University news

Connecting you to the latest AI research and innovation

Stay up-to-date with the latest news from MBZUAI and the wider industry, featuring insights into ongoing University research, innovations, and developments shaping the future of artificial intelligence. The Node gathers expert commentary, press announcements, and initiatives from the University and its partners, keeping you informed on the most relevant trends and breakthroughs.

Low-Complexity NN Technology: Model and Precision Search, Acceleration Circuit, and Applications

Wednesday, 24 April, 2024

Low-Complexity NN Technology: Model and Precision Search, Acceleration Circuit, and Applications

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Quantization represents a popular NN complexity-reduction technology that leverages the (im)precision-tolerant nature of neural network training and inference. Our ongoing efforts have delivered main-stream NNs with only 1-bit weights, e.g., […]

International Olympiad in AI launches to nurture the next generation of AI talent

Wednesday, 24 April, 2024

International Olympiad in AI launches to nurture the next generation of AI talent

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A first-of-its-kind International Olympiad in Artificial Intelligence (AI) competition for high school students will be held this summer, providing a platform to celebrate the next generation of artificial intelligence innovators and developers from around the world.

AI Startup Spotlight Series: LibrAI

Wednesday, 24 April, 2024

AI Startup Spotlight Series: LibrAI

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Can you introduce yourself and share the story behind founding LibrAI? Hello, I’m Xudong Han, founder of LibrAI, a startup committed to advancing AI safety and responsible AI practices. I […]

Extended Reality on-the-move

Tuesday, 23 April, 2024

Extended Reality on-the-move

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Smartphones are our ubiquitous companions, and we often use them on the go, which for an increasingly large portion of the world’s population means: when we’re out and about in […]

Separating fact from fiction with uncertainty quantification

Monday, 22 April, 2024

Separating fact from fiction with uncertainty quantification

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Maxim Panov, assistant professor of ML at MBZUAI, is developing methods that are grounded in theoretical statistics that can be used to improve the utility of language models and other machine learning applications.

Optimizing AI Systems through Cross-Layer Design: A Data-Centric Approach

Monday, 22 April, 2024

Optimizing AI Systems through Cross-Layer Design: A Data-Centric Approach

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As artificial intelligence (AI) transforms various industries, state-of-the-art models have grown exponentially in size and capability. However, previous optimization efforts have primarily concentrated on computational aspects, often overlooking the significant […]

Multi-Omics Data Fusion for Enabling Precision Medicine

Thursday, 18 April, 2024

Multi-Omics Data Fusion for Enabling Precision Medicine

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Large quantities of heterogeneous, interconnected, systems-level, molecular (multi-omic) data are increasingly becoming available. They provide complementary information about cells, tissues and diseases. We need to utilize them to better stratify […]

AI Safety Research

Thursday, 18 April, 2024

AI Safety Research

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We delve into our research on AI safety, focusing on advancements aimed at ensuring the robustness, alignment, and fairness of large language models (LLMs). The talk will start with an […]

Fine-tuning Text-to-Image Models: Reinforcement Learning and Reward Over-Optimization

Wednesday, 17 April, 2024

Fine-tuning Text-to-Image Models: Reinforcement Learning and Reward Over-Optimization

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After a brief overview of my research, I will present three recent results in fine-tuning text-to-image diffusion models. (i) In the first work, we train a reward function using a […]

Cross-modal understanding and generation of multimodal content

Monday, 15 April, 2024

Cross-modal understanding and generation of multimodal content

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Video generation consists of generating a video sequence so that an object in a source image is animated according to some external information (a conditioning label, a driving video, a […]

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