial Neural Networks

Illumination on AI EP#2- Gaining Smartness with AI

In today’s era, AI is furnishing the way in which technology is used by the people for the completion of their work. AI is helping in making the work easier and faster to do. As experts are saying that “Artificial intelligence could be ‘billions of times smarter’ than humans and humans may need to merge with the computers to survive”.
According to Dave waters – “Predicting the future isn’t magic, it’s artificial intelligence”
Considering this in mind we know how AI technology is changing the world at a rapid pace . Also, there are numerous applications in our life that are the valuable gifts of AI. With proper knowledge about usage of AI, in our lives we will able to make our present and future better.

Let’s take a look at them and understand the utility of artificial intelligence in making human work smarter and more accurate and its value in the real world.

I. Artificial Intelligence in Work Automation-

In this era of perfectionism, everyone desires everything flawless and Artificial Intelligence is helping them to achieve it. As a result AI is spreading like wildfire in today’s industries and with the help of industrial robots’ industries are reaching new heights and profit margins. Various software’s provided by prestigious companies help in tackling all the problems and difficulties related to an industry.
For e.g.- A company called KAWASAKI provided ‘duAro’, a collaborative robot shortly known as Cobot.  duAro is a dual-arm SCARA robot with 4 axes each arm that can coexist with humans in the workplace. Features of duARO are it takes less space because of its two co-axial arms and have easy teaching to the operator. This cobot has high safety feature if there is a collision with the worker, the collision detection function will stop the duAro safely.

 duAro Robot
Figure 1 duAro Robot

Similarly, a Software called Datapine is a business intelligence solution that’s available around the world. No matter what size your company is, analyzing information and visualizing the right KPIs is now easier. So, Data pine’s Software as a Service platform provides you all the power and flexibility to visualize your data in the most professional way. Not only Datapine is an AI based software there are several other software’s available online which uses AI technology and providing better results in every field.

Datapine software view
Figure 2  Datapine software view


From the above discussion we can see how AI has awakened the industrial automation and  helps in reducing human efforts and providing the best optimum product for the world.  Therefore , Artificial intelligence is engulfing the world inside through its advantages and ease which it is giving to humans. Also, just to do things by sitting at home comfortably and you can make your presence felt anywhere in the world.

II. Artificial Intelligence in Medical Field –

In the medical field, Artificial intelligence is providing better tools for diagnostics which are providing fast and accurate results. AI uses complex algorithms and software’s in various medical devices in all sector to provide a better result. Companies like IBM provides ‘IBW Watson health ‘helps in solving the world’s health challenges through the use of data, analytics and AI with the help of human experts. In oncology, Watson is at work supporting
cancer care in more than 300 hospitals and health organizations.

Also, Google in 2015 makes a deal with Johnson & Johnson to develop AI based surgical robots. The robots will help surgeons to perform surgery by providing better data which will minimize trauma and damage to the patient. Some systems allow surgeons to remotely control devices inside the patient’s body to minimize entry wounds and reduce blood loss.
Robotic surgical systems such as the Da Vinci made by the American company Intuitive Surgical have been Approved by the Food and Drug Administration (FDA) in 2000 used in general operations. Da Vinci Surgical Systems are used all around the world with an estimated 200,000 surgeries conducted in 2012.

 Da Vinci Surgical Robot
Figure 3 Da Vinci Surgical Robot

III. Artificial Intelligence in E-commerce –

Artificial intelligence is taking over everything which is present online. AI is everywhere whether it is related to business or safety. Talking about how AI works in the E-commerce industry here are some features which AI offers in E-commerce. As we all know AI-based systems are capable of learning new things from their environment.

Due to which AI in e- commerce creates customer-centric searches. There are many search engines which gives the results similar to how a human thinks. AI also helps with re-targeting potential customers .If someone spends a lot of time on a site viewing some product his/her data is observing by the system.  for this reason, the system will automatically send him/her notifications of their interest. AI is giving the user more personalized experience. let’s hope AI will make a huge contribution in E-commerce business.

