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Unleashing the potential of ChatGPT in education

December 27, 2024 by Balaji Chandrasekaran, Smrithy Girijakumari Sreekantan Nair,

ChatGPT, an advanced language model powered by artificial intelligence, has emerged as a transformative tool in the field of education. This article explores the potential of ChatGPT in revolutionizing learning and collaboration within educational settings. By leveraging natural language processing and machine learning, ChatGPT offers an interactive and personalized learning … [Read more...] about Unleashing the potential of ChatGPT in education

Learning 101 reloaded: Revisiting the basics for the GenAI era

December 27, 2024 by Junaid Qadir

In this paper, we delve into the transformative landscape of education amidst the disruptive advances of generative AI (GenAI), characterized by an unprecedented capacity to generate new information with tools such as ChatGPT. Building upon my previous publication, “Learning 101: the Untaught Basics,” in this magazine, I interrogate what has changed since then and how learners … [Read more...] about Learning 101 reloaded: Revisiting the basics for the GenAI era

Privacy-preserving distributed learning: Techniques, applications, and future challenges

The rapid increase in data generated by connected devices has created a pressing need for privacy-preserving techniques in distributed learning. This article examines methods that enable collaborative machine learning (ML) while maintaining data security and user privacy. Key approaches such as federated learning (FL), differential privacy (DP), secure multiparty computation (SMPC), and homomorphic encryption (HE) are analyzed for their unique capabilities and various applications. FL facilitates model training across decentralized data sources, ensuring data remain local, while DP mitigates privacy risks by adding controlled noise. SMPC and HE support secure computations on encrypted data, maintaining confidentiality during processing. Despite their effectiveness, these techniques face challenges related to computational complexity, scalability, and regulatory compliance. The article reviews current advancements, practical implementations, and future directions, emphasizing the need for optimized, accessible solutions to enhance data security in distributed systems.

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