MBZUAI is a global partner in Meta's release of Llama 2, joining organizations like IBM, AWS, Microsoft, and NVIDIA. MBZUAI will provide early feedback and help build the software as a global community. MBZUAI is working on large language models, developing a sustainable LLM named Vicuna, and strengthening infrastructure for LLM-chat evaluation. Why it matters: MBZUAI's involvement promises to bring about a new generation of UAE-born AI advancements built around the Llama 2 ecosystem and fact-checking capabilities.
The Technology Innovation Institute (TII) in Abu Dhabi has launched Falcon 2, a new series of large language models including the Falcon 2 11B and Falcon 2 11B VLM. The Falcon 2 11B outperforms Meta’s Llama 3 (8B) and performs on par with Google’s Gemma 7B, as verified by Hugging Face. Falcon 2 11B VLM is TII's first multimodal model with vision-to-language capabilities and is open-source, making it accessible to developers. Why it matters: This release strengthens the UAE's position in AI research and development, providing open-source models that can be deployed on smaller infrastructures and used in diverse sectors.
IFM has released K2-V2, a 70B-class LLM that takes a "360-open" approach by making its weights, data, training details, checkpoints, and fine-tuning recipes publicly available. K2-V2 matches leading open-weight model performance while offering full transparency, contrasting with proprietary and semi-open Chinese models. Independent evaluations show K2 as a high-performance, fully open-source alternative in the AI landscape. Why it matters: K2-V2 provides developers with a transparent and reproducible foundation model, fostering trust and enabling customization without sacrificing performance, which is crucial for sensitive applications in the region.
Researchers from MBZUAI have released MobiLlama, a fully transparent open-source 0.5 billion parameter Small Language Model (SLM). MobiLlama is designed for resource-constrained devices, emphasizing enhanced performance with reduced resource demands. The full training data pipeline, code, model weights, and checkpoints are available on Github.
Hamad Bin Khalifa University (HBKU) has released Fanar 2.0, the second generation of Qatar's Arabic-centric Generative AI platform, built entirely at QCRI. The core of Fanar 2.0 is Fanar-27B, which was continually pre-trained from a Gemma-3-27B backbone using 120 billion high-quality tokens and only 256 NVIDIA H100 GPUs. Fanar 2.0 includes capabilities like FanarGuard, Aura, Oryx, Fanar-Sadiq, Fanar-Diwan, and FanarShaheen for moderation, speech recognition, vision understanding, Islamic content, poetry generation, and translation. Why it matters: This shows that sovereign, resource-constrained AI development in the Arabic language is possible, producing competitive systems in the region.
MBZUAI has been actively involved in developing AI and generative models, contributing to models like Llama 2, Jais, Vicuna, and LaMini. Professor Preslav Nakov notes Llama 2's improvements in size and carbon footprint over Llama 1. MBZUAI aims to tackle challenges like information accuracy, economic costs, and the scarcity of Arabic online content. Why it matters: MBZUAI's work helps address the limitations of current LLMs, particularly for Arabic, and promotes sustainable AI development in the region.
The Technology Innovation Institute (TII) in the UAE has made its Falcon 40B large language model royalty-free for commercial and research use. Falcon 40B is ranked #1 on Hugging Face's leaderboard for LLMs, outperforming models like LLaMA. The model is now available under the Apache 2.0 license, promoting open access and collaboration in AI. Why it matters: This decision could accelerate AI innovation in the region by providing easier access to a state-of-the-art LLM for both public and private sector applications.