IV. Artificial Intelligence in Video Surveillance-

In old times the video surveillance was a tough job to do. A security operator has to go through the large volumes of data for analyzing and finding any violation and accident. But things have changed now Artificial Intelligence in surveillance gives real-time monitoring and uses image processing, object tracing or facial recognition or better analysis and security purposes. AI in surveillance utilizes computer software programs for analyzing the images
from video surveillance cameras in order to recognize humans, vehicles or objects.

Advanced artificial technology builds an impact on video surveillance from companies to public bus stations, Public Places, Airports, Train Stations, and Security Companies are facing the problem of threats, where video footage helps to monitor live motion during incidents or accidents. The AI-powered software helps to bring an added component of intelligence to develop the process more efficient and powerful to monitor.

 Video Surveillance Process
Figure 4 Video Surveillance Process


V. Artificial Intelligence in Cyber-security-

Online world or in technical term digital world is the present time major necessity of every person. So, to protect the digital world is comes as a huge responsibility to every person. As today’s world is becoming digital, protection of this digital world is an utmost responsibility. In the 21st century, cyber crime is rapidly growing and it is estimated that it will cost the global economy more than$2 trillion by 2021.

Also, AI-powered Cyber security can ensure high standards of security and helps to fight against cyber-attacks. Presently we are facing malware and viruses, The Black Hat hackers know how the attack should be done.  Also,they are expert in the skill of attacking organizations without leaving evidence for cyber cells.

Many companies are working and giving solutions for providing end-to-end security. Companies like LogRhythm helps customer to rapidly detect and respond quickly to cyber threats.
There are many other features of AI in the field of cyber-security where we can use artificial intelligence to make our work secure and safe. They are password protected and credibility detection frameworks like bio metric logins.

Also, Artificial intelligence  identifies different physical qualities like fingerprints, retina scans.  By taking all these measures with AI we can do better in the upcoming future in better threat hunting. There are many other features of artificial intelligence in the field of cyber security.

Because the features are for password protection and credibility detection frameworks like bio metric logins. Artificial intelligence helps to identify different physical qualities like fingerprints, retina scans.
Hence, by taking all these measures with AI we can do better in the upcoming future in better threat hunting.

VI. Artificial Intelligence in Agriculture-

Agriculture is the base of any economy and maintaining agriculture properly is the major concern of any country. With the increasing population, we have to maintain the proper and healthy food. The population is increasing demand for massive food production. AI in the agriculture sector is conquering various heights.

Also, by using AI based systems a farmer can be saved from the harmful effects of pesticides . Agriculture robots like ‘Agrobot E- series’ is a robotic strawberry harvester uses real – time artificial intelligence, 3-D sensing and gentle harvest and fruit handling techniques. This robot has Up to 24 robotic arms working wireless as a team and the flexible platform fits into any configuration.

Finally another robot which is revolutionizing the history of farming is ‘ecoRobotix’ is a 100% autonomous automated robot weeder which do its navigation by GPS and sensors and driven by solar power. Two robotic apply a micro dose of herbicide, systematically targeting the weeds that have been detected. The machine can be completely controlled and configured by means of a Smartphone app.

Working of ecoRobotix
Figure 6 Working of ecoRobotix

Therefore as we are seeing any applications of AI in all sectors.  As a result, we can finally say that AI is making us smarter than ever before. Furthermore, we are looking forward to using all possible and fruitful outcomes of AI. Seems like the intelligent world is waiting for us let’s go and conquer this world.


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Illumination on AI EP#1- The Emergence of Artificial Intelligence

artificial intelligence

Ever since you heard  the word Artificial intelligence don’t you ever wondered , how this came into existence in the world. Let’s acquire some knowledge on the emergence of artificial intelligence and the meaning of artificial intelligence to enlighten our minds. So, in simple words, the term artificial intelligence can be understood as the ability of a computer controlled machine or computer robots to perform and replicate similar action as that of human beings with intelligence and smartness equal to them.

The term intelligence is a mixture of various qualities like one should have Reasoning,Learning, Problem Solving, perception and Linguistic Intelligence.

According to Alan Turing “A computer would deserve to be called intelligent if it could deceive a human into believing that it was human”

I. Early Days –

In the 1940s to the 50s researchers from diverse fields started thinking of the likelihood of making an artificial mind. The major role play for the development of artificial intelligence was initiated by Alan Turing..

