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Mass production of AI solutions

MBZUAI ·

MBZUAI Assistant Professor Qirong Ho is researching AI operating systems to standardize algorithms and enable non-experts to create AI applications reliably. He emphasizes that countries mastering mass production of AI systems will benefit most from the Fourth Industrial Revolution. Ho is co-founder and CTO at Petuum Inc., an AI startup creating standardized building blocks for affordable and scalable AI production. Why it matters: This research aims to democratize AI development and promote widespread adoption across industries in the UAE and beyond.

ML Systems For Many

MBZUAI ·

Qirong Ho, co-founder and CTO of Petuum Inc., will be contributing to the "ML Systems for Many" initiative. Petuum is recognized for creating standardized building blocks for AI assembly. Ho also holds a Ph.D. from Carnegie Mellon University and is part of the CASL open-source consortium. Why it matters: Showcases the ongoing efforts to democratize AI development and deployment, making it more accessible and sustainable, although the specific initiative is not further detailed.

Optimizing AI Systems through Cross-Layer Design: A Data-Centric Approach

MBZUAI ·

A Duke University professor presented a data-centric approach to optimizing AI systems by addressing the memory capacity and bandwidth bottleneck. The presentation covered collaborative optimization across algorithms, systems, architecture, and circuit layers. It also explored compute-in-memory as a solution for integrating computation and memory. Why it matters: Optimizing AI systems through a data-centric approach can improve efficiency and performance, critical for advancing AI applications in the region.

Inspiring the next generation of machine learning systems graduates

MBZUAI ·

Dr. Qirong Ho joins MBZUAI as an assistant professor focusing on machine learning systems, aiming to inspire students to specialize in this area. He emphasizes the importance of AI software systems for turning AI prototypes into real products, addressing a skills imbalance in the AI field. MBZUAI is expanding its machine learning department and finalizing its Centre for Integrative AI. Why it matters: This highlights MBZUAI's focus on developing expertise in AI infrastructure and systems, crucial for translating research into practical applications within the UAE and beyond.

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.

AI and the silver screen: how cinema has imagined intelligent machines

MBZUAI ·

This article discusses how AI has been portrayed in cinema, from early automatons in Metropolis to modern depictions of digital consciousness in Blade Runner and Terminator. It explores themes such as autonomy, intelligence, and responsibility. The films mentioned capture themes that still shape public imagination. Why it matters: Examining AI through the lens of cinema provides insights into societal hopes, fears, and questions about humanity's relationship with intelligent machines, influencing public perception and ethical considerations.

Climate conscious computing

MBZUAI ·

MBZUAI's Qirong Ho and colleagues are developing an Artificial Intelligence Operating System (AIOS) for decarbonization, aiming to reduce energy waste in AI development. The AIOS focuses on improving communication efficiency between machines during AI model training, as inefficient communication leads to prolonged tasks and increased energy consumption. This system addresses the high computing power demands of large language models like ChatGPT and LLaMA-2. Why it matters: By optimizing energy usage in AI development, the AIOS could significantly reduce the carbon footprint of AI technologies in the region and globally.