Embodied AI

CES 2026 drew 148,000+ attendees and 4,100+ exhibitors, with Chinese companies making up nearly a quarter and standing out in AI hardware and robotics. The post ties their optimism to manufacturing-led iteration speed, not one breakthrough; Lenovo Qira, Nvidia Vera Rubin, and AMD Helios show the race is shifting to cloud and hybrid AI.

He Xiaopeng said XPeng's four 2026 vehicle models will use its Turing AI chip, and Ultra SE and Ultra trims will run a second-gen VLA model for entry-level L4-assisted driving. The post says MAX uses one 750 TOPS chip, Ultra SE uses two, and Ultra uses three; XPeng has entered 60 countries and regions, and VLA 2.0 is already being road-tested in Europe. The real signal is that automakers are pulling chips, models, and deployment in-house as a ceiling-on-performance play, not just a cost move.

At CES 2026, NVIDIA said its six-chip Rubin AI platform is now in full production and cuts token generation cost to about one-tenth of the prior platform. The post cites 50 petaflops NVFP4 inference for Rubin GPUs, 5x gains from its KV-cache storage tier, and the new open autonomous-driving model family Alpamayo; the key signal is production status and cost curve, not the “AI everywhere” framing.

NVIDIA showed at CES that DGX Spark and DGX Station can run 100B to 1T-parameter models locally on deskside systems. The post cites a 35% average llama.cpp speedup, up to 70% NVFP4 compression, 775GB coherent memory on DGX Station, and a 250,000 token/sec pretraining demo. The real signal is the local dev loop: fine-tuning, inference, RAG, coding assistants, and robotics demos all target replacing some cloud iteration with deskside compute.

NVIDIA said the new Mercedes-Benz CLA will be the first U.S. vehicle to ship DRIVE AV with enhanced Level 2 point-to-point driver assistance by the end of this year. The post describes a dual-stack design: end-to-end AI for core driving plus a classical safety stack built on Halos, with OTA upgrades, urban navigation, active collision avoidance, and automated parking. The launch timing is specific, but the post does not disclose pricing, sensor configuration, or the exact ODD.

NVIDIA released open models, datasets and training tools spanning Nemotron, Cosmos, Alpamayo, Isaac GR00T and Clara, plus 10T language tokens, 500K robotics trajectories, 455K protein structures and 100TB of vehicle sensor data. Newly disclosed items include Nemotron Speech/RAG/Safety, Cosmos Reason 2, Transfer 2.5, Predict 2.5, GR00T N1.6 and Alpamayo 1; the key signal is that NVIDIA is opening the data stack across agents, physical AI, AVs and biomedicine.

Former Huawei Cloud embodied robotics lead Zhu Senhua left in Oct. 2025 to found Julao Panshi, which has raised a seed round worth tens of millions of RMB. The company says it uses brain-inspired methods to modify VLA for embodied AI; prototype tests showed 40% higher deployment efficiency in open environments and a 90% cut in data needs for few-shot manipulation. The key point is that it starts as a VLA add-on, while targeting Asia-Pacific service and industrial use cases where overseas customers accept robots that replace only 50%-70% of human labor.