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In2Mate closes angel round to fund warm‑bodied companion robot JiaBan

In2Mate, formally Shadow Gather Energy Robotics (Shanghai) Co., Ltd., a high‑tech developer of emotional‑companion robots, has completed its angel financing round. Founded on Feb 14, 2026, the firm targets immersive physical companionship scenarios and develops JiaBan, a thermostatic tangible robot built for emotional interaction to ease loneliness and anxiety. Proceeds from the angel round will back ongoing R&D and market rollout of its flagship JiaBan companion robot.

Briefs

  • ASD warns on share volatility, says new embodied AI robot business in early stage

    ASD Co., Ltd. said in a stock exchange filing that its shares had surged more than 20% over two consecutive trading days on Sept 3 and Sept 4, triggering an abnormal fluctuation alert, while clarifying that its newly launched embodied intelligence robotics collaboration project remains in a nascent stage with revenue of only 137,200 yuan ($19,000) and is not expected to have a material impact on this year's financial results, as the company reported a net loss of 93.4 million yuan for the six months ended June 30 on operating revenue of 1.351 billion yuan, with cookware and small appliances accounting for 84.46% of total revenue and industrial robots contributing 12.20%, while the robotics partnership is a newly explored business facing uncertainties in technology iteration, project implementation and commercialisation.

  • Simple AI secures hundreds-of-millions-yuan Pre-A round to advance embodied robot development

    Chinese general embodied AI robotics developer Simple AI has closed a multi-hundred-million-yuan Pre-A financing round backed by investor Kexi Capital and other institutional backers. Positioned as an AI-native embodied intelligence system provider, the firm has launched an in-house data production engine that has processed over 20,000 hours of robotic scenario data. From August 19 to 23, its new-generation service robot Xiaopu successfully completed a wide range of household workflows and fine manipulation tasks in hotel settings, demonstrating steady progress in real-world embodied AI deployment.

  • OpenAI to build in-house humanoid robots and data-center machines, Altman confirms

    OpenAI CEO Sam Altman confirmed during a recent podcast appearance that the company will develop its own humanoid robot hardware alongside specialized robots for data center operations. The firm has upgraded its former world-simulation project into OpenAI Robotics, targeting short-term robotic solutions to support infrastructure workers while pursuing the long-term vision of ubiquitous personal robots for everyday users. OpenAI also plans to launch its first screen-free portable AI device as early as 2027. Featuring a donut-shaped form factor, the upcoming gadget is expected to retail for more than $300.

  • IFA 2026 opens in Berlin with expanded content zone, new innovation stage

    The 2026 IFA consumer electronics trade fair kicked off at the Berlin Exhibition Grounds on Friday, running through Sept 8, with an expanded content creation zone and a new ICC Innovation Dialogue stage highlighting AI future tech, smart home, and mobility.

    Founded in 1924, the event is one of the world's longest-running consumer electronics exhibitions. This year's edition underscores the industry's pivot toward AI-driven applications and cross-sector integration.

  • Building data base, Maniformer joins robotics standards push

    During the 2026 China International Big Data Industry Expo, the Shanghai Robotics Industrial Technology Research Institute, together with Maniformer and other industry leaders, issued a joint initiative on data quality and standards for the robotics sector, aiming to improve data quality, refine industry norms, and foster a shared ecosystem. The initiative targets key challenges in embodied intelligence and humanoid robotics, rallying consensus around three pillars: establishing unified data standards, sharing compliant high-quality data resources, and driving innovative commercial applications.

  • Dobot, CAS institutes' MoE paper accepted by EMNLP 2026

    A research paper co-authored by Dobot, the Institute of Computing Technology of the Chinese Academy of Sciences, the Nanjing College of the University of Chinese Academy of Sciences, the Nanjing Information High-Speed Rail Research Institute, and two other CAS-affiliated schools has been accepted for publication at the Findings of EMNLP 2026, the top-tier international conference on computational linguistics and natural language processing, which will take place in Budapest from 24–29 October. The study, titled “Meta-Learning Where to Allocate Experts: Task-Conditioned Layer-Wise Compression for MoEs,” proposes a novel compression method for mixture-of-experts models, marking a collaborative research achievement among the Chinese academic and industrial partners.
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