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first_img Spirit AI Co-Founder: The breakthrough for robotic brains is expected as early as next year

According to a report by Reuters, Gao Yang, co-founder and chief scientist of the Chinese humanoid robot startup Spirit AI, stated that humanoid robots could complete most general tasks based on verbal instructions as early as next year, but it will take at least 8 more years to enter households. He mentioned that the brain is the weakest link in the entire robotics technology stack, and it is expected to reach a milestone similar to GPT-3.0 by mid-2027, allowing users to speak to robots in natural language and have them perform a series of reasonable physical actions to attempt to complete tasks.Spirit AI was founded in 2024, has about 300 employees, and raised $670 million in funding within two years, with a valuation of $2.9 billion. The company employs about 1,000 contractors who wear data collection devices at home or in factories, primarily relying on real-world data for training. The success rate for simple tasks in a structured living room environment is 90%. Currently, dozens of Moz1 wheeled humanoid robots are deployed on production lines at CATL and JD.com.Gao Yang stated that the next 1-2 years represent the initial window for industrial applications, and after two years, they can enter commercial service scenarios to perform simple tasks, but entering households will be more challenging. In terms of safety, full-body force control is implemented, and the robots will automatically engage emergency braking when encountering significant interaction forces. High-quality data is the main bottleneck for training the robot's brain.

There are 106 national embodied intelligence data collection centers and over 5,000 robots

According to a research report released by Tiger Sniff on September 20, as of August 2026, there are a total of 106 publicly disclosed centralized embodied intelligence data collection centers in the country, of which 84 are in operation, accounting for 79.25%. 52 centers disclosed the number of deployed robots, totaling approximately 3,972 units, which estimates that there are at least over 5,000 robots operating in data collection centers nationwide. The peak of construction is expected in the first quarter of 2026, after which new projects will significantly decrease, and the industry will shift from intensive construction to concentrated operation.In terms of regional distribution, Jiangsu, Zhejiang, and Guangdong have 18, 17, and 11 centers respectively, Sichuan has 8, and Beijing has 7. In terms of robot brands, Zhiyuan Robotics appeared 31 times, Leju 15 times, UBTECH 13 times, and Yushu Technology and Galaxy General each 10 times. 65.96% of data collection centers use a single robot brand, while 34.04% adopt a multi-brand strategy, and cross-entity data reuse remains a challenge.Regarding data pricing, the current real machine data costs about 500 to 1,000 yuan/hour, UMI and other non-entity data costs about 300 to 400 yuan/hour, and simulated synthetic data costs about 200 to 500 yuan/hour, with remote operation collection accounting for 79.05%. The report points out that centralized data collection has not yet formed a stable commercial closed loop, with buyer growth lagging behind base expansion. Centers that primarily rely on one-time construction funding will face greater operational pressure, and the industry elimination race has already begun.

first_img Fake AI trading robot tutorial deceives 224 victims into deploying malicious contracts

On September 14, blockchain intelligence company TRM Labs released a report revealing that fake YouTube tutorials lured 224 victims into deploying and funding malicious smart contracts under the guise of building AI-based crypto arbitrage bots, resulting in the theft of 274.6 ETH. TRM identified a total of 234 contracts deployed by the victims, with funds ultimately flowing into six collection addresses controlled by the operators. The stolen ETH was worth approximately $517,000 at the time of the transfer, with a median loss of 1 ETH per incident.Unlike common wallet theft attacks, this scam did not involve phishing links, spoofed domains, or malicious authorization prompts. Victims chose the tutorials themselves, copied the code, deployed the contracts, and funded them from their own wallets, with each step authorized by the victims themselves. As a result, wallet security warnings and phishing blacklists could not be triggered. TRM discovered nine nearly identical YouTube tutorials disguised as different creators, using AI-generated virtual hosts and voiceovers, promising to build fully automated crypto trading bots with Claude, and guiding victims to a compiler website controlled by the operators, some of which mimicked the commonly used Remix development environment.In one variant analyzed by TRM, a backend script would discard the source code pasted by the victims and retrieve another contract from the operator's server, with the clean code displayed on the screen never being on-chain. The replaced contract accepted deposits and transferred any balance over 0.05 ETH to the operators when the victims pressed Start or Withdraw, with no arbitrage logic or AI functionality included in the contract.
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