AI Tutorial

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 this article is to explain that.

Quantum Computing Algorithms for AI By Amit Ray

Earlier we have discussed Spin-orbit Coupling Qubits for Quantum Computing and the foundations of  Quantum computing and artificial intelligence.  This article is to explain the foundation quantum computing algorithms in depth in a simplistic way. Here we explained the concepts of quantum annealing, Quantum Monte Carlo Tree Search, quantum algorithms for traveling salesman problem and Quantum algorithms for gradient descent problems. Read More »Quantum Computing Algorithms for Artificial Intelligence

Spin-orbit Coupling Qubits for Quantum Computing

Spin-orbit Coupling Qubits for Quantum Computing and AI

The Power of Spin-orbit Coupling Qubits for Quantum Computing

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 analogue to these in quantum computing are known as qubits. The qubits are implemented in nanoscale dimensions, such as spintronic, single-electron devices and ultra-cold gas of Bose-Einstein condensate state devices. Manipulation and measurement of the dynamics of the quantum states before decoherence are the primary characteristic of quantum computing. 

 

Quantum Computing with AI

Involving electron spin  in designing electronic devices with new functionalities, and achieving quantum computing with electron spins is among the most ambitious goals of  compassionate artificial superintelligence – AI 5.0.  Utilizing quantum effects like quantum superposition, entanglement, and quantum tunneling for computation is becoming an emerging research field of quantum computing based artificial intelligence. 

Read More »Spin-orbit Coupling Qubits for Quantum Computing and AI

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 CPU. (We also have a tutorial.)
  • CIFAR – The next step up in difficulty is the CIFAR-10 dataset, which contains 60,000 images broken into 10 different classes. For a bigger challenge, you can try the CIFAR-100 dataset, which has 100 different classes.
  • ImageNet – ImageNet hosts a computer vision competition every year, and many consider it to be the benchmark for modern performance. The current image dataset has 1000 different classes.
  • YouTube 8M – Ready to tackle videos, but can’t spare terabytes of storage? This dataset contains millions of YouTube video ID’s and billions of audio and visual features that were pre-extracted using the latest deep learning models.
  • Kaggle Datasets – Open datasets contributed by the Kaggle community. Here, you’ll find a grab bag of topics.
… Read more..