Also, Alan Turing with his team builds the famous bombe machine for decryption of the ‘ENIGMA’ code. After this, he developed the Turing test in 1950. A Turing test is done to deduce a machine’s ability to reveal intelligent behavior. The idea behind the test is – if a human questioner is asking a series of questions with a computer. And a human respondent where he/she cannot reliably distinguish the machine from the human, the machine passes the test.

Turing test
Figure 1 Procedure of the Turing Test

Turing test provides the idea that machine can  work and behave like humans. This turns out a noteworthy gift by Alan Turing for artificial intelligence.

II. Dartmouth Artificial intelligence conference –

Everything starts with a thought and Dartmouth conference in 1956  laid the keystone of artificial intelligence in Dartmouth college conference which was organized by John McCarthy, Marvin Minsky, and two gems of the world- Claude Shannon and Nathan Rochester. The primary proposal of the conference is- “every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it”.

The proposal goes on to discuss various topics. Topics like computers,  neural networks, TOC, abstraction, and creativity . Clarity of these concepts is necessary to develop the field of AI in future.

In records, it has been found that there was a total of 47 participants at the Dartmouth conference. The Dartmouth conference was the instant in which AI acquires its value in the world. Officially it is the birth of Artificial Intelligence. The person who finally formulates the term artificial intelligence is John McCarthy (American computer scientist) and also, he is known as the father of artificial intelligence.

III . The expansion period of artificial intelligence-

From 1956-1974 artificial intelligence started making an impact on everyone’s mind. After the famous Dartmouth conference and many other conferences which nurtures the field of artificial intelligence had taken place. Once Claude Shannon said that “I myself could very easily imagine that happening. I see no limit to the capabilities of machines. As microchips get smaller and faster, I can see them getting better than we are. I can visualize a time in the future when we will be to robots as dogs are to humans”.

Artificial intelligence initiated the impossible things to make happen and achieved different aspects in terms of machine functioning. computers started solving algebra word problems, proving theorems in geometry and learning to speak English. As  a result researchers indicate an exceptional hopefulness that a fully intelligent machine will be there in less than 20 years.

Government agencies like the Defense Advanced Research Projects Agency (DARPA) showing interest and invested their money into a different field related to AI. DARPA helped sustain AI by giving its valuable support in terms of funding and the initial development period of AI.

  • Also, in 1956 the occurrence of artificial intelligence in fiction had been seen firstly in the movie named “forbidden planet” in which a character called “Robby the robot” exhibits AI. In similar ways, artificial intelligence keeps on reaching people eyes and minds.After this, a period has come which provided a major boom in the growth of artificial intelligence.
robby robot
Figure 2 Robby the robot
  •  In 1968 a movie came named 2001: A Space Odyssey – imagining    where AI could lead directed by Stanley Kubrick and the screenplay was written by Kubrick and Arthur C.Clarke in which an artificial intelligent computer HAL 9000 is featured. HAL (Heuristically programmed Algorithmic computer) is a computer which is in charge of maintaining mechanical and life system supports on the board and HAL have several eyes placed around the spacecraft and can do many functions such as speech, speech recognition, facial recognition, lip reading, interpreting emotions, expressing emotion.
HAL 900
Figure 3 Appearance of HAL 900

After seeing this audience interest in artificial intelligence and the awareness towards this field of research keeps on increasing. These kinds of development in the field fiction in terms of AI gained numerous benefits for the researchers as well.

IV. AI first and second winter –

After the enlargement in the field of AI, the researchers started facing hindrances . As a result British government stopped investing in the field of artificial intelligence.

In the second AI winter (1987-1993) the business section obsession reached its new peak. AI field continued doing advances which lead to new perception for the whole world in artificial intelligence. Due to improper computer power and hardware investors started taking off their money and support from the field of AI.

Finally the major breakthroughs for AI from AI winters are cheaper and mass production of graphics processing units (GPU’s), Big data and better algorithms for fast functioning of Artificial intelligence.

