Peter Waggett

Alessandro Curioni

Srinivasan Arunachalam

Stefan Wörner

David Sutter

Yunchao Liu

Kristan Temme

Panagiotis Barkoutsos

Anthony Annunziata

Ivano Tavernelli

Amira Abbas

Junye Huang

News

Research

IBM Quantum Challenge generates better solutions than challenge creators thought possible

The power of quantum neural networks

Quantum kernels can solve machine learning problems that are hard for all classical methods

IBM welcomes CERN as a new hub in the IBM Quantum Network

The Discovery Accelerator comes to Europe

Quantum

NeurIPS 2020

APS March Meeting 2021

ASP-DAC 2021

IJCAI 2021

Quantum Error Correction

Quantum Chemistry

Machine Learning

Quantum Community

Quantum Information Science

Quantum Circuits and Software

Materials Discovery

Accelerated Discovery

Quantum Machine Learning

We now know that quantum computers have the potential to boost the performance of machine learning systems, and may eventually power efforts in fields from drug discovery to fraud detection. We're doing foundational research in quantum ML to power tomorrow’s smart quantum algorithms.

Machine learning uses data to teach AI systems to imitate the way that humans learn. They can find the signal in the noise of big data, helping businesses improve their operations. We've been in the field since since the beginning: IBMer Arthur Samuel even coined the term “Machine Learning” back in 1959. 

Quantum advantage requires innovation at every layer of the quantum stack. Our software team works alongside the hardware developers to build an expansive library of quantum circuits and to create programming tools so that anyone can develop their own quantum software.

Quantum computing represents a paradigm shift in the types of problems we can solve. Getting it right requires deep understanding of the underlying theory. We’re exploring the fundamentals of quantum science, from entanglement and superposition to the development of novel quantum algorithms. 

To trust AI systems, explanations can go a long way. We’re creating tools to help debug AI, where systems can explain what they’re doing. This includes training highly optimized, directly interpretable models, as well as explanations of black-box models and visualizations of neural network information flows.

Explainable AI

We’re creating tools to help AI systems explain why they made the decisions they did. 

IBM and the UK government will announce the Hartree National Centre for Digital Innovation.jpg

Quantum Machine Learning

Our work

IBM welcomes CERN as a new hub in the IBM Quantum Network

Quantum kernels can solve machine learning problems that are hard for all classical methods

The power of quantum neural networks

IBM Quantum Challenge generates better solutions than challenge creators thought possible

Publications

Quantum Neural Networks for Speech and Natural Language Processing

Quantum computing models for artificial neural networks

The power of quantum neural networks

A co-design framework of neural networks and quantum circuits towards quantum advantage

When Machine Learning Meets Quantum Computers: A Case Study

Practical application improvement to Quantum SVM: theory to practice

Related teams

Explainable AI

Machine Learning

Quantum Circuits and Software

Quantum Information Science