# Robotics Related Articles

HTX News Center provides the latest articles and in-depth analysis on "Robotics", covering market trends, project updates, tech developments, and regulatory policies in the crypto industry.

Wall Street Morning Report: S&P Earnings Growth Hits 30-Year High, Nvidia Becomes SpaceX's 6th Largest Shareholder

Wall Street Morning Report: S&P 500 earnings growth hits a 30-year high; Nvidia becomes SpaceX's 6th largest shareholder. Market Summary: U.S. stocks ended slightly lower on Friday after record highs, with the S&P 500 posting a weekly gain. Weaker-than-expected July retail sales data significantly reduced market expectations for a September Fed rate hike. Key Themes: * **Macro & Rates:** The probability of the Fed holding rates steady in September rose to ~70%. Geopolitical tensions in the Middle East supported oil prices near $90. Focus this week is on a $16B 20-year Treasury auction testing investor demand amid high yields. * **Corporate Earnings:** S&P 500 Q2 earnings grew 31%, the fastest pace since 1992 excluding recession recoveries, driving a valuation reset. * **AI & Tech Sector Rotation:** The AI investment narrative faces scrutiny over financing and return timelines. Semiconductor stocks saw divergence: memory (SanDisk, Micron) and optical communication (Applied Optoelectronics) surged, while Broadcom fell sharply on credit rating downgrade concerns over AI leasing exposure. * **Notable Moves:** Nvidia disclosed a ~$21B stake in SpaceX. AMD rose 6.5% after a record debt issuance. Reddit rallied ahead of its S&P 500 inclusion. This Week's Highlights: * **Fed Minutes (Thu):** Key for gauging policy divergence and September rate outlook. * **Key Earnings:** Alibaba, Walmart, Nvidia, AMD. * **Events:** Seoul AI Summit, World Robot Conference, potential恒生指数 rebalancing. * **Data:** U.S. jobless claims, Japan core CPI, Korea early export data (a leading indicator for semiconductors).

marsbitYesterday 04:49

Wall Street Morning Report: S&P Earnings Growth Hits 30-Year High, Nvidia Becomes SpaceX's 6th Largest Shareholder

marsbitYesterday 04:49

Explosion in Deep Sea Robots, the Hardest Series A Round Emerges

Deep-sea robotics startup Deepsea Zhiren has secured over 5 billion yuan in its Series A funding, a landmark deal backed by prominent investors including GGV Capital, Dachen Capital, Genesis Capital, Everbright Capital, China Life Insurance Investment, CETC Investment, and the energy tech fund managed by Cathay Capital with TotalEnergies as the cornerstone LP. Existing investors also participated significantly. The company, founded by industry veteran Ma Yiming, specializes in developing heavy-duty work-class ROVs for extreme deep-sea environments up to 6,000 meters, used in oil and gas, offshore wind, and subsea cable operations. Its product line includes models like "Taurus" (1,000m), "Phoenix 600" (3,000m), and "Singularity" (6,000m). A key achievement is securing multi-million dollar orders from UAE's telecom giant Etisalat, marking a breakthrough for Chinese-made deep-sea robotics in the international market. Deepsea Zhiren differentiates itself through full-stack in-house R&D—from pressure-resistant structures to control systems and AI—and a modular hardware approach. It has built a comprehensive internal standard system aligned with top global offshore specifications. The company is now advancing its "Deep Matrix" initiative, an unmanned, AI-powered, multi-robot cluster system designed for permanent seabed operations. This system aims to drastically reduce reliance on support vessels and human operators, potentially cutting costs in offshore oil field operations by billions over their lifecycle. The funding round signals strong market confidence in the deep-sea tech sector, recently highlighted in China's national policy. With the global subsea services market valued at around 1.5 trillion yuan and growing over 20% annually, Deepsea Zhiren aims to redefine deep-sea development through integrated hardware and embodied AI systems, positioning itself as a global pioneer in ocean robotics.