So, after facing several difficulties and a lot of hard work in this field the researchers found a new approach for AI. Because they believed that to showcase real intelligence of machine it will need a body. By that, they want to develop a body that will able to face challenges of the world. A body which will able to do all the work and bring down human efforts. Artificial intelligence can be used smartly and efficiently to get more productive results.

AI into body
Figure 4 Transforming AI into body

V. AI from 1993 to present –

AI till 1993 accomplished its new heights but the main challenge for researchers is to make a perfect model. In 1997 first computer chess-playing system named “Deep blue” Beat a world chess champion Garry Kasparov. Similarly, in 2005, a Stanford robot won the “DARPA” Grand Challenge by driving autonomously for 131 miles along an unrehearsed desert trail . Many other astonishing developments continue to happen in the field of Investment. And interest in the field of AI starts raising from 21st century.  when the concepts like machine learning, big data, deep learning and artificial general intelligence proven its value in present times.

Big data along with Artificial intelligence making things a lot easier and fascinating. As a result in today’s world,  AI and big data are like the backbone of each other. Also, Artificial intelligence powered systems need data for its betterment and new learning. So, Big data is making AI systems more sharp and smarter for fulfilling its output.

Also, AI is vigorously reaching new peaks of this world and conquering every challenge. Challenges which are coming in the betterment of Artificial Intelligence. Hence, Artificial intelligence is empowering the humans in every field to do better with help of it .

As a result, an overwhelming impression is growing within the education sector. Due to this the education sector is using AI. In the form of various tools which are helping in development and skills to get better outcomes from students. So, Artificial intelligence will be going to be compulsory in institutions. To get students to learn how to use and learn from technology for their better future. In the coming years, artificial intelligence will be much more expanded in our day to day life. Let’s, get ready to dive into the magical world of AI.

               Next –  Illumination on AI : EP#2  Gaining smartness with AI



The Pinch of Robotics Series : EP#4 : History of Robots

Water Tower Design


History of Robots: Since computer science has emerged as a field of studies not very long ago, the concept of a robot is quite contemporary for the people. However, the idea behind a robot was not conceptualized only in the last century. In fact, mythological studies suggest that people ruminated about “mechanical men” in the pre-biblical times as well. Not that this has much evidence to support itself but it is believed that the “First People” or the precursor race was advanced enough to have had highly intelligent machines in place during their time. There are mentions of devices pertaining to highly sophisticated machinery in almost all of the religious books.


Here are a few mentions of automated machines in ancient times-

  • In ancient Greece (c. 270 BC), Ctesibius produced the first organ and water clocks with moving figures to demonstrate applications of pneumatics and hydraulics.
  • In the 4th century BC, Greek mathematician Archytas theorised a mechanical steam-operated bird which he called “The Pigeon”.
  • Hero of Alexandria (10–70 AD), a Greek mathematician and inventor, created numerous user-configurable automated devices, and described machines powered by air pressure, steam and water.

    Water Tower Design
                                                                                      Su Song’s Water Clock

Su Song’s Water Clock

Su Song (1020–1101 AD) was a renowned Chinese polymath during the time of the Song Dynasty.

In 1066, Su Song built a water clock in the form of a tower which featured mechanical figurines which chimed the hours.

The beginning of the automata is associated with the invention of early Su Song’s astronomical clock tower which featured mechanical figurines that chimed the hours. This mechanism had a programmable drum machine with pegs (cams) that bumped into little levers that operated percussion instruments. The drummer could be made to play different rhythms and different drum patterns by moving the pegs to different locations.

Da Vinci’s Robot Model

Leonardo da Vinci (1452–1519) is arguably the most widely known polymath of all time. Besides his renowned and highly intricate artwork he is also known to have devised machinations generations ahead of its time.

In Renaissance Italy, da Vinci sketched plans for a humanoid robot around 1495. His notebooks, rediscovered in the 1950s, contained detailed drawings of a mechanical knight now known as Leonardo’s robot, able to sit up, wave its arms and move its head and jaw. The design was probably based on anatomical research recorded in his Vitruvian Man. It is not known whether he attempted to build it.


The late nineteenth century saw demonstration of several remotely guided vehicles called torpedoes. In the early 1870s torpedoes were developed by John Ericsson (pneumatic), John Louis Lay (electric wire guided), and Victor von Scheliha (electric wire guided).

