A recent talk at MBZUAI discussed "Green Learning" and Operational Neural Networks (ONNs) as efficient alternatives to CNNs. ONNs use "nodal" and "pool" operators and "generative neurons" to expand neuron learning capacity. Moncef Gabbouj from Tampere University presented Self-Organized ONNs (Self-ONNs) and their signal processing applications. Why it matters: Exploring more efficient AI models is crucial for sustainable development of AI in the region, as it addresses computational resource constraints and promotes broader accessibility.
Dr. Tarek Ali Fadaak, a Shura Council member, discussed the importance of environmental balance and improved resource management in Saudi urban planning during a 2018 KAUST lecture. He highlighted challenges like insufficient and poorly utilized open spaces in Saudi cities, emphasizing the need for aesthetic improvements and more public spaces. Fadaak stressed the importance of investing in the education of Saudi youth to drive future development and address these urban planning challenges. Why it matters: This underscores the ongoing focus on sustainable urban development and the role of Saudi talent in shaping future cities within the Kingdom, aligning with Vision 2030 goals.
MBZUAI's Class of 2023 valedictorian, Klea Ziu, credits her meditation practice for balancing her studies in machine learning. Ziu, the first Albanian graduate from MBZUAI, was among 59 graduates receiving master's degrees in computer vision, machine learning, and NLP. She will represent MBZUAI at COP28 as part of the Climate Ambassador Program, focusing her AI research on reducing carbon dioxide production in the oil and gas industry. Why it matters: This highlights MBZUAI's focus on attracting international talent and applying AI research to sustainability challenges relevant to the UAE and the broader region.
MBZUAI researchers are using federated learning to optimize energy production and use in microgrids, balancing individual and grid-level needs with a focus on sustainability. They presented a multi-agent framework called MAHTM at the ICLR 2023 workshop, aiming to minimize the carbon footprint of electrical grids. The system uses three layers of decision-making agents to minimize cost, decrease carbon impact, and balance production. Why it matters: This research offers a novel approach to integrating renewable energy sources into existing grids, potentially accelerating the transition to more sustainable energy systems in the region and globally.
Professor Jeffrey Sachs of Columbia University gave a keynote at KAUST's Winter Enrichment Program (WEP) 2022 on "resilience." He emphasized the need to end greenhouse gas emissions by mid-century through decarbonizing the energy system. Sachs highlighted the importance of science and technology solutions, especially in adapting to climate change. Why it matters: The talk underscores the importance of KAUST's research initiatives, such as the Circular Carbon Initiative, in developing technologies for carbon capture and utilization, aligning with Saudi Arabia's net-zero targets.
KAUST has launched the first school-based mangrove nursery in the Middle East, located at The KAUST School (TKS) with 1,000 seedlings. TKS students collected, planted, and nurtured mangrove propagules under HSE guidance to create a living classroom. The first generation of nursery-grown mangroves is now ready for planting on the shoreline. Why it matters: The initiative reflects KAUST’s commitment to environmental awareness and supports Saudi Arabia’s Vision 2030 environmental goals.
MBZUAI President Eric Xing led a global collaboration to develop Vicuna, an LLM alternative to GPT-3 addressing the unsustainable costs of training LLMs. OpenAI CEO Sam Altman acknowledged Abu Dhabi's role in the global AI conversation, building off of achievements like Vicuna. Xing and colleagues are publishing research at MLSys 2023 on "cross-mesh resharding" to improve computer communication in deep learning, aiming for low-carbon, affordable, and miniaturized AI. Why it matters: This research signals a push towards sustainable AI development in the region, emphasizing efficiency and reduced environmental impact.
MBZUAI's Qirong Ho and colleagues are developing an Artificial Intelligence Operating System (AIOS) for decarbonization, aiming to reduce energy waste in AI development. The AIOS focuses on improving communication efficiency between machines during AI model training, as inefficient communication leads to prolonged tasks and increased energy consumption. This system addresses the high computing power demands of large language models like ChatGPT and LLaMA-2. Why it matters: By optimizing energy usage in AI development, the AIOS could significantly reduce the carbon footprint of AI technologies in the region and globally.