Realtime AI News
GPT 6之后，具身智能走向何方？诺因发布GLOW技术报告，给出机器人“一教就会”的答案
GPT 6之后，具身智能走向何方？诺因发布GLOW技术报告，给出机器人“一教就会”的答案. 人类演示一次，机器人即可实现跨场景任务复用
According to qbitai.com, GPT 6之后，具身智能走向何方？诺因发布GLOW技术报告，给出机器人“一教就会”的答案.
人类演示一次，机器人即可实现跨场景任务复用
The signal matters because AI capabilities are moving into more specific product, infrastructure, or business workflows.
The next things to watch are availability, pricing or access limits, and whether the update creates a measurable workflow change for builders or enterprise users.
Why it matters
This update reflects the continued movement of AI capabilities into concrete product, platform, and industry contexts.
Nearby Updates
All09/24, 15:00
Anthropic CEO says company will slow down ‘as much as necessary’
Anthropic’s CEO has said publicly that the company will slow its AI development “as much as necessary,” a stance Storyboard18 framed as the AI race meeting its safety brake. The pledge puts safety evaluation ahead of release speed, but the trigger conditions are still defined by the company itself.
09/24, 13:46
Stripe Tour Debuts in China as Managed Payments Goes Live
Stripe held its first Stripe Tour event in China, where it announced that Stripe Managed Payments (SMP) is now fully live. Chinese outlet QbitAI framed the debut around Stripe's pitch that it is building infrastructure for the AI economy.
09/24, 13:45
Lingchu Intelligence Details Psi-R2.5 Data Work: Reversing World Model Psi-W0 to Align Human and Robot Actions
Lingchu Intelligence has updated the data-quality and human-robot alignment methods behind its embodied model Psi-R2.5, building on 100,000-hour-scale data collection. The company says it reverse-uses its world model Psi-W0 to generate matching human-operation data from real robot data, producing strongly paired samples that serve both as training material and as demonstrations for in-context learning.
09/24, 13:19
Tsinghua and Infinigence Open-Source RLark, a Cloud-Native Platform for Embodied AI
Tsinghua University and Infinigence have jointly open-sourced RLark, a cloud-native platform for embodied intelligence that the source describes as a new control tower for robotics. The project claims robot onboarding in five minutes and cross-cluster task launch in ten seconds.