Institute of Foundation Models

Institute of Foundation Models


Message from the President

The mission of the IFM is to position our academic research at the forefront of Generative AI development, and ground it on substantial societal needs. This institute will be the hub of activity for fundamental research in areas we already have pioneered with the ability to focus those energies now into a wide spectrum of powerful foundation models such as the GPTs for lingual, visual, and biological data that can be used in industries dedicated to healthcare, climate change and sustainability, and in turn advance the innovation of foundation models itself. The options are endless and we look forward to partnering with others in this area.

department-chair

Professor Eric Xing

MBZUAI President

Who We Are

We are a dedicated research hub for building, understanding, using, and risk-managing Foundation Models including the large language models underlying the ChatGPTs, and transformers pre-trained on biological data underlying those tools like AlphaFold2, and many more to emerge. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contribution to UAE’s knowledge-driven economy.

Why Foundation Models

Foundation Models stand as a bedrock of advanced AI, enabling versatile and deeper machine insights, transformative content generation capability, and potentially super-human problem-solving skills. We must make this new technology affordable, safe, ethical, standardizable, and certifiable.

Our Values

Research

Pursuing advanced studies to push AI frontiers.

Talent

Cultivating and nurturing top AI innovators.

Artifacts

A Diverse Array of Foundational Models.

Empower

Enabling others through AI capabilities and insights.


Projects

LLM360: Open-source LLMs for Transparency, Trust, and Collaborative Research

LLM360 is a groundbreaking open-source framework aimed at enhancing transparency and collaboration in AI research. It offers detailed insights by providing full access to training processes, including checkpoints, datasets and source code for models like Amber and CrystalCoder. LLM360 aims to democratize LLMs by offering a framework for open-source LLMs to foster transparency, trust, and collaborative research.

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Vicuna: A “Decarbonized” Vet High-Performance LLM

Vicuna is a lightweight, open-source LLM chatbot fine-tuned with user-shared conversations from ShareGPT, surpasses 90%* quality of OpenAI ChatGPT and Google Bard, outperforming models like LLaMA and Stanford Alpaca in over 90%* of cases, all achieved at a training cost of approximately $300.

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GET: A Foundation Model for Genome

GET is a foundation model for transcriptional regulation that accurately predicts gene expression in diverse human cell types, adapts to different conditions and sequencing platforms, and identifies regulatory elements and interactions, making it a valuable tool for gene regulation analysis.

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JAIS – World’s Best Arabic LLM

Jais, an open-source Arabic large language model, surpasses existing models in quality and competes strongly with English models despite limited English data, serving over 400 million Arabic-speaking individuals worldwide.

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ClimateGPT: Our Commitment to the COP28’s Mission on Sustainability

ClimateGPT is a specialized LLM for conversations related to Climate Change and Sustainability topics in both English and Arabic languages.

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GLaMM: A Multimodal Foundation Model with Pixel Grounding Capabilities

The first LLM with pixel-level visual grounding capabilities with the flexibility to process both image and region inputs.

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The “Zoo” of LLMs

Visit our “Zoo” of LLMs where, a diverse ensemble of foundational models are being developed, forming a versatile and dynamic ecosystem for a wide range of language/visual/audio-related tasks and applications.

Coming Soon

COMPRER: A multi-modal foundation model for cardiovascular disease

COMPRER is a foundation model for enhancing medical-image representation, diagnostic inferences, and prognosis of diseases. It integrates high-resolution fundus images and ultrasound images of the carotid arteries into a single model that encompasses both modalities. The model achieves higher scores in evaluating medical conditions and predicting future cardiovascular events compared to existing models.

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