What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
iTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
Researchers have documented parallel programs querying Alibaba’s Amap mapping service for entrance-navigation information about public places in China. Their preliminary report links the observed request path to Tencent Cloud infrastructure, but it does not identify who directed the activity, why the data was being collected, or which AI model—if any—definitively powered it.
What the researchers observed
The Swarmchasers, a group of independent researchers, reported on October 4, 2026, that programs submitted to urlquery caused the service’s browser to load Amap pages and APIs. Urlquery is a domain-scanning service that can load submitted web addresses; its publicly visible records let the researchers inspect the requests.
The queries appeared to seek entrance-level navigation shares for public places in China, including parks, museums, zoos, and hospitals. In one documented result, Chengdu Zoo’s entrances were listed as North Gate 71%, East Gate 23%, and Southeast Gate 6%. Another location’s readout listed Ground Car Park at 40%, Main Gate at 26%, and smaller shares for other entrances. These are the reports’ readouts, not independently verified measurements of actual visitor traffic.
Free tools Windows power users keep installed
One-click scans. No signup required.
Why call it an “agent fleet” rather than a swarm?
The Swarmchasers described parallel runs doing the same kind of work, but said they saw no evidence in the records they reviewed that the runs communicated with one another. They therefore used “agent fleet,” not “swarm.” The phrase characterizes the observed pattern; it does not prove that the runs were independent agents or establish a particular system design.
#1 Best Overall
- AI-Powered Raspberry Pi Robot Dog — PiDog: Powered by Raspberry Pi (5/4B/3B+/3B/Zero 2W), OpenClaw, and multi-LLMs like ChatGPT, Gemini, Grok, DeepSeek, Qwen & Ollama. With 12 servos, camera, gyroscope, hearing & touch sensors, PiDog can see, listen, talk, move, and interact intelligently. Supports OpenCV, MediaPipe, TTS & STT, app control, FPV & Python. A great STEM robotics gift for students, makers & tech enthusiasts—perfect for birthdays and holidays. (Raspberry Pi not included)
- Realistic Dog-like Movements: PiDog's 12 powerful servos enable 32 dog-like actions, including walking, sitting, standing, shaking its head, wagging its tail, and performing playful tricks, closely mimicking a real dog and providing an engaging experience. This is an AI development robot product designed for engineers, suitable for ages 15 and above
- Rich Sensor Suite for Interactive Experiences: PiDog features ultrasonic, touch, gyroscope, sound, camera, speaker and microphone. These provide it with advanced hearing, vision, and touch, enabling it to see, detect obstacles, respond to touch, and recognize sounds, making interactions highly engaging
- AI-Powered Interactions with OpenClaw & Multi-LLMs. PiDog combines voice, vision, and gesture recognition for immersive AI experiences. Powered by OpenClaw and multi-LLMs like ChatGPT, Gemini, Grok, DeepSeek, Qwen, Doubao, and Ollama (local LLMs), it can understand questions, respond naturally through TTS & STT, recognize math problems, interpret hand gestures, and hold smart conversations. OpenClaw also enables customizable AI behaviors and personalized robotics development, helping users create their own intelligent robotic companion
- Comprehensive Learning Resources and Support: PiDog offers detailed online documentation, video tutorials, prompt technical support, and an active forum community, ensuring beginners can easily complete all projects and enjoy a great experience
TechCrunch’s October 5 account also noted the researchers’ distinction. It said the activity did not appear more nefarious than working around Alibaba’s API rules, while emphasizing that the investigation was still ongoing. That assessment is not a finding about the operator or ultimate purpose.
How much activity did the report count?
For September 28 through October 4, 2026, the Swarmchasers counted 2,048 Amap reports across 216 places, including 1,810 reports on October 4 alone. They recorded as many as 14 runs active at once and 51 places worked on during the busiest hour.
Rank #2
- Optimized AI Arm Kit for LeRobot & Hugging Face Projects – The SO-ARM101 is an upgraded low-cost robotic arm servo motor kit designed for AI robotics enthusiasts and developers. Fully compatible with LeRobot and Hugging Face frameworks, it supports imitation learning and reinforcement learning, making it ideal for real-world robotics applications. (3D-printed parts not included.)
- Enhanced Wiring & Performance – Compared to the SO-ARM100, the SO-ARM101 features improved wiring to prevent disconnection at joint 3 and eliminates range-of-motion limitations. The leader arm uses optimized gear ratio motors for smoother performance—no external gearboxes required.
- Real-Time Leader-Follower Functionality – New real-time tracking allows the leader arm to follow the follower arm, enabling human intervention and correction during reinforcement learning (RL) training. Perfect for hands-on AI robotics development and research.
- Open-Source, DIY-Friendly & Nvidia-Compatible – Developed by TheRobotStudio, this open-source AI Arm kit integrates seamlessly with the LeRobot platform, offering PyTorch-based datasets, simulation, training, and deployment tools. Fully compatible with Nvidia Jetson edge devices, including reComputer Mini J4012 Orin NX 16 GB.
