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Results for "Entelligent"

Research to revenue: How academics can excel in business

MBZUAI ·

Dr. Pooja Khosla, formerly an academic, co-founded Entelligent, a climate fintech startup that uses big data and machine learning to help companies manage climate change risk. Khosla recently spoke at MBZUAI, advising academics to translate research into real-world applications, leveraging their unique access to data and analytical thinking. She emphasized the importance of simplifying complex work to make it accessible, noting AI's role in accelerating complex tasks. Why it matters: This highlights the growing trend of translating academic research into practical, impactful business solutions within the AI and climate tech sectors, potentially inspiring more researchers in the region to pursue entrepreneurial ventures.

OmniGen: Unified Multimodal Sensor Generation for Autonomous Driving

arXiv ·

The paper introduces OmniGen, a unified framework for generating aligned multimodal sensor data for autonomous driving using a shared Bird's Eye View (BEV) space. It uses a novel generalizable multimodal reconstruction method (UAE) to jointly decode LiDAR and multi-view camera data through volume rendering. The framework incorporates a Diffusion Transformer (DiT) with a ControlNet branch to enable controllable multimodal sensor generation, demonstrating good performance and multimodal consistency.

Microsoft Azure AI CTO to speak on cognition and intelligence

MBZUAI ·

Microsoft Azure AI CTO Dr. Xuedong Huang will speak at the MBZUAI Executive Program on AI-powered communications. Huang will share his experience in advancing Microsoft's AI stack, from deep learning infrastructure to new user experiences. He has over 170 U.S. patents and has contributed to speech technology, including Windows SAPI and Azure Speech. Why it matters: This talk can help foster knowledge transfer and collaboration between a global AI leader and the UAE's flagship AI university.

Machine Learning Integration for Signal Processing

TII ·

Technology Innovation Institute's (TII) Directed Energy Research Center (DERC) is integrating machine learning (ML) techniques into signal processing to accelerate research. One project used convolutional neural networks to predict COVID-19 pneumonia from chest x-rays with 97.5% accuracy. DERC researchers also demonstrated that ML-based signal and image processing can retrieve up to 68% of text information from electromagnetic emanations. Why it matters: This adoption of ML for signal processing at TII highlights the potential for advanced AI techniques to enhance research and security applications in the UAE.

From cloud computing to cloudless computing

MBZUAI ·

Ang Chen from the University of Michigan presented a talk at MBZUAI on reducing cloud manageability burdens. The talk covered detecting semantic errors before cloud deployment and curating datasets for automated generation of cloud management programs. He introduced the concept of "cloudless computing" to free tenants from cloud management tasks. Why it matters: This research direction could simplify cloud infrastructure management for businesses in the UAE and beyond, allowing them to focus on core activities.

How a team of researchers from MBZUAI is using AI to empower businesses with instant data analytics

MBZUAI ·

MBZUAI researchers developed Data Wise, an AI platform that provides instant data analytics for businesses. The platform uses AI agents and LLMs to analyze raw customer data and generate actionable recommendations. Data Wise aims to address the shortage of data scientists, particularly in the UAE and GCC. Why it matters: This platform democratizes access to advanced analytics, empowering businesses in the region to make data-driven decisions without relying on scarce technical expertise.

Machine Learning Risk Intelligence for Green Hydrogen Investment: Insights for Duqm R3 Auction

arXiv ·

This paper introduces an AI-driven decision support system for green hydrogen investment in Oman, specifically for the Duqm R3 auction. The system uses publicly available meteorological data to predict maintenance pressure on hydrogen infrastructure, creating a Maintenance Pressure Index (MPI). This tool supports regulatory oversight and operational decision-making by enabling temporal benchmarking against performance claims.