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Results for "Agentic commerce"

Agentic commerce: The quiet revolution in how we buy - Gulf News

Gulf News · Apr 8

Agentic commerce leverages artificial intelligence agents to automate and personalize the buying experience for consumers, marking a significant shift in retail. This 'quiet revolution' is transforming traditional e-commerce by streamlining purchasing decisions and enhancing user convenience. The article likely discusses the implications and adoption of such AI-driven buying methods within the Middle East's consumer market. Why it matters: The integration of AI agents into commerce has the potential to reshape consumer expectations and business strategies across the GCC retail sector.

The rise of agentic AI: homegrown Lawa.AI gains momentum

MBZUAI · Invalid Date

MBZUAI Provost Timothy Baldwin predicts that 2025 will be a breakout year for agentic AI, with 33% of enterprise software applications including agentic AI capabilities by 2028. MBZUAI doctoral students Wafa Alghallabi and Omkar Thawaker have launched Lawa.AI, an AI agent being tested on the university's website to provide faster answers and deeper understanding. Lawa.AI evolved from a research project in multimodal efficiency and LLMs and aims to bridge the gap between people and information in higher education and government. Why it matters: This highlights the UAE's focus on translating AI research into practical applications and the growing importance of agentic AI in various sectors.

DaringFed: A Dynamic Bayesian Persuasion Pricing for Online Federated Learning under Two-sided Incomplete Information

arXiv · May 9

This paper introduces DaringFed, a novel dynamic Bayesian persuasion pricing mechanism for online federated learning (OFL) that addresses the challenge of two-sided incomplete information (TII) regarding resources. It formulates the interaction between the server and clients as a dynamic signaling and pricing allocation problem within a Bayesian persuasion game, demonstrating the existence of a unique Bayesian persuasion Nash equilibrium. Evaluations on real and synthetic datasets demonstrate that DaringFed optimizes accuracy and convergence speed and improves the server's utility.