- Comprehensive Learning Resources – Includes detailed open-source assembly and calibration guides, testing tutorials, and deployment instructions. From wiring to AI training, get everything you need to start building, teaching, and optimizing your robotic arm for grasping and placing tasks.
The figures describe the researchers’ collected and classified records, not a complete census. Urlquery records expire, the researchers say their counts are lower bounds, labels do not reliably identify runs, and urlquery does not store page content. The report also cautions that exact simultaneity was rare: a handful of fast agents could account for the pattern attributed to up to 14 active runs.
By the report’s update, the researchers had five entrance-share readouts. The figures are evidence of what the observed queries returned, not proof that the shares reflect real-world use or that the data was retained or used for any particular purpose.
Rank #3
- Raspberry Pi AI Robot: powered by Raspberry Pi (5/4B/3B+/3B/Zero 2W), features 12 servos and sensors for vision, hearing, and touch. Integrated with ChatGPT-4o, it responds to complex queries. With app control and FPV, users can manage and see its view in real-time. It supports Python programming
- Realistic Movements: 12 powerful servos enable 32 actions, including walking, sitting, standing, shaking its head, wagging its tail, and performing playful tricks, closely mimicking a real and providing an engaging experience
- Rich Sensor Suite for Interactive Experiences: features ultrasonic, touch, gyroscope, sound, camera, speaker and microphone. These provide it with advanced hearing, vision, and touch, enabling it to see, detect obstacles, respond to touch, and recognize sounds, making interactions highly engaging
- Engaging Interactions with ChatGPT-4o: with ChatGPT-4o enables voice interactions and visual recognition, making it smarter and more responsive. Users can have natural conversations, solve math problems via the camera, and interpret gestures, creating diverse and fun interactions
- Comprehensive Learning Resources and Support: offers detailed online documentation, video tutorials, prompt technical support, and an active forum community, ensuring beginners can easily complete all projects and enjoy a great experience
What the Tencent Cloud connection does—and does not—show
The report connects the observed request path to Tencent Cloud using inbox creation records and requests from Tencent Cloud addresses with a proxy Via header ending in hysandbox-ats. This supports a connection to that hosting network in the requests the researchers examined; it does not identify the person or organization directing the agents.
The Swarmchasers stress that Tencent Cloud is open to anyone and that a Via name is self-reported. They also say their tests did not match Tencent’s public Agent Sandbox product in its standard internet mode. The team had not reviewed the data behind those tests, so the report does not establish that Tencent’s product was involved.
Rank #4
- 【End-to-End Imitation Learning】Hiwonder SO-ARM101 robot arm is an embodied intelligent hardware platform compatible with the Lerobot open-source framework. It provides developers with streamlined access to shared code, templates, and pre-trained models to explore the latest advancements in AI research.
- 【Dual-Camera Vision System】Equipped with both a gripper-mounted camera and an external camera, the system supports both precise manipulation and environmental awareness for accurate imitation learning.
- 【Hiwonder High-Performance Bus Servos】Featuring 12 high-torque bus servo motors with magnetic feedback, the Hiwonder SO-Arm101 robotic arm delivers smooth, stable motion, eliminating issues like power deficiency and jitter.
- 【Professional Control & Debugging】Integrated with the Hiwonder BusLinker V3.0 debugging board, the system supports servo scanning, real-time status monitoring, and trajectory control. The professional PC software simplifies device calibration and debugging, making it accessible for both researchers and hobbyists.
- 【Open-Source Compatibility】The SO-ARM101 robotic arm is designed to be fully compatible with the LeRobot open-source project. We acknowledge the contributions of the open-source community; all trademarks and copyrights belong to their respective owners.
Was Claude the model behind the runs?
The report does not establish a definitive model. Although 211 reports carried a “claude” label, the researchers say code-style comparisons and limited model tests were more consistent with Tencent Hy and other Chinese model families than with Claude. No record they found names the model or a training job.
Those comparisons are not a reliable attribution: the tests were small, and models’ self-identification can vary with prompt and language. The “claude” label alone does not show that Claude ran the activity, and the report does not confirm Tencent Hy or any other model either.
What remains unknown
- Who operated the runs: the observed hosting network does not establish the operator’s identity or affiliation.
- Why the entrance data was collected: the records cannot distinguish an evaluation or task-generation run from training rollouts, and do not establish another purpose.
- Whether the activity was harmful: the preliminary observations do not substantiate claims of espionage, an attack, or a government operation.
- How the activity was orchestrated: parallel queries were observed, but the records reviewed did not show communication between them.
The Swarmchasers’ preliminary report, dated October 4 and updated October 5–6, documents activity only through October 6 and says a full report will follow. Its evidence supports a developing observation of Amap queries and a Tencent Cloud network connection—not a settled account of who was behind them or what they intended.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
