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WEP 2023 takes success to the edge

KAUST ·

KAUST's Winter Enrichment Program (WEP) 2023, themed "Edge – transform the world you know," was held from January 8-19. The program featured a diverse range of topics including AI, renewable energy, and arts, with activities held across KAUST and off-campus. The program, running since 2012, aims to inspire engagement, knowledge, motivation, and leadership within the KAUST community. Why it matters: KAUST's WEP fosters interdisciplinary learning and community engagement, promoting a holistic approach to education and innovation in Saudi Arabia.

SSRC Joins Forces with UNSW to Fortify Systems, Prevent Hacking

TII ·

The Secure Systems Research Center (SSRC) has partnered with the University of New South Wales (UNSW Sydney) to research enhancements and scaling of the seL4 microkernel on edge devices. The collaboration aims to extend the seL4 microkernel to support dynamic virtualization, combining minimal trusted computing base with strong isolation. This will address challenges related to heterogeneous hardware, software, and environmental factors in edge computing. Why it matters: This partnership aims to improve the security of edge devices in critical sectors, addressing vulnerabilities in cyber-physical and autonomous systems.

SSRC Secures seL4 Membership

TII ·

The Secure Systems Research Center (SSRC) has obtained membership in the seL4 Foundation. This membership allows SSRC to participate in and contribute to the open-source development of seL4, a formally verified microkernel OS. SSRC aims to research, contribute to, and advance next-generation high-end edge device environments using seL4's capabilities. Why it matters: This move enhances the UAE's capabilities in developing secure and resilient edge computing solutions, fostering innovation in critical sectors like secure communications and drone technology.

Energy-Efficient and Secure EdgeAI Systems: From Architectures to Applications

MBZUAI ·

Muhammad Shafique from NYU Abu Dhabi discusses building energy-efficient and robust EdgeAI systems. The talk covers trends, challenges, and techniques for optimizing software and hardware stacks. These optimizations aim to enable embodied AI in autonomous systems, IoT-Healthcare, Industrial-IoT, and smart environments. Why it matters: The research addresses key challenges in deploying AI on resource-constrained edge devices in the GCC region, particularly regarding energy efficiency and security.

Technology Innovation Institute Announces Strategic Collaboration with Qualcomm to Advance Edge-AI and Autonomous Robotics

TII ·

Technology Innovation Institute (TII) and Qualcomm Technologies are collaborating to advance edge-AI and autonomous solutions. The partnership will combine TII's robotics expertise with Qualcomm's edge-computing platforms to develop intelligent systems for complex environments. TII will explore Qualcomm's Dragonwing IQ9 and IQ10 platforms to build robots for sectors like energy, mining, construction, and smart cities. Why it matters: This collaboration strengthens the UAE's position in developing advanced autonomous systems and edge-AI technologies for critical industries, fostering innovation and economic growth.

KAUST alumnus appointed vice dean of scientific research at University of Jeddah

KAUST ·

KAUST alumnus Ramy M. Qaisi (Ph.D. '16) has been appointed as the vice dean for scientific research and sustainable development at the University of Jeddah. Qaisi's Ph.D. research at KAUST focused on graphene as an exploratory material under Professor Muhammad Mustafa Hussain. Since joining the University of Jeddah in 2017, he has also co-founded the Department of Science and Technology there. Why it matters: This appointment highlights KAUST's role in developing research leadership within Saudi Arabia's expanding higher education system.

A compact multimodal model for real-time video understanding on edge devices

MBZUAI ·

MBZUAI researchers developed Mobile-VideoGPT, a compact and efficient multimodal model for real-time video understanding on edge devices. The system uses keyframe selection, efficient token projection, and a Qwen-2.5-0.5B language model. Testing showed that Mobile-VideoGPT is faster and performs better than other models while being significantly smaller, and the model and code are publicly available. Why it matters: This research enables on-device AI processing for video, reducing reliance on remote servers and addressing privacy concerns, which can accelerate the adoption of AI in mobile and embedded applications.