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Explainable AI: Driving Transparency And Trust In AI-Powered Solutions

AI systems are becoming integral to our daily lives. However, the increasing complexity of many AI models, particularly deep learning, […]

As machine learning models grow in complexity and size, deploying them on resource-constrained devices like mobile phones, embedded systems, and

World foundation models (WFMs) bridge the gap between the digital and physical realms. These powerful neural networks can simulate real-world

The sheer size and computational demands of large ML models, like LLMs, pose significant challenges in terms of deployment, accessibility,

Tabular data, the backbone of countless scientific fields and industries, has long been dominated by gradient-boosted decision trees. However, TabPFN

SmolAgents is an open-source Python library developed by Hugging Face for building and running powerful AI agents with minimal code.

AI agents represent a significant advancement in AI, signifying a shift from AI systems that merely assist humans to AI

The rapid development and adoption of Artificial Intelligence (AI), particularly generative AI like Large Language Models (LLMs), has brought forth

Ensuring the ethical use of Large Language Models (LLMs) is paramount to fostering trust, minimizing harm, and promoting fairness in

Ensemble Learning aims to improve the predictive performance of models by combining multiple learners. By leveraging the collective intelligence of

The application of machine learning (ML) in sectors such as healthcare, finance, and social media poses risks, as these domains

Federated Learning (FL) decentralizes the conventional training of ML models by enabling multiple clients to collaboratively learn a shared model