Hugging Face

Fujitsu’s latest generative AI breakthrough compresses large language models by 94% using 1-bit quantization, tripling inference speed and retaining 89% accuracy. Combined with brain-inspired knowledge distillation, these enhancements power high-speed, low-cost AI for CRM, image recognition, and edge deployments, all while reducing energy demands.
The GSMA Foundry has launched Open-Telco LLM Benchmarks, an open-source AI evaluation framework designed to enhance telecom-specific large language models (LLMs). Supported by Hugging Face, The Linux Foundation, Deutsche Telekom, SK Telecom, and more, this initiative aims to improve AI efficiency, security, and compliance in 5G and 6G networks. Learn how this industry-wide benchmark is shaping the future of telecom AI innovation.
AI agents are transforming industries in 2025, but scaling them efficiently without Large Language Models (LLMs) is impossible. LLMs provide critical capabilities such as reasoning, knowledge retrieval, and contextual understanding that power AI automation. This detailed article explores why LLMs are essential for AI agents, the role of Retrieval-Augmented Generation (RAG), optimization strategies, and the best free resources to master LLMs.

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Telecom networks are facing unprecedented complexity with 5G, IoT, and cloud services. Traditional service assurance methods are becoming obsolete, making AI-driven, real-time analytics essential for competitive advantage. This independent industry whitepaper explores how DPUs, GPUs, and Generative AI (GenAI) are enabling predictive automation, reducing operational costs, and improving service quality....
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Article & Insights
This article explores the deployment of 5G NR Transparent Non-Terrestrial Networks (NTNs), detailing the architecture's advantages and challenges. It highlights how this "bent-pipe" NTN approach integrates ground-based gNodeB components with NGSO satellite constellations to expand global connectivity. Key challenges like moving beam management, interference mitigation, and latency are discussed, underscoring...
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