Pascini said it closed a Series B round of over RMB 1 billion, bringing its valuation above RMB 10 billion. Lead investors include Huangpujiang Capital, Kaitai Capital, and Xinan Capital; the post says Pascini will use 10-billion-scale real-world multimodal data to train its VTLA model, but does not disclose model details.

Zhongke Diwuji completed Pre-A and Pre-A+ rounds worth hundreds of millions of yuan within one month, and became a Unitree core ecosystem partner in Jan 2026. Since 2025, it has supplied the "brain" model for Unitree robots; the company says its FAM models use secondary pretraining and heatmap alignment to learn new tasks from 3-5 real-robot demos, with 97% success on basic tasks. The signal to watch is commercialization: it is moving from POC to power inspection, industrial handling, and retail deployments, charging robot OEMs per-device license.

Waymo placed a $6.25 task on a delivery platform to send a rider 1 km away to close a robotaxi door, with another $5 after completion. The post frames this as software dispatching human labor, not a one-off gig, and argues platform workers are becoming a human API inside automated workflows. The point to watch is the AI-plus-labor loop; the post does not disclose Waymo's scale, frequency, or formal product design.

The piece argues China has embedded AI into manufacturing, with 30,000+ smart factories, and over half of all industrial robots installed globally in 2024 going to Chinese plants. It cites shop-floor data: Zeekr's Ningbo plant uses 800+ robots, Xiaomi says its Beijing factory produces one car every 76 seconds, while only 18% of U.S. manufacturers report a formal AI strategy and two-thirds struggle to scale pilots. The real point is not frontier models but AI deployment in factory automation, scheduling, and inspection.

Noematrix closed a Series A worth several hundred million yuan, led by C Capital, with Sea Limited and Puhua Capital participating, and Prosperity7 Ventures increasing its stake. Founded in Nov. 2023, the company says its Noematrix Brain has been deployed on wheeled single-arm, wheeled dual-arm, and humanoid dual-arm robots in retail pharmacies and hotel laundries; the post does not disclose valuation or revenue. The sharper signal is its claimed hundreds of thousands of hours of real-robot data and its data-model-scenario loop.

Jensen Huang said at Davos that global VC investment topped $100 billion in 2025, with most capital going to AI-native startups building the AI stack’s application and infrastructure layers. He described AI as a five-layer stack: energy, chips and computing infrastructure, cloud data centers, models, and applications, and cited a US nursing shortage of about 5 million where AI can handle charting and transcription. The key point for practitioners is that the bottleneck is not just models, but the full infrastructure and labor chain.

UK agency ARIA selected 12 AI scientist projects from 245 proposals, doubled its planned funding, and will give each team about £500,000 for nine months. ARIA defines an AI scientist as a system that hypothesizes, runs experiments, analyzes results, and iterates; the funded projects still rely on existing tools. The key signal is reproducible lab-loop execution, not press-release heat: one cited external study reports LLM agents failed to complete a scientific workflow 3 out of 4 times.

At CES, Silicon Valley 101 discussed humanoid robot deployment and cited official figures: 21 of 38 humanoid exhibitors were Chinese companies. Guests noted Boston Dynamics plans Atlas deliveries in 2026 and 30,000 annual capacity by 2028, but argued scale claims do not prove product-market fit; in warehouses, wheeled bases plus arms often beat humanoids on ROI.

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.