marsbit08/13 02:58

Explosion in Deep Sea Robots, the Hardest Series A Round Emerges

marsbit08/13 02:58

After Yushu Got Hot, a 68-Year-Old Auto Parts Boss Bet 1.85 Billion

After staying relatively low-profile for years, Shanghai Bate Technology, a traditional auto parts supplier, has recently been thrust into the spotlight as a leading humanoid robotics concept stock. This shift is largely tied to the impending IPO of robotics company Unitree, with which Bate collaborates on prototype development. Bate's founder, 68-year-old Jin Kun, is making a bold bet on this new frontier. The company is investing 1.85 billion yuan to build a major R&D and production base in Kunshan for planetary roller screws—a key component in robot joints. With an annual capacity of 2.6 million sets planned, plus overseas expansion, this represents a massive, forward-looking commitment from a firm whose 2025 revenue of 2.3 billion yuan still relies almost entirely on its traditional automotive business (over 98%). The investment highlights a strategic pivot. Bate aims to leverage decades of expertise in metal processing, precision manufacturing, and heat treatment from the automotive sector and apply it to the burgeoning robotics industry. However, this move carries significant risk. The company has not yet secured formal supplier contracts or begun mass deliveries for its roller screws. It is essentially betting on future demand in a market that remains nascent. The broader industry context adds to the uncertainty. While multiple Chinese manufacturers are racing to invest in similar robotics component capacity (totaling over 6 billion yuan), the downstream humanoid robot market is still in its early stages. Estimates put 2025 global shipments at only around 18,000 units, primarily for entertainment, education, and data collection rather than large-scale industrial use. This creates a critical mismatch: the speed of upstream component factory construction and capital investment is far outpacing the commercialization and adoption of the robots themselves. Bate's story, driven by Jin Kun's decisive gamble, encapsulates the high-stakes transition facing traditional manufacturers seeking a "second growth curve" in robotics—a future full of potential but currently backed more by market anticipation than concrete financial results.

marsbit08/12 09:02

After Yushu Got Hot, a 68-Year-Old Auto Parts Boss Bet 1.85 Billion

marsbit08/12 09:02

In Just 6 Months, 4 Rounds of Funding: West Lake University Professor's Venture Takes Off

Westlake Robotics, an embodied artificial intelligence company, has completed its Series A financing round within just six months and a total of four rounds, raising a cumulative 5 billion RMB. The investor lineup includes prominent institutions such as SAIF Partners, Xiaomiao Langcheng, Henan Investment Group Huirong Fund, and Haiyuan Fund, forming a high-quality capital matrix comprising state-owned, industrial, and leading venture capital. The rapid and intensive capital injection reflects strong market confidence in the company's technological approach, product deployment capabilities, and long-term potential. The newly acquired funds will be primarily allocated to the research and development of a unified large model for humanoid robots and the establishment of a talent cultivation base for embodied AI. Founded in 2024, Westlake Robotics originated from the industrial transformation of pioneering achievements in AI and robotics at Westlake University. The founding team is led by Wang Donglin, a leading figure in China's embodied AI and robot learning field, and co-founder Zhang Yue, an expert in natural language processing. The core R&D members hail from top-tier tech companies like Alibaba, ByteDance, Tencent, and Huawei, as well as prestigious global universities. The company follows a fully self-developed strategy integrating a "universal brain + humanoid body-specific cerebellum + proprietary humanoid hardware." It is one of the few domestic enterprises capable of holistically connecting the three core areas of embodied AGI cognitive reasoning, full-body motion control, and humanoid hardware. Its proprietary technologies include the General Motion Model-GAE system for low-latency teleoperation and motion generalization, and a dual pre-trained architecture for general and body-specific processing to bridge cognitive reasoning and physical movement. In 2026, Westlake Robotics launched its self-developed humanoid robot "Westlake o1," completing the full technology chain from underlying algorithms to pre-trained models and hardware. The company has secured nearly 100 million RMB in orders, with applications in scientific research, education, data collection, and power inspection. Future targets include high-risk industrial inspection, post-disaster search and rescue, and remote precision assembly. The company has also partnered with the Longyou County government to establish a county-wide real-scenario training base for humanoid robots, aimed at collecting high-quality motion data and validating technology in authentic environments. With the latest funding, Westlake Robotics plans to further advance its core model development and talent acquisition strategy, accelerating progress toward the "GPT moment" for embodied intelligence in China.

