AI

Dive into our in-depth coverage of MWC 2025, highlighting the latest innovations in 5G, AI, IoT, and more. Discover how industry leaders are shaping the future of technology with groundbreaking announcements and developments unveiled during the event.
AI is playing a key role in telecom security by strengthening threat detection, fraud prevention, and regulatory compliance. As 5G, IoT, and edge computing expand, telecom networks face cyber threats such as AI-specific attacks, network intrusions, and data breaches. AI-powered security solutions provide automated threat response, anomaly detection, and AI lifecycle protection, helping telecom providers maintain a secure and resilient network infrastructure.
Broadband leaders and utility companies, including CTA, NCTA, and PG&E, have extended the Voluntary Agreement for Small Network Equipment through 2028. The initiative has already improved home internet device energy efficiency by 89% since 2015, and new targets aim for an additional 10% reduction by 2026. With compliance from major ISPs and device manufacturers, this industry-led effort is making home broadband more sustainable while enhancing performance.
AI is transforming the relationship between telcos and hyperscalers like AWS, Google Cloud, and Microsoft Azure. With AI-driven automation, cloud-native networks, and edge computing, telecom operators are optimizing efficiency, reducing costs, and unlocking new revenue streams. As AI-powered innovations reshape 5G, cybersecurity, and digital services, these strategic partnerships are set to redefine the future of telecom.
Recent advancements in artificial intelligence training methodologies are challenging traditional assumptions about computational requirements and efficiency. Researchers have discovered an “Occam’s Razor” characteristic in neural network training, where models favor simpler solutions over complex ones, leading to superior generalization capabilities. This trend towards efficient training is expected to democratize AI development, reduce environmental impact, and lead to market restructuring, with a shift from hardware to software focus. The emergence of efficient training patterns and distributed training approaches is likely to have significant implications for companies like NVIDIA, which could face valuation adjustments despite strong fundamentals.
Rule-based AI agents operate on predefined rules, ensuring predictable and transparent decision-making, while LLM-based AI agents leverage deep learning for flexible, context-aware responses. This article compares their key features, advantages, and use cases to help you choose the best AI solution for your needs.
AI agents are transforming industries by automating tasks, improving decision-making, and enabling intelligent interactions. This article explores the five core components of AI agents—perception, learning, reasoning, action, and communication—detailing their functions, technologies, and real-world applications across finance, healthcare, retail, and more.
What are AI agents? AI agents are intelligent software systems that perform tasks autonomously, adapt to new data, and make context-aware decisions. Unlike traditional automation, AI agents use machine learning, NLP, and advanced analytics to improve efficiency, reduce costs, and drive business growth. Explore their key features, benefits, and industry applications in this in-depth AI Agent Blog Series.
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.
Alibaba Cloud’s Qwen2.5-Max is the latest AI model shaking up the industry, competing directly with GPT-4o, DeepSeek-V3, and Llama-3.1-405B. Featuring a cost-efficient Mixture-of-Experts (MoE) architecture, Qwen2.5-Max lowers AI infrastructure costs by up to 60% while excelling in reasoning, coding, and mathematical tasks. As China’s AI sector accelerates, this release highlights a shift from brute-force computing to efficiency-driven AI innovation, challenging U.S. and Chinese tech giants alike.
NTT Data is ramping up its India expansion with a new $0.5 billion investment, reinforcing its commitment to making India a top 5 revenue market. With over $3 billion already invested in data centers, submarine cables, and cloud services, the company is now focusing on AI-driven digital infrastructure and IT services. As AI adoption and data localization grow, NTT Data sees India as a key innovation hub and a crucial part of its global strategy.
DeepSeek AI has emerged as a major competitor to OpenAI, offering a low-cost, efficient AI chatbot that has soared to the top of the Apple App Store. Founded in China, DeepSeek’s compute-efficient AI models, aggressive pricing, and open-source approach have disrupted the industry. With AI advancements like DeepSeek-R1 for reasoning tasks and Janus Pro for AI image generation, the startup is reshaping the global AI race—but also raising concerns about cybersecurity, U.S. AI leadership, and regulatory oversight.

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Explore the collaboration between Purdue Research Foundation, Purdue University, Ericsson, and Saab at the Aviation Innovation Hub. Discover how private 5G networks, real-time analytics, and sustainable innovations are shaping the "Airport of the Future" for a smarter, safer, and greener aviation industry....
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Explore how Generative AI is transforming telecom infrastructure by solving critical industry challenges like massive data management, network optimization, and personalized customer experiences. This whitepaper offers in-depth insights into AI and Gen AI's role in boosting operational efficiency while ensuring security and regulatory compliance. Telecom operators can harness these AI-driven...
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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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