Steer Studios, the global games studio arm of Savvy Games Group, held a company day at KAUST to recruit talent. Savvy Games Group aims to invest SAR 142 billion to establish 250 game companies in Saudi Arabia and create 39,000 jobs. Steer Studios representatives interviewed and networked with KAUST students, seeking skills in marketing, computer engineering, 3D art, animation, and game design. Why it matters: This event highlights Saudi Arabia's commitment to developing its gaming and esports sector, aligning with Vision 2030 and creating opportunities for local talent in a rapidly growing industry.
Nicu Sebe from the University of Trento presented recent work on video generation, focusing on animating objects in a source image using external information like labels, driving videos, or text. He introduced a Learnable Game Engine (LGE) trained from monocular annotated videos, which maintains states of scenes, objects, and agents to render controllable viewpoints. Why it matters: This talk highlights advancements in cross-modal AI, potentially enabling new applications in gaming, simulation, and content creation within the region.
MBZUAI researchers presented a new approach to video question answering at ICCV 2023. The method leverages insights from analyzing still images to understand video content, potentially reducing the computational resources needed for training video question answering models. Guangyi Chen, Kun Zhang, and colleagues aim to apply pre-trained image models to understand video concepts. Why it matters: This research could lead to more efficient and accessible video analysis tools, benefiting fields like healthcare and security where video data is abundant.
KAUST Professor Peter Markowich discusses the role of mathematics in football, describing a match as a random process with a drift. The randomness stems from player conditions, referee decisions, weather, and more, while the drift represents the higher probability of the better team winning. He notes that the complexity arising from 11 players on each side increases the randomness compared to sports like tennis. Why it matters: This perspective highlights the interplay of chance and skill in sports, offering a mathematical lens for understanding game dynamics.
MBZUAI's BioMedIA lab, led by Mohammad Yaqub, is developing AI solutions for healthcare challenges in cardiology, pulmonology, and oncology using computer vision. Yaqub's previous research analyzed fetal ultrasound images to correlate bone development with maternal vitamin D levels. The lab is now applying image analysis to improve the treatment of head and neck cancer using PET and CT scans. Why it matters: This research demonstrates the potential of AI and computer vision to improve diagnostic accuracy and accessibility of healthcare in the region and beyond.
The paper introduces MIRAGE, a framework for evaluating LLMs' ability to simulate human behaviors in murder mystery games. MIRAGE uses four methods: TII, CIC, ICI and SCI to assess the LLMs' role-playing proficiency. Experiments show that even GPT-4 struggles with the complexities of the MIRAGE framework.
MBZUAI researchers created a new benchmark dataset called TextGames to evaluate the reasoning abilities of LLMs. The dataset uses simple, text-based games requiring skills like pattern recognition and logical thinking. LLMs struggled with the hardest questions, suggesting limitations in their reasoning capabilities despite advancements in language understanding. Why it matters: This research highlights the need for specialized reasoning models and benchmarks that go beyond memorization to truly test AI's problem-solving abilities.