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AI for Good

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AI for Good is a year-round digital platform where AI innovators and problem owners learn, build and connect to identify practical AI solutions to advance the United Nations' Sustainable Development Goals (SDGs).

We have less than 10 years to solve the United Nations’ Sustainable Development Goals (SDGs). AI holds great promise by capitalizing on the unprecedented quantities of data now being generated on sentiment behaviour, human health, commerce, communications, migration and more.

The goal of AI for Good is to identify practical applications of AI to advance the United Nations Sustainable Development Goals and scale those solutions for global impact. It’s the leading action-oriented, global & inclusive United Nations platform on AI.

AI for Good is organized by ITU in partnership with 40 UN Sister Agencies and co-convened with Switzerland.  Visit the site here and join the platform if interested.

Curated by mokiethecat

AI is getting bigger, but does bigger always mean better? As Large Language Models (LLMs) dominat

Challenging the resource-intensive "bigger is better" trend of Large Language Models (LLMs), this webinar introduced the Expressive Neural Network (ENN). This novel architecture rethinks activation functions using classical signal processing (Discrete Cosine Transform), resulting in enhanced flexibility, faster convergence, and significantly smaller, more energy-efficient AI models.

ENNs demonstrate how traditional signal processing can inspire next-generation AI, enabling efficient edge computing in resource-constrained environments. This approach prioritizes expressiveness over sheer size for future neural networks. The webinar featured speaker Ana Pérez-Neira, moderated by Ian F. Akyildiz and Alessia Magliarditi. It was organized by the ITU Journal on Future and Evolving Technologies (ITU-J FET).

EarthSayers Ian F. Akyildiz; Alessia Magliarditi; Ana Pérez-Neira

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