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NVIDIA and AMD will launch AI chips in China by July 2025, including the B20 and Radeon AI PRO R9700, tailored to comply with U.S. export rules. With performance capped under regulatory thresholds, these GPUs aim to support Chinaโ€™s enterprise AI needs without violating tech trade restrictions. NVIDIA is also rolling out a lower-cost chip based on Blackwell architecture, signaling a shift toward compliant yet capable AI compute options in restricted markets.
In Episode 222 of The G2 on 5G, analysts Will Townsend and Anshel Sag cover T-Mobileโ€™s 6G equipment testing, Googleโ€™s mid-range Pixel 9a, Vodafoneโ€™s 200M IoT milestone, the GSAโ€™s RedCap group, AT&T’s satellite trials for FirstNet, and MediaTekโ€™s powerful new chipsets for phones and Chromebooks.
Qubrid AI unveils Version 3 of its AI GPU Cloud, featuring smarter model tuning, auto-stop deployment, and enhanced RAG UIโ€”all designed to streamline AI workflows. The company also teased its upcoming Agentic Workbench, a new toolkit to simplify building autonomous AI agents. Along with App Studio and data provider integration, Qubrid is positioning itself as the go-to enterprise AI platform for 2025.
The integration of tariffs and the EU AI Act creates a challenging environment for the advancement of AI and automation. Tariffs, by increasing the cost of essential hardware components, and the EU AI Act, by increasing compliance costs, can significantly raise the barrier to entry for new AI and automation ventures. European companies developing these technologies may face a double disadvantage: higher input costs due to tariffs and higher compliance costs due to the AI Act, making them less competitive globally. This combined pressure could discourage investment in AI and automation within the EU, hindering innovation and slowing adoption rates. The resulting slower adoption could limit the availability of crucial real-world data for training and improving AI algorithms, further impacting progress.
AMD and Rapt AI are partnering to improve AI workload efficiency across AMD Instinct GPUs, including MI300X and MI350. By integrating Rapt AI’s intelligent workload automation tools, the collaboration aims to optimize GPU performance, reduce costs, and streamline AI training and inference deployment. This partnership positions AMD as a stronger competitor to Nvidia in the high-performance AI GPU market while offering businesses better scalability and resource utilization.
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. Discover key insights, real-world case studies, and strategic actions for telecom leaders. Download the Full Report Now to stay ahead in AI-powered service assurance.
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.
Artificial Intelligence (AI) took center stage at Davos 2025, influencing discussions on governance, AI agents, and Chinaโ€™s growing AI presence. As we approach MWC 2025 in March, AI is expected to dominate key sessions on AI-driven telecom innovations, security risks, and business applications. With major players like Salesforce, Nvidia, and emerging Chinese startups shaping the landscape, AIโ€™s expanding role in industries and global policies is more critical than ever.
LG is launching its 2025 LG gram laptop lineup at CES 2025, featuring the brand’s first hybrid AI integration. Combining on-device AI for fast, secure local processing with cloud-based AI powered by GPT-4o, these laptops deliver personalized productivity through features like Time Travel for revisiting files and calendar/email management. Powered by Intelโ€™s latest processors, the lineup includes the flagship LG gram Pro with Arrow Lake CPUs and NVIDIA RTX 4050 graphics, and the ultra-portable LG gram Pro 2-in-1, which has won a CES Innovation Award. With sleek designs and cutting-edge features, LG gram laptops aim to redefine performance and portability.
Nvidia has completed its acquisition of Run:ai, an Israeli AI infrastructure startup. The deal highlights Nvidiaโ€™s commitment to advancing AI innovation by optimizing GPU utilization and making Run:aiโ€™s software open source. This move is set to enhance scalability and efficiency across diverse hardware ecosystems, empowering organizations globally.
T-Mobile and NVIDIA are at the forefront of AI-driven 6G innovation, establishing a groundbreaking partnership to integrate artificial intelligence into 6G radio access networks (RAN). Through the AI RAN Innovation Center and NVIDIAโ€™s AI Aerial platform, T-Mobile aims to create smarter, more adaptive networks, generating new revenue streams and enhancing performance across diverse applications. This collaboration marks a pivotal step in telecomโ€™s AI evolution, positioning T-Mobile to lead in future network standardization and innovation through partnerships with industry giants like Ericsson, Nokia, and Microsoft.

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Whitepaper
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....
Whitepaper
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....
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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