marsbit08/12 02:53

In Just 6 Months, 4 Rounds of Funding: West Lake University Professor's Venture Takes Off

marsbit08/12 02:53

Two Funding Rounds Secured in 40 Days, Embodied Data Practitioner Enters the Arena

Investment news outlet learned on August 12th that ScaleForce, an Embodied AI data infrastructure company, has raised two funding rounds within 40 days from investors including top domestic embodied AI industry players, Hengxu Capital, and Capital Today. Established less than three months ago, ScaleForce has already secured a multi-million-yuan data order from its lighthouse customer, TaShi Zhihang. It has also established collaborations with multiple world model companies, leading embodied intelligence hardware manufacturers, and industry solution providers. Founder Guo Jiangliang believes that the competition in embodied intelligence has entered its second phase, which focuses on data and intelligence. ScaleForce aims to enable data to flow through the entire lifecycle of physical AI, fostering infinite intelligence within the physical world. The immense popularity of embodied intelligence contrasts sharply with a severe shortage of high-quality, real-world interactive data needed for training. Unlike large language models that can scrape training material from the internet, embodied AI requires multimodal physical interaction data involving vision, touch, joint trajectories, object mechanics, and environmental temporal alignment, which must be collected in the real world. The industry faces challenges such as uncontrollable data quality, insufficient scale, and poor data generalization across different robotic platforms. ScaleForce addresses these issues with its core product, the MatrixOS physical AI operating system. It features the ADA (Action-Data Alignment) data generalization engine, which reportedly increases cross-platform task success rates from 65% to 92%. Its GDP (Global-Deep-Proactive) data quality engine employs various analytical methods to optimize data collection, achieving an 80% usable conversion rate. The company has built a global, scalable data production network with over 95% automation, utilizing human-centric collection paradigms and sub-millisecond multi-sensor synchronization kits. MatrixOS functions as a comprehensive data "production system" for embodied intelligence, connecting the physical world for data acquisition, processing, and management, then delivering it to models and applications. ScaleForce is building what it claims will be the world's largest and lowest-cost high-quality data production and distribution network. The company has secured its position in the emerging embodied AI data industry chain by providing tailored scene data to hardware makers, real physical interaction data to world model companies, and task-specific data closed loops to industry clients. Its partnership network includes world model firms like ZhiZai WuJie, Huawei's Ascend ecosystem, and academic institutions like Peking University and Beihang University. International expansion is also underway, starting in Southeast Asia. The founding team brings deep industry experience. Founder Guo Jiangliang was a founding member of Baidu Intelligent Cloud and former Technology VP of AInnovation. Chief Scientist Alex, a Peking University PhD, has held core roles at Meta AI and Huawei Noah's Ark Lab. The team's combined expertise in technology, product, and commercialization forms the foundation for ScaleForce's rapid progress. With 2026 considered the "first year of embodied data," and 2027-2029 viewed as a critical window for the scaled commercialization of humanoid robots, the demand for robust data infrastructure is poised for significant growth. As companies like Unitree approach IPOs, the next phase of competition in embodied intelligence will heavily rely on data, marking a crucial time window for the embodied data sector.

marsbit08/12 02:46

Two Funding Rounds Secured in 40 Days, Embodied Data Practitioner Enters the Arena

marsbit08/12 02:46

Just Now, Lin Junyang Officially Announces the Startup Company Pragmatik Labs

Justin Lin, former technical lead of Alibaba's Qwen large language model, has officially announced the launch of his AI startup, Pragmatik Labs (also known as p7k), based in Shanghai. The company is focused on developing next-generation agents that operate across both digital and physical worlds. The startup's research is divided into two main areas: Digital Agents for knowledge work and business operations, and Physical Agents for embodied intelligence capable of performing long-term tasks in the real world. Pragmatik Labs also emphasizes translating research into products and pursuing long-term exploratory projects. The company has secured significant funding, reportedly raising hundreds of millions of USD in a round co-led by Gaorong Capital and Sequoia Capital China, with additional support from Tencent and the Shanghai Future Industry Fund. The post-money valuation is estimated to be around $2 billion. Lin, who left Alibaba in March, has a background in linguistics and computational linguistics. He played a key role in developing the open-source Qwen model series. In a previous article, he argued that the next phase of AI will shift from training models to training agents and multi-agent systems. The company's name, "Pragmatik," reflects both a connection to linguistics (pragmatics) and a pragmatic approach to achieving AGI. His move signals a growing focus among top AI researchers on building agents that can not only reason but also execute complete tasks, moving beyond the foundational model race.