The Brennan torpedo, invented by Louis Brennan in 1877, had two contra-rotating propellers that were spun by rapidly pulling out wires from drums wound inside the torpedo that powered it. Differential speed on the wires connected to the shore station allowed the torpedo to be guided to its target, hence making it the world’s first practical guided missile.

In 1897 the British inventor Ernest Wilson was granted a patent for a torpedo remotely controlled by radio waves.

In 1898 Nikola Tesla publicly demonstrated a wireless-controlled torpedo that he hoped to sell to the US Navy.

Archibald Low, known as the “father of radio guidance systems” for his pioneering work on guided rockets and planes during the First World War. In 1917, he demonstrated a remote controlled aircraft to the Royal Flying Corps and in the same year built the first wire-guided rocket.

Etymology of The Term “Robot”

The term robot comes from the Slavic word “robota” which loosely translates to ‘forced labourer”. As intended, robots were created to aid humans in ways both general and specific. ‘Robot’ was first applied as a term for artificial automata in the 1920 play R.U.R. by the Czech writer, Karel Čapek. However, Josef Čapek was named by his brother Karel as the true inventor of the term robot.

Robots in The Past Century

In 1928, one of the first humanoid robots, Eric, was invented by W. H. Richards. Its frame consisted of an aluminium body of armour with eleven electromagnets and one motor powered by a twelve-volt power source. Eric was exhibited at the annual exhibition of the Model Engineers Society in London, where it delivered a speech. It robot could move its hands and head and could be controlled through remote control or voice control.

In 1926, the Westinghouse Electric Corporation built “Televox” a cardboard cutout connected to various devices. In 1939, the humanoid robot known as Elektro was debuted at the 1939 New York World’s Fair. It was seven feet tall and weighing 120.2 kg, and could walk by voice command, speak about 700 words, smoke cigarettes, blow up balloons, and move its head and arms. The body consisted of a steel gear, cam and motor skeleton covered by an aluminum skin. In 1928, Japan’s first robot, Gakutensoku, was designed and constructed by biologist Makoto Nishimura.

Present Day

As we are advancing towards an age of mechanical autonomy, the need for having to control robots manually keeps on decreasing. With the understanding of Machine Learning and Artificial Intelligence concepts, the present day robots are capable of both carrying out and improving upon their tasks without human intervention.

Here are a few robots of the recent times –

  • Valkyrie – This robot was originally designed by NASA to be operated at the International Space Station. It is able to walk by itself, pick up objects and use tools. The aim is that it could be used to help humans in danger zones and disaster-stricken areas. It also has several built-in cameras, recording and sonar equipment. 

    SCHAF Robot
                                                                                    SCHAFT Robot
  • Schaft – Made by a Japanese company, this robot won the DARPA robotics competition. This 4 feet 11 inches tall robot uses a high-voltage liquid-cooled motor technology and a capacitor to power itself instead of a battery. This gives it greater movement and mobility since batteries limit how fast the robot can actually perform tasks.
                                                                                CHIMP ROBOT
  • CHIMP – CHIMP (Carnegie Mellon University Highly Intelligent Mobile Platform) moves like a tank by using tracks to move over rough terrain. The robot is still capable of standing up when necessary and can even use its claws for climbing.


  • Alpha Dog – This robot can stand upright, walk continuously for 20 miles and is able to carry 400 pounds. The robot is also able to pick itself up if it falls over. The robot is designed to follow soldiers and carry their weapons through rough terrain and automatically go wherever they go, without having to stop. The Alpha Dog is currently being tested by the Marines.

The Future

With the technological potential that seems to be at hand it is not possible to cover every aspect of how robots are going to be designed and become a part of our lives in the decades to come, although it is merely inevitable that there will soon be a time when robots will have replaced humans in the rudimentary roles. The question that remains is – how far are we willing to let robots into our lives?



Previous Blogs:
What are Embedded Systems?
Evolution of Computer Programming.
Click to learn more about Robotics.

