MBZUAI launched the AI Quorum, a winter series from October 2022 to March 2023, to stimulate AI research. The first session, led by Professor Michael Jordan, focused on collaborative learning with around 20 research experts. Discussions covered the use of edge devices like cell phones and hospitals providing data to build large models, as well as risks like free-riding and adversarial attacks. Why it matters: The AI Quorum initiative positions MBZUAI as a hub for global AI collaboration, addressing key challenges and opportunities in collaborative learning for real-world applications.
MBZUAI hosted the Second Workshop on Collaborative Learning as part of the AI Quorum in Abu Dhabi, focusing on collaborative and federated learning for sustainable development. Researchers discussed applications in medicine, biology, ecological conservation, and humanitarian aid. Eric Xing highlighted the potential of large biology models, similar to LLMs, to revolutionize biological data analysis. Why it matters: This workshop underscores the UAE's commitment to advancing AI research in crucial sectors like healthcare and sustainability through collaborative learning approaches.
Sai Praneeth Karimireddy from UC Berkeley presented a talk on building planetary-scale collaborative intelligence, highlighting the challenges of using distributed data in machine learning due to data silos and ethical-legal restrictions. He proposed collaborative systems like federated learning as a solution to bring together distributed data while respecting privacy. The talk addressed the need for efficiency, reliability, and management of divergent goals in these systems, suggesting the use of tools from optimization, statistics, and economics. Why it matters: Collaborative AI systems can unlock valuable distributed data in the region, especially in sensitive sectors like healthcare, while ensuring privacy and addressing ethical concerns.
A global consortium of universities and research institutions has launched a collaborative project to investigate the application of artificial intelligence in education. The project aims to explore how AI can be used to personalize learning, improve student outcomes, and enhance teaching practices. Participating institutions will share data, resources, and expertise to develop AI-powered educational tools and strategies. Why it matters: This initiative could accelerate the development and adoption of effective AI solutions tailored to the specific needs of diverse educational contexts in the Middle East.
Dr. Yali Du from King's College London will give a presentation on learning to cooperate in multi-agent systems. Her research focuses on enabling cooperative and responsible behavior in machines using reinforcement learning and foundation models. She will discuss enhancing collaboration within social contexts, fostering human-AI coordination, and achieving scalable alignment. Why it matters: This highlights the growing importance of research into multi-agent systems and human-AI interaction, crucial for developing AI that integrates effectively and ethically into society.
Insyab, a startup specializing in collaborative robotics and drone solutions, was founded by KAUST alumnus Dr. Ahmed Bader and KAUST Professor Mohamed-Slim Alouini. Their flagship product, AirFabric™, is a broadband ultra-low-latency wireless connectivity solution enabling teams of unmanned vehicles to collaborate effectively. The technology allows robots to interact in real time and share learning, unlocking a "1+1=3" value proposition. Why it matters: This highlights KAUST's role in fostering deep-tech entrepreneurship and developing innovative solutions for industrial automation in the region.