7 Key Requirements for Quantum Computing

Here, we discussed seven key  requirements for implementing efficient quantum computing systems. The seven key requirements are long coherence time, high scalability, high fault tolerance, ability to initialize qubits, universal quantum gates,  efficient qubit state measurement capability, and faithful transmission of flying qubits.  They are seven guidelines for designing effective quantum computing systems.  Quantum computing is the key technology for future artificial intelligence. In our Compassionate AI Lab, we are using AI based quantum computing

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Deep Learning Past Present and Future – A Review

Deep Learning Past Present and Future – A Review Deep learning is making a big impact in many areas of human life for solving complex problems. Deep learning models share various properties and the learning dynamics of neurons in human brain. Deep learning is an umbrella term. It covers many areas of artificial intelligence. In our Compassionate AI Lab, deep learning is now used in medical health care, radiology analysis, old age care, new drug discover to

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Artificial Intelligence for Balance Control and Fall Detection of Elderly People

Artificial Intelligence for Balance Control of Elderly People Designing automated balance control system for elderly people is one of the key project  of our Compassionate AI Lab. Here, Dr. Amit Ray discuses about one of the recent project of AI using deep learning algorithms for automatic balance control of elderly people. He explains how machine learning algorithms can be used to study and improve the dynamical properties of postural stability of elderly people. The project focuses on

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Quantum Computer with Superconductivity at Room Temperature

Quantum Computer with Superconductivity at Room Temperature Quantum computer with superconductivity at room temperature is going to change the landscape of artificial intelligence. In the earlier article we have discussed quantum computing algorithms for artificial intelligence.  In this article we reviewed the implication of superconductivity at room temperature on quantum computation and its impact on artificial intelligence.    Long coherence time (synchronized), low error rate and high scalability are the three prime requirements for quantum computing.  To

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Quantum Computing Algorithms for Artificial Intelligence

Quantum Computing Algorithms for Artificial Intelligence Dr. Amit Ray explains the quantum annealing, Quantum Monte Carlo Tree Search, Quantum algorithms for traveling salesman problems, and Quantum algorithms  for gradient descent problems in depth. This tutorial is for the researchers, developers, students and the volunteers of the quantum computing team of the  Sri Amit Ray Compassionate AI Lab. Many of our researchers and students asked me to explain the quantum computing algorithms in a very simplistic term.  The purpose of

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Spin-orbit Coupling Qubits for Quantum Computing and AI

Spin-orbit Coupling Qubits for Quantum Computing and AI Here, Dr. Amit Ray discusses the power, scope, and challenges of Spin-orbit Coupling Qubits for Quantum Computing with Artificial Intelligence in details. Quantum computing for artificial intelligence is one of the key research project of Compassionate AI Lab. We summarize here some of the recent developments on qubits and spin–orbit coupling  for quantum computing.  In digital computing, information is processed as ones and zeros, binary digits (or bits). The

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Deep Learning Research Datasets

List of Datasets for Artificial Intelligence, Data Science, Deep Learning and Machine Learning Projects. This list is created for the research and experimentation of  compassionate AI Lab.  UCI Machine Learning Repository, maintains 436 data sets as a service to the machine learning community. MNIST – MNIST contains images for handwritten digit classification. It’s considered a great entry dataset for deep learning because it’s complex enough to warrant neural networks, while still being manageable on a single

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