The Pinch of Robotics Series : EP#3 : Evolution of Embedded Systems

Embedded Systems

An Embedded System is a computer hardware infused with a software to carry out a specific or variety of tasks. The programmability of an embedded system can either be rigid or flexible. That is, an embedded system may have only one functionality, or may be programmable to carry out whatever function the user asks it to do. Embedded systems are real time systems. The processors are subjected to a limited time constraint and designed to work on an event-to-system response method.

Circuit Wallpaper
Fig 1: Circuit Board

An Embedded System consists if a microcontroller, which is the principal component in an embedded system. It contains memory, programmable input and output peripherals as well a processor.

Embedded systems are widely popular because of their limited capabilities. They are cheaper than a standard computer system and usually smaller, take low electrical input, and carry out the operation designated just as effectively. Because of their low cost maintenance, embedded system units can easily be mass produced.

The most common example for an embedded system would be a cell phone. It consists of designated circuitry to receive radio signals and convert those radio signals into electrical signals and vice versa. It also contains DRAM memory segments to hold phone numbers and names.

Cell phone exploded view
Fig 2: Cell phones have designated circuits for fixed functionalities


Following timeline highlights the events throughout history contributing towards the embedded systems we know of today:
1833Michael Faraday discovers an increase in electrical conduction with temperature in silver sulphide crystals.
1874Ferdinand Braun notes that electric current flows freely in only one direction at the point of contact between a metal point and a galena crystal.
1959Robert Noyce works upon Jean Hoerni’s planar process to patent a monolithic integrated structure ripe for mass production.

The very first recognizably modern embedded system was the Apollo Guidance Computer, developed in the 1960s by Charles Stark Draper at the MIT Instrumentation Laboratory. At the time this project was considered highly risky manoeuvre, because of the device’s monolithic circuitry and reduced size. An early mass-produced embedded system was the Autonetics D-17 guidance computer for the Minuteman missile, released in 1961.


Applo computer 1960
Fig 3: Apollo Guidance Computer (1960)

Since the introduction of embedded systems in 1960s their size has gone down and throughput has increased rapidly. Also introduced to embedded systems over the time are User Interfaces (UIs), monitors and dedicated power storage units.


Worldwide, large investments continue to happen towards designing devices pertaining to information, communication and entertainment; and making them intelligent through embedded software. Be it telecommunication, radar systems, underwater acoustics, automotive, industrial or entertainment gadgets—embedded systems have been employed to do things smartly. The current growth in embedded intelligence technology is fuelled by the fact that there has been steady increase in processing power and storage capacity. Southward cost has also triggered rapid pace in research and development in this area. All these have led to greater output with lesser horsepower (MIPS), lower memory, lesser power consumption and smaller physical dimension.

The recent advancements in the embedded systems has seen their designs become more edgy and crafty. But their performance in the upcoming time will be upgraded drastically with the help of multicores. The advancements in nanotechnology and reducing the memory and power requirement along with the sizes of the ICs. These processors deliver more performance per watt with a smaller die size, offering better performance (counted in instructions per second, transactions per second, calls handled per second, measurements per second, and overall throughput) and consolidation (the combination of multiple distinct pieces of functionality often serviced by multiple different operating system instances on a single chip). Multicores in a system can be achieved via virtualization. It allows a designer to create multicores inside a partition system. These cores will be segregated from each other in time and space, hence offering mutual exclusivity and fault containment.
Multicore and virtualization are revolutionizing the embedded systems’ designs.

Fig 4: Multicores

Here are a few embedded systems that will soon become a common presence in our day to day lives:

Ubiquitous computing – The term Ubiquitous Computing (Ubicomp), also known as Pervasive Computing, was coined around 1988 by Mark Weiser when he was heading the Xerox Palo Alto Research Center (PARC). As the term suggests, Ubiquitous Computing is a branch of computer science that deals with the connectivity of our smartphones and other intercommunicating devices with the objects we interact with in our daily lives. These can range from our clothes to our coffee mugs and other accessories. With advancements in cloud computing, ubiquitous computing has got a real boost. We could soon expect more objects infused with ubiquitous computing.

Embedded vision and speech – Voice and vision recognition systems infused to neural networks are fast becoming a thing. You don’t need to hold a device in your hand and press a set of buttons to do something anymore. You simply need to speak and the device works. Machine Learning algorithms ensure that the system learns your preferences and operate accordingly so you don’t have to specify every time.

