Artificial Intelligence Overview and Applications

Artificial Intelligence Overview

AI refers to ‘Artificial Intelligence’ which means making machines capable of performing quick tasks like human beings. In simple words, Artificial Intelligence (AI) is the ability of machines to perform tasks that usually require human intelligence.

AI has two key components –

  • Automation
  • Intelligence

Goals and Applications of Artificial Intelligence

Key Goals of Artificial Intelligence

  • Automate Workloads: Artificial Intelligence collects and analyze data using smart sensors or machine learning algorithms and automatically route service requests to reduce the human workload. Artificial Intelligence simplifies IT Operations as well.
  • Data Management: AI applications help to manage and analyze large databases simply. Moreover, displays a meaningful view of assets, business, staff or clients.
  • Improve Customer Service: With the use of a virtual assistant, businesses can provide real-time support and interations to its clients.
  • Increase Revenue: All the applications using Artificial Intelligence in DevOps helps business to identify the upcoming risks and maximize sales opportunities.

3 Stages of Artificial Intelligence

Stage 1. Machine Learning

It is a set of algorithms used by intelligent systems to learn from experience.

Stage 2. Machine Intelligence

These are the advanced round of algorithms used by machines to learn from experience. E.g. – Deep Neural Networks.

Artificial Intelligence technology is currently at this stage.

Stage 3. Machine Consciousness

It is self-learning from experience without the need for external data.


Different Stages of Artificial Intelligence

3 Types of Artificial Intelligence

1. Artificial Narrow Intelligence (ANI)

It comprises of primary/role tasks such as those performed by chatbots, personal assistants like SIRI by Apple and Alexa by Amazon.

2. Artificial General Intelligence (AGI)

Artificial General Intelligence comprises of human-level tasks such as performed by self-driving cars by Uber, Autopilot by Tesla. It involves continual learning by the machines and using AI in software testing.

3. Artificial Super Intelligence (ASI)

Artificial Super Intelligence refers to intelligence way smarter than humans.

What Makes System AI Enabled

AI Enabled Systems

Difference Between AI, NLP, ML, DL & Neural Networks

  • Artificial Intelligence (AI)

Building systems that can do intelligent things in Cyber Security using AI.

  • Natural Language Processing (NLP)

Building systems that can understand language. It is a subset of Artificial Intelligence used for IT Infrastructure Management, 

  • Machine Learning (ML)

Building systems that can learn from experience. It is also a subset of Artificial Intelligence.

  • Neural Network (NN)

A biologically inspired network of Artificial Neurons.

  • Deep Learning (DL)

Building systems that use Deep Neural Network on a large set of data. It is a subset of Machine Learning.

Difference Between NLP AI ML DL NN

A Holistic Strategy

Enterprises are facing Adoption challenges when Implementing Artificial Intelligence, Data Quality and Quantity. With an effective AI platform and Strategy Enterprises can accelerate their Digital Transformation journey. Now though you know what is Artificial Intelligence and applications so, its time to learn AI Transformation Road Map and Adoption Strategy.