marsbit08/11 23:45

Just Now, Lin Junyang Officially Announces the Startup Company Pragmatik Labs

marsbit08/11 23:45

New Job in the Robotics Industry: A 'Bone Doctor' Earning 6,000 Yuan Monthly, Specializing in Treating Broken Limbs

A new job has emerged in the robotics sector: the "orthopedic surgeon" for robots, earning around 6,000 RMB per month by specializing in repairing robots and robotic dogs. As the number of robots explodes, with IDC projecting 18,000 humanoid robots shipped globally in 2025 and China's MIIT predicting over 100,000 units produced domestically in 2026, demand for maintenance and repair is rising. The repair process, as demonstrated by Zhao Xin, a former service industry worker turned self-taught repairman, involves diagnosing issues like joint noises, disassembly, and part replacement. The technical barrier is relatively low, often simpler than repairing drones, with basics learnable in a month. The real challenge is obtaining proprietary parts, which are monopolized by manufacturers, lack public schematics, and are expensive. Currently, third-party repair shops, like those run by Zhao Xin or Nanjing Kaogong Yunji's Fang Jinghua, offer cheaper (10-15% of robot price, 20-50% cheaper than OEM) and faster (one week vs. over a month) service, mainly for out-of-warranty units used in entertainment performances. However, repair volume remains low—just 1-3 robots/month for some shops—making it unsustainable as a primary business. Most repair shops rely on other revenue streams like training, drone repair, or leasing. Training programs are emerging, with courses from 8 to 40 days and fees from 5,000 to 30,000 RMB. Graduates often enter sales or operations roles. For pure repair jobs, salaries range from 6,000-8,000 RMB/month for beginners to over 10,000 RMB for experienced technicians. While companies like JD.com plan large-scale technician training, the robot repair market still awaits broader industry growth to become a fully viable standalone profession.

marsbit08/10 05:31

New Job in the Robotics Industry: A 'Bone Doctor' Earning 6,000 Yuan Monthly, Specializing in Treating Broken Limbs

marsbit08/10 05:31

AI Takes Over the Lab? Latest Research from USTC Puts It to the Test in the Real Physical World

This study from the University of Science and Technology of China presents a real-world stress test for AI in scientific research. Researchers developed a machine-readable, modular laboratory for catalysis, consisting of 45 automated workstations. They evaluated 48 configurations combining 6 agent frameworks and 9 large language models (LLMs) across 32 expert-defined research tasks, conducting 4,608 tests. The key findings reveal a significant gap between AI's planning ability and reliable physical execution. Only 3.3% of all generated workflows (151 out of 4,608) could be executed without human correction. The best-performing agent/LLM combination achieved a 28.1% success rate. In a five-round closed-loop experiment, the AI could adjust local parameters based on results but failed at higher-level scientific replanning, such as redesigning analytical methods or correcting persistent critical omissions. Maintaining logical integrity for long-sequence workflows (over 30 steps) also proved challenging. The research distinguishes three often-conflated AI capabilities: generating plausible experimental plans, creating physically executable workflows, and performing evidence-driven strategic replanning. Results show the first does not guarantee the second, and parameter tuning is not equivalent to scientific reasoning. The platform serves as both a "testing ground" to quantify AI's scientific aptitude and a potential "training ground." By forming a "plan-execute-feedback-replan" loop with real-world feedback, it can expose AI shortcomings and generate data for iterative improvement, moving toward true end-to-end autonomous discovery.

marsbit08/06 08:31

AI Takes Over the Lab? Latest Research from USTC Puts It to the Test in the Real Physical World

marsbit08/06 08:31

活动图片