AI

IBM Research AI: Advancing AI for industry and society

AI helps explain your microbiome

Newly published research describes an Explainable AI to help understand the link between skin microbiome composition and personal wellbeing.

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Introducing the AI chip leading the world in precision scaling

We’ve made strides in delivering the next-gen AI computational systems with cutting-edge performance and unparalleled energy efficiency.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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Boosting our understanding of microbial world with software repurposing

In our latest paper published in the Microbiome Journal, we propose a way to improve the speed, sensitivity and accuracy of what’s known as microbial functional profiling – determining what microbes in a specific environment are capable of.

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Moving beyond the self-reported scale: Objectively measuring chronic pain with AI

Together with Boston Scientific, we are presenting research that details the feasibility and progress towards our new pain measurement method at the 2021 North American Neuromodulation Society Annual Meeting.

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