G42 and its portfolio company Analog have signed non-binding Memoranda of Understanding (MoUs) with Advanced Machine Intelligence (AMI Labs), co-founded by AI pioneer Yann LeCun. The agreements, signed during the UAE-France Business Dialogue, focus on frontier AI research, advanced compute infrastructure, sovereign cloud, and industrial applications, specifically the development of 'world models' for physical environments. This collaboration aims to merge AMI Labs' research with G42's AI infrastructure and Analog's Physical Intelligence platform to apply world models across various industries. Why it matters: This partnership signifies a major step in the UAE's pursuit of cutting-edge AI research, particularly in 'Physical Intelligence' and AI's interaction with the real world, reinforcing international technological cooperation between the UAE and France.
Pascal Fua from EPFL presented an approach to implementing convolutional neural nets that output complex 3D surface meshes. The method overcomes limitations in converting implicit representations to explicit surface representations. Applications include single view reconstruction, physically-driven shape optimization, and bio-medical image segmentation. Why it matters: This research advances geometric deep learning by enabling end-to-end trainable models for 3D surface mesh generation, with potential impact on various applications in computer vision and biomedical imaging in the region.
Professor Le Song has joined MBZUAI as Deputy Department Chair of the Machine Learning Department. He brings decades of experience from institutions like Georgia Tech, Google Research, and Carnegie Mellon University. Le Song's research focuses on machine learning methods and algorithms for complex and dynamic data, with over 160 papers published in top ML conferences. Why it matters: This appointment bolsters MBZUAI's machine learning department and signals the university's commitment to attracting world-class AI talent to the UAE.
TII Chief Researcher Mérouane Debbah and MBZUAI President Eric Xing visited École Polytechnique in France to discuss AI research and training. They reviewed AI projects and opportunities to increase the visibility of UAE-led research. The meeting aimed to strengthen collaboration between MBZUAI, TII, and École Polytechnique. Why it matters: Such partnerships can foster knowledge exchange and accelerate AI innovation in the UAE by leveraging international expertise.
Yanwei Fu from Fudan University will present research on multimodal models, robotic grasping, and fMRI neural decoding. Topics include few-shot learning, object-centered self-supervised learning, image manipulation, and visual-language alignment. The research also covers Transformer compression and applications of large models with MVS 3D modeling in robotic arm grasping. Why it matters: While the talk is not directly about Middle East AI, the topics covered are core to advancing AI research and applications in the region.
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.
Prof. Mérouane Debbah of the Technology Innovation Institute (TII) warns that current AI development relies on unsustainable, energy-intensive "bruteforce computing." He argues that the field needs more energy-efficient algorithms instead of simply scaling up GPUs. Debbah suggests neuromorphic computing as a potential solution, drawing inspiration from the human brain's energy efficiency. Why it matters: This critique highlights a crucial sustainability challenge for AI in the GCC and globally, as the region invests heavily in compute-intensive AI models.
Patrick van der Smagt, Director of AI Research at Volkswagen Group, discussed the use of generative machine learning models for predicting and controlling complex stochastic systems in robotics. The talk highlighted examples in robotics and beyond and addressed the challenges of achieving quality and trust in AI systems. He also mentioned his involvement in a European industry initiative on trust in AI and his membership in the AI Council of the State of Bavaria. Why it matters: Understanding control in robotics, along with trust in AI, are key issues for further development of autonomous systems, especially in industrial applications within the GCC region.