Augmented Reality infused with Artificial Intelligence – Augmented Reality based devices might flood the streets faster that you’d expect. Projects like Google Glass and miniscule games like Pokemon Go have already ensured the Augmented Reality will serve as a popular prospect, where the digital life is merged with the physical real world creating countless more opportunities in the field of entertainment, education and research.

Augmented Reality Embedded Systems
Fig 5: Augmented Gaming is becoming increasingly popular

Gaming Tech – Virtual Reality headsets are already quite popular among household gamers. Recent developments have indicated that there soon will be devices on the market which would grant a gamer a sense of touch inside the digital world. This will not only create new gameplay opportunities but will also bring about exponentiation of the gaming market.

Script recognition – The script recognition systems come in handier than you’d think. Inability to understand a handwriting can often lead to drastic outcomes. These systems convert a handwritten text to clear faced text.

Previous Blogs:

Evolution of Computer Programming.
Click to learn more about Robotics.

The Pinch of Robotics Series : EP#2 : Computer Programming 

Evolution of Computer Programming 


  • Introduction

The Pinch of Robotics Series : EP#2 will focus on Evolution of computer programming.

A language works so as to facilitate communication between two parties. A computer language, thusly, eliminates the barrier between a user and a machine. In other words, a computer language allows a user to use a machine to carry out required tasks.

  • History

Although the computer programming languages surfaced some seventy years ago, the bud to this flower can be traced back to almost two hundred years ago since the invention of the punch-card-programmable Jacquard loom. It wasn’t a programming language in the modern sense — there was no computation and no logic — but it started a cascade that would eventually lead to Charles Babbage’s Analytical Engine, and Ada Lovelace’s 1842 deconstruction of his work which led to the first computer program. It will not be until the early 1940s that the first electronic programmable computers burst into existence and with them a need for a programming language.

Over the past decades, programming languages have evolved in such a way so that they have become easy for the users to comprehend. Based on the ease of access, the programming languages are of three types –

1.   Machine Language

It’s the native tongue of the computer. It’s the most primitive form of programming language for an electronic computer, in which the data is handled in the form of 0s and 1s which the machine interpreted via an absence or presence of voltage over an infinitesimal unit of time. Since binary language is closest to a computer, it is far from convenient for humans, takes excessively much time and is incredibly complex, to a point that it has, as of recent, become an esoteric language.


Machine Language

2.  Assembly Languages

Assembly languages are an effort to make programming relatively easy for humans. When binary language was deemed too complicates, there came need for a language that had words resembling those of a language humans understood. That is how assembly language came onto the scene. It introduced mnemonics that added relevance to programming. This too, however, was deemed inefficient after a while.


Assembly Language

3.  High Level Languages

High-level languages are more English-like and, therefore, make it easier for programmers to “think” in the programming language. High-level languages also require translation to machine language before execution. This translation is accomplished by either a compiler or an interpreter. Compilers translate the entire source code program in one go, while Interpreters translate source code programs one line at a time. Interpreters are more interactive than compilers.

The catch with High Level Languages is that with every new language that is meant to add to the ease of user access, the processing requirement of the same increases. Thankfully, with the new up and coming high end processors, practically employing said languages is becoming feasible.


High Level Languages

The process of developing a new language has resulted in a plethora of languages to choose from today. There are all types of languages depending on their usage and user requirement. Some of these types are –

4.  System Languages

System programming languages pertains more towards management of a computer system rather than concerning with the overlying applications. A system language, is generally responsible for:

  • Memory management
  • Process management
  • Data transfer
  • Caches
  • Device drivers
  • Directly interfacing with the operating system.

The most widely used systems programming languages are C and C++.

5.  Scripting Languages

Scripting languages are used to combine systems and applications. Their code is usually very dense, that is, a small line of code is capable to carrying long operations. These languages are also mostly dynamic, which means that compilers have very little to do in comparison with the corresponding run-time systems. Scripting languages came about largely because of the development of the Internet as a communications tool. JavaScript, ASP, JSP, PHP, Perl, Tcl and Python are examples of scripting languages.

