The term ‘Artificial Intelligence’ was first coined by John McCarthy in 1956 during his first academic conference on this very topic. But what do we actually understand by the term — Artificial Intelligence? 

Well, the term Artificial was included to illuminate the fact that this intelligence is acquired from the knowledge-base that is programmed into a system to carry out specific tasks. Whether it’s as simple a robot programmed to perform a particular task or to fast forward a few years and we have smart home devices with speech recognition, temperature sensors, remote control, data analysis and many more, all in one. 

Machine Learning-Artificial Intelligence
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Even though Artificial Intelligence operated using the programming codes integrated, they are now capable of much more than just executing the programmed tasks.

Basic Aspects of Artificial Intelligence –

1.) Physical Body — Consider a situation wherein we accidentally touch a vessel containing hot boiled water & quickly pull-away our arm. The information that the vessel contains hot water was sent to our brain from our visual and touch sensors which are our eyes and our skin respectively. The decision to pull away the arm was made by the brain and was sent back to the arm and the action was carried out accordingly. This whole process is known as response to stimuli. 

If you notice that in order to gather information and carry out a particular task, the brain relied on the respective sensors. Similarly in the machine world, even though all the input data is analyzed and processed in the virtual brain, it still needs a physical body to gather information and to carry out the resultant tasks. This physical body could be stationary machine like a computer or an in-motion one like a rumba. It would depend on the pattern of data collection and type of task which needs to be executed.

2.) Working Algorithm — Now, in order to find any meaning in the data that is been collected by the physical body, a machine relies on the algorithm that is fed in the system. Once the machine has analyzed the data, depending upon the algorithm that is fed in the system, it will carry out the necessary tasks. This whole process until here is known as narrow learning.

This has been around for the while and this is one of the basic function of Artificial Intelligence. But It’s just the basic one. Now, This begs the question whether AI can do more than just follow algorithms? Will machines ever be able to work on understanding feelings, reasoning, emotions, creativity or consciousness?

Well, The idea of Artificial Intelligence does not just stop at performing programmed tasks. Just like in order to learn something new, we as rely on gathering knowledge from our environment say by reading books, understanding nature and its patterns etc. , machines are now programmed to do the same. To learn new patterns and analyzing situations and formulating the best course of action in any new situations. 

And this brings us to the next stage in the development of AI — Machine Learning.

3.) Machine Learning — It is basically following the given instructions which were programmed in the system but with time it gets better at doing the tasks with time. 

Now how does this work? 

Machine Learning is a much more complex algorithm which instructions the particular system to not only perform the task but also gather more information about the background of the task and retain the results once the tasks were performed. This would help the machine understand the circumstances under which the task was carried out and the outcome of the performed tasks. Now, this information is retained by the machine to create multiple permutations and combinations for the same scenarios where the mentioned algorithm could help make informed decisions thereafter.

With Machine Learning comes the next best step up in AI — Deep Learning

4.) Deep Learning — Deep learning is basically a subset of Machine Learning. The basic functionality remains the same but the method of gathering the knowledge and the extent to which it can accumulate and process it is quite advanced. For example, although Machine learning is good enough to manage data and analyze them, it would still need human intervention in case there is an inaccuracy or if there is any change in circumstances. Whereas, In deep learning, the machine does not rely on human intervention as such. Since with good gathered knowledge, deep learning has the ability to understand, reason, prioritize the actions and make intelligent decisions in all related situations. But Deep Learning does rely on one particular action — Data Feeding. It is needed to recognize patterns, anomalies and to make a prediction.

Deep Learning-Artificial Intelligence
Source — TEDx Talks — A New Philosophy on Artificial Intelligence | Kristian Hammond | TEDxNorthwesternU

5.) Artificial Neuron Networks (ANN) — This is a key process to deep learning. We know, the neurons in the human brain are fed with all the information acquired by various senses so it can deduce all possibilities and then by proper decision-making provides the best course of action to the human body. Similarly, ANNs are expanded into sprawling networks with a huge number of possible outputs and predictions that are devised using a huge collection of data. Tasks like speech recognition, chat-bots, translation and language generation, stock market predictions, drug development and many more.

Deep Learning-Artificial Intelligence

Artificial Intelligence — The Future

The future of Artificial Intelligence
Art by @everythingstartswithanidea

1.) With the evolution of AI, computers will be able to take over humans in all the industries, from healthcare to freight forwarding and many more.

2.) We will have to maintain a good relationship with the machines as they will become our comrades, best friend and our caretaker.

3.) With the process of database collection, analytics and deep learning with neural networks, Artificial Intelligence would be able to predict future with good accuracy.

4.) Our jobs will be taken up by machines with better performance rate and efficiency.

5.) With Artificial Intelligence, we will be challenged with alternate job opportunities which would involve helping AI be at their best in helping us.

6.) Achieving perpetuity by copying our own thought pattern and memories into the digital realm.

Our Everyday Top 5 Applications of Artificial Intelligence –

1.) Search Engines — Google SEO and Analytics tools are one of the best examples of Artificial Intelligence technologies in this age. is a project which is exclusively dedicated to the digital data flow and programming on a wide range of tasks.

2.) Virtual Assistant — Google Home, Amazon Echo, Alexa, Siri & Cortana are the top virtual assistant made widely available to us which providing us assistance with automation, natural speech recognition and conversation, recommendations, reminders and multi-device integration.

Applications of Artificial Intelligence - Google Home
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3.) Autopilot Machinery — The semi-stealth mode Tesla cars have been around for about 2–3 years. Tersus AG 960 AutoSteer System is an autopilot solution for agricultural machinery. Warehouse Machinery — Unmanned aerial vehicles and self-governed forklifts have been replacing human labour on a high scale.

4.) Boosting OTT Services — Media Streaming provider like Netflix uses AI-based algorithm to compute the priority of its original content based on user preferences and streaming patterns.

Applications of Artificial Intelligence - Netflix
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5.) Digital Marketing Strategies — Using Machine learning algorithms help online vendors like Amazon enhance their customer’s experience by recommendations using past behaviour, historical data and location, promotions and real-time customer support.

Top 5 AI Technologies We Eagerly Await –

1.) Robotic Process Automation with AI — Robotic Process Automation alone would mean Robots imitating human responses but with Artificial Intelligence it will now be able to simulate human thinking patterns and intelligence to predict the best course of action.

Applications of Artificial Intelligence - Robot
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2.) Cyber Defence — Artificial Intelligence algorithms focus on detecting the abnormal events after carefully considering the baseline for the normal behaviour patterns. AI software is now able to work through a large database that is generated by cybersecurity systems.

3.) Digital Twin — Digital Twin is the virtual connection between the digital world and our physical world. It acquires data from the physical world, processes it and uses this data to create a prototype for a physical device or machinery to be manufactured. For now, NASA uses digital twin technologies to develop Next-Gen automobiles and machinery.

4.) Emotion Recognition — Using Speech Recognition and face detection, AI designers are working on developing an application which would be able to understand, detect and replicate the range of human emotions. Speech Analyzing Softwares like Lyrebird is working on this technique to help people who have lost their voice due to some illness or otherwise to find their voice again by understanding their movements and expressions to recreate their voice.

5.) Decision Making Management — Knowledge-Centric software platforms such as Pegasystems, Maana are in the rise in the business industry as it helps in the automation of the company’s digital process, internal & external business processes and manage customer relations.

Artificial Intelligence will keep on surprising us with innovations which would deeply affect our personal, professional and social life so lets very well make our contribution to the revolution.

Applications of Artificial Intelligence - Thinking
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So which AI innovation are you excited about?