Zhipu Just Dropped Full Stack AI Model on China Chips: West Panics!

Video Description

Zhipu and Huawei just open-sourced GLM-Image — and the real shock is that it was trained end-to-end on China’s domestic AI stack, using Huawei Ascend Atlas 800T A2 hardware and MindSpore. That’s a straight signal that China is building an alternative compute ecosystem that can compete at scale. Then Google upgrades Veo 3.1 with reference-image video generation, native vertical output, 1080p plus 4K upscaling, and SynthID watermarking, rolling it out across Gemini, YouTube Create, and Vertex AI like it’s about to flood the entire internet with controllable AI video. After that, Google pushes into the real world with MedGemma-1.5 and MedASR, built for CT, MRI, pathology slides, lab report extraction, and clinical speech-to-text — basically turning medical AI into something that looks workflow-ready. And finally, Rokid unveils AI glasses that integrate ChatGPT, record 4K, translate in 89 languages, and even add payments through Alipay+ GlassPay, making AI wearables feel like an actual consumer platform shift. 📩 Brand Deals & Partnerships: [email protected] ✉ General Inquiries: [email protected] 🧠 What You’ll See 0:00 Intro 0:52 China's first AI model trained entirely on domestic chips 1:40 Ascend Atlas 800T A2 chips and MindSpore framework 2:23 Autoregressive + diffusion decoder design 4:11 Commercial API at $0.014 per image 4:38 China's AI Independence 6:26 Google Veo 3.1 Update 6:44 Reference-image video generation 7:04 Vertical Video Support 7:17 1080p output with 4K enhancement 7:39 Rollout across Gemini, YouTube Create, Vertex AI 8:25 SynthID Watermarking 9:15 Medical AI for CT, MRI, and pathology 11:19 Document parsing for medical data 12:16 Clinical speech-to-text for radiology dictation 13:03 Rokid AI smart glasses with ChatGPT 14:03 4K Video Recording 14:12 89-Language Translation 14:37 QR payment integration via glasses 🚨 Why It Matters This video shows the real shift happening right now: AI is no longer just about better models. It’s about stacks, distribution, and real-world deployment. With GLM-Image, China proves it can train competitive multimodal systems on its own chips and frameworks, weakening the global compute chokehold. With Veo 3.1, Google turns AI video into a distribution weapon by pushing it into Gemini, YouTube, and enterprise pipelines all at once. With MedGemma and MedASR, medical AI stops being a demo and starts looking like a workflow layer. And with Rokid, AI wearables evolve into a consumer device category that can translate, record, assist, and even pay — all from your face. #AI #Google #chinaai