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Results for "Yoav Shoham"

Stanford faculty member brings AI knowledge to UAE

MBZUAI ·

Stanford Professor Yoav Shoham, a leading AI expert, will speak at the MBZUAI Executive Program. Shoham will present on lingual cognition and intelligence as part of a virtual class session. He has founded several AI companies, including AI21 Labs, and chairs the AI Index initiative. Why it matters: The participation of globally recognized AI experts like Shoham enhances the prestige and educational value of AI programs in the UAE, attracting talent and fostering innovation.

Intelligence Autonomy via Lifelong Learning AI

MBZUAI ·

Professor Hava Siegelmann, a computer science expert, is researching lifelong learning AI, drawing inspiration from the brain's abstraction and generalization capabilities. The research aims to enable intelligent systems in satellites, robots, and medical devices to adapt and improve their expertise in real-time, even with limited communication and power. The goal is to develop AI systems applicable for far edge computing that can learn in runtime and handle unanticipated situations. Why it matters: This research could lead to more resilient and adaptable AI systems for critical applications in remote and resource-constrained environments, with potential benefits for various sectors in the Middle East.

A vision in color

KAUST ·

Shozo Yokoyama, a biology professor at Emory University specializing in color vision evolution, was interviewed by KAUST. Yokoyama's lab identified amino acids regulating red-green and UV vision in vertebrates. He emphasizes the importance of young scientists developing fresh perspectives on evolution and learning directly from animals. Why it matters: While not directly an AI story, the piece highlights KAUST's broader research focus and its investment in attracting and showcasing international scientific expertise, relevant to building a strong research ecosystem.

CRC Seminar Series - Conor McMenamin

TII ·

Conor McMenamin from Universitat Pompeu Fabra presented a seminar on State Machine Replication (SMR) without honest participants. The talk covered the limitations of current SMR protocols and introduced the ByRa model, a framework for player characterization free of honest participants. He then described FAIRSICAL, a sandbox SMR protocol, and discussed how the ideas could be extended to real-world protocols, with a focus on blockchains and cryptocurrencies. Why it matters: This research on SMR protocols and their incentive compatibility could lead to more robust and secure blockchain technologies in the region.

From Individual to Society: Social Simulation Driven by LLM-based Agent

MBZUAI ·

Fudan University's Zhongyu Wei presented research on social simulation driven by LLMs, covering individual and large-scale social movement simulation. Wei directs the Data Intelligence and Social Computing Lab (Fudan DISC) and has published extensively on multimodal large models and social computing. His work includes the Volcano multimodal model, DISC-MedLLM, and ElectionSim. Why it matters: Using LLMs for social simulation could provide new tools for understanding and potentially predicting social dynamics in the Arab world.

AI Seminar Series: Kajetan Schweighofer

TII ·

The Technology Innovation Institute (TII) is hosting an AI seminar by Kajetan Schweighofer on October 28, 2025, from 11:00 AM to 12:00 PM GST. TII describes itself as a global research center focused on discovery science and transformative technologies. The seminar series is part of TII's efforts to share its developments and research. Why it matters: Such seminars contribute to the growth of the AI ecosystem in the UAE by facilitating knowledge sharing and collaboration.

Disrupting The Drug Development Process Using Multi-Modal Deep Learning and Patient-on-a-Chip Platform

MBZUAI ·

Shahar Harel, Head of AI at Quris, presented a BIO-AI approach to drug safety assessment using a 'patient-on-a-chip' platform. This platform simulates the human body and generates high-frequency microscopy and biochemical data on drug interactions, considering patient genomics and ethnicity. The data is used to train multimodal deep learning models to predict drug safety and provide patient-specific recommendations. Why it matters: This approach offers a potential alternative to animal models, promising faster and more personalized drug development while reducing safety concerns.

On a mission to end fake news

MBZUAI ·

MBZUAI Professor Preslav Nakov is researching methods to combat fake news and online disinformation through NLP techniques. His work focuses on detecting harmful memes and identifying the stance of individuals regarding disinformation. Four of Nakov’s recent papers on these topics were presented at NAACL 2022. Why it matters: This research aims to mitigate the impact of weaponized news and online manipulation, contributing to a more trustworthy information environment in the region and globally.