6.  Esoteric Languages

“Esoterica” is something which is used and understood by only a small number of population. Consequently, esoteric languages are of a special kind used by a select number of people. These are mainly intended to be used for fun and kicks. Programming geeks and fanatics of lore and culture develop most of these languages. Few examples of esoteric languages are Whitespace, Malbolge, Ceaser, Shakespeare, Pikachu etc.


  • Ousterhout’s Dichotomy

The Ousterhout’s Dichotomy, proposed by John Ousterhout as a software development paradigm, categorises modern day computer languages distinctly into two groups, namely system languages that manages the efficacy of a system and overlying scripting languages also called “glue” languages that wire everything together.


If you guys are new to our blog series and want to know about Robotics and Its Basics click here.

The Pinch of Robotics Series : EP#1

Basics of Robotics and Mechatronics

As engineers all over the world keep working further on the technological advancements, we as a society keep moving towards relying more and more on machine with each passing day. As machines have started frequenting our lives more and more, it has thus become important for one to learn how they work, in order to create and use them.


Understanding the machines however requires one to take to comprehending the multidisciplinary edifice the baselines the creation, working, and application of a machine, called “Mechatronics”. When Japanese engineer Tetsuro Mori coined this in the late 1960’s, his combination of the terms ‘mechanical’ and ‘electronics’ became synonymous with engineering innovation. Indeed, the field of mechatronics is a wide-ranging, multidisciplinary sector that combines engineering, computer science and technology to innovate, improve and simplify systems and processes. The last few years have seen a drastic boom in the application of its study in our everyday lives. Hence, it can be said that studying mechatronics has never been more rewarding.


It needs to be noted here that while it has many practical applications, mechatronics in itself is a theoretical approach which unites the principles of mechanics, electronics, and computing to generate a simpler, more economical and reliable system. While it encompasses the understanding of machines, mechatronics is not also branching out into different fields of sciences paving way for studies of current and future prospects.


The human zest to create a machine that could substitute for a person and carry out their task with equal if not more efficiency has given rise to intelligent computational machines called robots. Robots are complex machinations designed to carry out one or many tasks. Each robot is programmed to be able to carry out said tasks without too much user intervention.

                            A.I. Infused Humanoid

Understanding and working of robots pertains to the field of study called “Robotics”. While this term is often considered synonymous to mechatronics that is not actually the case.

Robotics is a branch of mechatronics which specifically  deals with understanding the working of robots. That is to say, all of robotics is mechatronics but not vice versa. The field of robotics is advancing exponentially every day, with each prospect getting more complex and life-like than its predecessor.

Every day, engineers strive to create a synergic machine that could carry would comprise of complimentary parts that when brought together would work better than their individual constituents. Another variable that comes into account while discussing robotics is how much a machine can compute by itself. That where Artificial Intelligence (AI) comes in. The new advancements and circumstances dictate the need of machines that can do the work of a human being.

The demographic of the world is changing rapidly. According to the World Health Organization, “The number of people aged 65 or older is projected to grow from an estimated 524 million in 2010 to nearly 1.5 billion in 2050.”

                                      2010 Census Shows 65 and Older Population Growing

This can be accredited to the medicinal and technological advancements that have rendered the human life expectancy risen. There are more retired workers than the newborns could account to be replaced. With a shortage of births to replace the retired workers, many countries are facing the prospect of shrinking workforces.

Japan’s workforce, for example, is expected to decline to roughly half its peak level by 2060. Henceforth, this indicates towards the need of more workforce in form other than people that could carry out the work, which signifies the importance of the robotics industry in the coming years.

Nearly every industry can find ways to incorporate these innovative technologies in an effort to improve output or reduce costs. This is why analysts expect that by 2020 the robot and AI market will exceed $150 billion. Robotics is a field flush with prospect and potential.

The possibilities that could be endowed upon with the right amount of funds and research is seemingly boundless. 😉


Mechatronics is the cluster of many domains and sub-domains including robotics. Robotics is going to be the future of Homo Sapiens in coming up of years. Hence, we should be well prepared to witness the change in technology, medical, industrial and other aspects of our life. Let’s get ready for “The New Era of Robotic Automation!”  🙂