
SemiAnalysis: The Huawei-DeepSeek Symbiosis
Right before China’s national day holidays, DeepSeek released Ascend support for TileLang, DeepGEMM, DeepEP, TileKernels, FlashMLA, and DeepSelect.Neither can do this alone. Although they have Pangu, Huawei has no frontier lab to prove their chip can train or infer models, DeepSeek has models but cannot buy the compute it needs. Each supplies exactly what the other lacks: Huawei provides the hardware and native software stack; DeepSeek brings the workloads and engineering needed to make th
Two companies with complementary strengths have formed a partnership: one provides hardware and software infrastructure but lacks frontier AI models to demonstrate the technology, while the other has advanced models but cannot obtain sufficient computing resources. The partnership involves one company releasing software support for the other's chip architecture, exchanging capabilities through kernel-authoring language. This arrangement is expected to deepen over the coming years as both parties work toward building a fully domestic ecosystem. The technical details show how the hardware architecture performs on various computational tasks and how the software has been optimized to work with that hardware.
Want to go deeper than the news? Explore live, cohort-based AI courses taught by practitioners.
Browse AI courses on Maven
Nvidia said the DSX Pod, a prebuilt containerized AI data center, reduces deployment time from six months to 14 days.
Also reported by The Decoder

At Nvidia’s GTC in Berlin, Huang unveiled their new plug-in data center—the DSX Pod—as the key to unlocking Europe’s AI infrastructure lag. Oh, and autonomous humanoid robotics.

Mistral is collaborating with NVIDIA to develop a new generation of AI-native engineering workflows powered by NVIDIA accelerated computing.
Also reported by The Decoder
Tighter integration between the popular open-source platform and Google's specialized processors could lower barriers for researchers training large models.
Also reported by MarkTechPost and SiliconANGLE

Nebius and Nscale are among global technology partners looking to NVIDIA Vera CPUs to build the next wave of infrastructure. Their momentum reflects rapid advancements in agentic computing. Agents do more than generate answers: they retrieve information, run software tools, execute code and evaluate results. Each step depends on fast CPU processing. Vera accelerates that work, helping agents respond faster and enabling data centers to make better use of computing capacity. Vera is designed to

General availability of the instances is coming next month, with planned expansion of availability to Europe — bringing an integrated platform for training, inference and large-scale reinforcement learning to cloud customers. A5X instances bring together NVIDIA Vera Rubin NVL72, NVIDIA ConnectX-9 SuperNICs, Google Cloud Virgo Network and Google Cloud’s fourth-generation advanced liquid-cooling technology for demanding agentic inference and reinforcement learning workloads at scale. Google Cloud