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Cognitive Science and Physics is being used to enhance Artificial Intelligence

Using Cognitive Science and Physics

This article explores the usages of Cognitive Science and Physics to combine with Artificial Intelligence. The power of AI is not only limited to Machines or programs or vehicles or smart systems, it enlarges with various domains to overcome the difficulties of hard environments where it is highly complicated or unable to dig in such kinds of environments. In order to extend its presence in vast fields such as astronomy and particle/nuclear physics is remarkable. To get or mimic human intelligence not almost but somehow can achieve by combining AI with Cognitive Science.

This article…


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Exploring Deep Learning, RL , NLP, Perception and Integrating Modules/Sub-fields.


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AI Modules or sub-fields introducing to newbie or starter of AI

Introducing & Exploring Problem Solving , Planing , Reasoning & Machine learning.

Due to readability issues divided this article into two parts.


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Reinforcement Learning Methods and working style

Learn in an interact way

Reinforcement Learning is part of Machine Learning and an agent learns on its own by interacting with Environment. RL does not require a data set.

Reinforcement Learning history and MDP is covered in more detail due to its popularity and more advanced research today, which is applicable in major applications like Autonomous Vehicles, Robotics, unknown and hard environments.

This article explores MDP & RL methods of Dynamic Programming along with examples. This article is particularly for beginners and those who want to know how RL is coming into picture. Due to non-deterministic actions of agents…


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Mathematical & Statistical Subjects in Artificial Intelligence Algorithms

Exploring Mathematical and Statistical Subjects of AI Algorithms.

Overview:

  1. Introduction
  2. Why Maths is required.
  3. List out Sub fields/ Modules of AI.
  4. Mathematical subjects and required topics.
  5. Applying Mathematical subjects in Neural Network for Multi Classification Example.
  6. Conclusion


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Quantum Program requires Quantum Computer ,Quantum Laws and Computational Tool(Linear Algebra)

Explored Concepts of Quantum programming in Simple way.

Quantum Computing = Quantum Physics (For Laws) +Linear Algebra (Computation) + Computer Science (Programming)

In this blog, I discuss the concepts of Quantum Programming and elaborate through mathematical perspective and comparing with Classical Computers for easy understanding. The following pic shows the topics that will discuss. Starting from Qubits. It is better to refresh required Linear Algebra.

Concepts of Quantum Programming


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Quantum Program requires Quantum Computer ,Quantum Laws and Computational Tool(Linear Algebra)

Explored Concepts of Quantum programming in Simple way.

Quantum Computing = Quantum Physics (For Laws) +Linear Algebra (Computation) + Computer Science (Programming)

In this blog, I discuss the concepts of Quantum Programming and elaborate through mathematical perspective and comparing with Classical Computers for easy understanding. The following pic shows the topics that will discuss. Starting from Qubits. It is better to refresh required Linear Algebra.

Concepts of Quantum Programming


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How Mathematical or Linear Algebra Objects(Vector, Matrices and Tensor) used in AI to store the different dimensions of Data.

Understand How Linear Algebra is applying in AI.

How Linear Algebra (Mathematical Objects) is using in Artificial Intelligence.

Shafi

Data Architect, Researcher & Guest Faculty in AI ,Autonomous Vehicles & Quantum Computing.

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