IBM boosts material discovery to make gadgets more sustainable

PAGs play a vital role in the manufacturing of computer chips. They are also one of several classes of chemical compounds that have recently come under enhanced scrutiny from environmental regulators. Researchers have been racing to create more sustainable ones – but the traditional process of discovering new materials is too slow, too costly, and too risky. So IBM researchers have turned to AI for help – and created new PAGs much, much faster, paving the way to the era of Accelerated Discovery.

Continue reading

Hybrid cloud for accelerating discovery workflows

Hybrid cloud could ultimately enable a new era of discovery, using the best resources available at the right times, no matter the size or complexity of the workload, to maximize performance and speed while maintaining security.

Continue reading

IBM researchers check AI bias with counterfactual text

Our team has developed an AI that verifies other AIs’ ‘fairness’ by generating a set of counterfactual text samples and testing machine learning systems without supervision.

Continue reading

Quantum circuits get a dynamic upgrade with the help of concurrent classical computation

Quantum phase estimation serves as a core building block of many other quantum algorithms due to its potential to provide exponential speedups.

Continue reading

IBM’s roadmap for building an open quantum software ecosystem

Software reliant on this nascent technology, one rooted in the physical laws of matter at the smallest scales, could soon revolutionize computing forever.

Continue reading

IBM’s AI learns to navigate around a virtual home using common sense

In a recent paper introduced at the 2021 AAAI Conference on Artificial Intelligence (AAAI), we describe an AI that trades off ‘exploration’ of the world with ‘exploitation’ of its action strategy to maximize rewards. In Reinforcement Learning, an AI gets a reward – such as a bag of gold behind a locked door in a video game – every time it reaches specific desirable states. We have greatly improved this exploration vs exploitation tradeoff using additional commonsense knowledge – in the form of crowdsourced text. Our work could lead to better mapping and navigation applications, and to a new generation of interactive assistive agents able to reason like humans.

Continue reading

IBM AI helps to break down massive code to ease cloud migration

We use AI to automatically break down the overall application by representing application code as graphs. Our AI relies on Graph Representation Learning – a popular method in deep learning. Graphs are a natural representation for software and applications. We translated the application to a graph where the programs become nodes. Their relationships with other programs become edges and determine the boundary to separate the nodes of common business functionality.

Continue reading

IBM physicist & APS Fellow Heike Riel: from furniture design to quantum computing

Heike Riel's recent appointment as an APS Fellow attests her leadership in science and technology. While many distinguished physicists are part of the APS, only a handful are elected to the fellowship — and even fewer still are female. So when Riel learned last fall that she had been selected, she was deeply touched. “It’s truly an honor and I am humbled to have received this recognition from one of the most highly respected organizations for professionals in physics,” she says. “I am very grateful for my colleagues as well as the teams and institutions that have supported me along the way.”

Continue reading

Mono2Micro AI speeds up app ‘refactoring’ before cloud move

To help the developers that update legacy applications, our team has created Mono2Micro (monolith-to-microservice) – an AI assistant that modernizes legacy applications to help move them to the cloud as microservices. Our tool simplifies and speeds up the often error-prone “application refactoring” process of partitioning and preserving the original semantics of the legacy, monolith applications.

Continue reading

IBM RXN: New AI model boosts mapping of chemical reactions

Today, Nature Machine Intelligence is featuring, "Mapping the Space of Chemical Reactions Using Attention-Based Neural Networks", research from IBM Research Europe and the University of Bern that investigates deep learning models to classify chemical reactions and visualizes the chemical reaction space.

Continue reading

AI goes anonymous during training to boost privacy protection

Our team of researchers from IBM Haifa and Dublin has developed software to help assess privacy risk of AI as well as reduce the amount of personal data in AI training. This software could be of use for fintech, healthcare, insurance, security – or any other industry relying on sensitive data for training.

Continue reading

Setting the bar for variational quantum algorithms using high-performance classical simulations

In the recently published Nature Physics research paper, we, along with our colleague Dr. David Gosset, associate professor at the University of Waterloo's Institute of Quantum Computing, show that certain properties of shallow quantum circuits on a two-dimensional grid of qubits can be simulated classically in time that grows only linearly with the number of qubits.

Continue reading