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  • What is AI inferencing? - IBM Research
    Part of the Linux Foundation, PyTorch is a machine-learning framework that ties together software and hardware to let users run AI workloads in the hybrid cloud One of PyTorch’s key advantages is that it can run AI models on any hardware backend: GPUs, TPUs, IBM AIUs, and traditional CPUs
  • Matthew Wilson - IBM Research
    I've worked as a Software Engineer for over 15 years, across a broad range of technologies such as IBM Z, CICS, Event-driven architectures, OpenShift, Robotic Process Automation and Machine learning I joined IBM Research in 2023, focussing on Foundation Models for Accelerated Discovery My research interests include inference serving and fine-tuning stacks, explainable AI and learning methods
  • What are foundation models? - IBM Research
    What makes these new systems foundation models is that they, as the name suggests, can be the foundation for many applications of the AI model Using self-supervised learning and transfer learning, the model can apply information it’s learnt about one situation to another
  • Artificial Intelligence - IBM Research
    AI for Code AI for Supply Chain AI Testing Automated AI Causality Computer Vision Conversational AI Explainable AI Fairness, Accountability, Transparency Foundation Models Generative AI Granite Human-Centered AI Knowledge and Reasoning Machine Learning Natural Language Processing Neuro-symbolic AI Speech Trustworthy AI Trustworthy Generation
  • Federated Learning meets Homomorphic Encryption - IBM Research
    Quality machine learning models require quality training data that is sometimes difficult to acquire due to privacy or regulatory constraints Federated learning is a technology that solves this issue by allowing multiple parties to collaboratively train a single machine learning model without sharing any of their training data Federated learning not only improves model generalization, but
  • Topics - IBM Research
    At IBM Research, we’re inventing what’s next in AI, quantum computing, and hybrid cloud to shape the world ahead
  • Quantum Machine Learning: An Interplay Between Quantum Computing and . . .
    Quantum machine learning (QML) is a rapidly growing field that combines quantum computing principles with traditional machine learning It seeks to revolutionize machine learning by harnessing the unique capabilities of quantum mechanics and employs machine learning techniques to advance quantum computing research This paper presents an overview of quantum computing for the machine learning
  • Snap machine learning - IBM Research
    A library that provides high-speed training of popular machine learning models on modern CPU GPU computing systems
  • Introducing AI Fairness 360 - IBM Research
    Machine learning models are increasingly used to inform high-stakes decisions about people Although machine learning, by its very nature, is always a form of statistical discrimination, the discrimination becomes objectionable when it places certain privileged groups at systematic advantage and certain unprivileged groups at systematic disadvantage Bias in training data, due to either
  • Machine Learning for Practical Quantum Error Mitigation
    We benchmark a variety of machine learning models---linear regression, random forests, multi-layer perceptrons, and graph neural networks---on diverse classes of quantum circuits, over increasingly complex device-noise profiles, under interpolation and extrapolation, and for small and large quantum circuits





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