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Results for "AI at Scale"

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.

Sustainable AI at scale

MBZUAI ·

MBZUAI is developing the AI Operating System (AIOS) to reduce the energy, time, and talent costs of AI computing. AIOS aims to make AI models smaller, faster, and more efficient, reducing reliance on expensive hardware and speeding up compute operations. It also enables cost-aware model tuning and standardizes AI modules for reliable operation. Why it matters: By addressing the environmental impact and resource demands of AI, AIOS could promote more sustainable and accessible AI development in the region and globally.

The AI Quorum continues with the first CASL Workshop

MBZUAI ·

MBZUAI's AI Quorum launched its second workshop, "Building Ecosystems for AI at Scale," focusing on AI scalability and business applications. The first CASL workshop aims to define steps for organizations to become self-sufficient with AI and explore new use cases. Speakers include MBZUAI faculty and researchers from CMU, Stanford, KAUST, UC Berkeley, and Google. Why it matters: The workshop highlights the UAE's growing role in fostering AI innovation and bridging the gap between academic research and industry applications in the region.

KAUST advances scalable AI through global collaboration

KAUST ·

KAUST is hosting a workshop on distributed training in November 2025, led by Professors Peter Richtarik and Marco Canini, focusing on scaling large models like LLMs and ViTs. Richtarik's team recently solved a 75-year-old problem in asynchronous optimization, developing time-optimal stochastic gradient descent algorithms. This research improves the speed and reliability of large model training and supports applications in distributed and federated learning. Why it matters: KAUST's focus on scalable AI and federated learning contributes to Saudi Arabia's Vision 2030 goals and addresses critical challenges in AI deployment and data privacy.

JPMorgan Chase AI strategy: US$18B bet paying off - AI News

Bahrain AI ·

The article discusses JPMorgan Chase's global AI strategy, detailing its substantial investment of US$18 billion into artificial intelligence initiatives. It highlights the reported success and payoff of these investments across various business operations. Without specific content provided, the article does not appear to detail any direct initiatives or partnerships within the Middle East region. Why it matters: While relevant to global AI investment trends, the article's specific impact on Middle East AI news and papers cannot be determined without regional context in the content.