The long-awaited V4 is more efficient and a win for Chinese chipmakers. On Friday, Chinese AI firm DeepSeek released a preview of V4, its long-awaited new flagship model. Notably, the model can process much longer prompts than its last generation, thanks to a new design that helps it handle large amounts of text more efficiently. Like DeepSeek's previous models, V4 is open source, meaning it is available for anyone to download, use, and modify. V4 marks DeepSeek's most significant release since R1, the reasoning model it launched in January 2025. R1, which was trained on limited computing resources, stunned the global AI industry with its strong performance and efficiency, turning DeepSeek from a little-known research team into China's best-known AI company almost overnight.

With the growing role of artificial intelligence in climate and weather research, efficient model training and inference are in high demand. Current models like FourCastNet and AI-GOMS depend heavily on GPUs, limiting hardware independence, especially for Chinese domestic hardware and frameworks. To address this issue, we present a framework for migrating large-scale atmospheric and oceanic models from PyTorch to MindSpore and optimizing for Chinese chips, and evaluating their performance against GPUs. The framework focuses on software-hardware adaptation, memory optimization, and parallelism. Furthermore, the model's performance is evaluated across multiple metrics, including training speed, inference speed, model accuracy, and energy efficiency, with comparisons against GPU-based implementations. Experimental results demonstrate that the migration and optimization process preserves the models' original accuracy while significantly reducing system dependencies and improving operational efficiency by leveraging Chinese chips as a viable alternative for scientific computing. This work provides valuable insights and practical guidance for leveraging Chinese domestic chips and frameworks in atmospheric and oceanic AI model development, offering a pathway toward greater technological independence.

How China is challenging Nvidia's AI chip dominance The US has dominated the global technology market for decades. But China wants to change that. The world's second largest economy is pouring huge amounts of money into artificial intelligence (AI) and robotics. Crucially, Beijing is also investing heavily to produce the high-end chips that power these cutting-edge technologies. Last month, Jensen Huang - the boss of the global AI chip industry leader, Nvidia - warned that China was just nanoseconds behind the US in chip development.

The United States and China have a relationship that could be summed up in a single word as, "complicated." And if you want to use more than one word, "kind of like that video of two dogs growling at each other through a gate." While megacorps just want to make as much money as possible, they have to keep this relationship in mind. Nvidia is in hot water with the US Commerce Department over recent chips designed specifically for the Chinese market. For context, Nvidia is making unbelievably, ridiculously, stupidly huge amounts of money at the moment, providing the hardware backbone for the AI software boom.

Chinese chips could catch up and even stand out in the current Artificial Intelligence (AI) boom, according to a news report published in a U.S. technology magazine Wednesday. In the current wave of enthusiasm for hardware optimized for AI, China's semiconductor industry sees a unique opportunity to establish itself, said the report published by MIT Technology Review, a magazine founded by the Massachusetts Institute of Technology. The article cites Chinese chip "Thinker" as an example. Designed to support neural networks, "Thinker" could recognize objects in images and understand human speech. What makes the chip stand out is its ability to "dynamically tailor its computing and memory requirements to meet the needs of the software being run."