Upload set_050_黄誉扬.json

set_050_黄誉扬.json

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+{
+    "set_id": "set_050",
+    "annotator": "黄誉扬",
+    "qa_pairs": [
+        {
+            "id": 1,
+            "domain": "Culture",
+            "task_type": {
+                "L1": "III. Cross-Video Integrated Reasoning",
+                "L2": "6. Integrated Summarization",
+                "L3": "(1) Abstractive Cross-Video Summarization"
+            },
+            "question": "Combining Video A’s description of hardware iteration and Video B’s analysis of the AI market, which option most accurately defines the 'technology-market' inflection point of the humanoid robot industry in 2025?",
+            "options": {
+                "A": "The industry focus has shifted from 'pre-programmed specific actions' to 'VLM-driven generalized task execution': actuator precision on the hardware side can support complex fine manipulation (such as precision assembly in Video A), while the AI side has closed the loop from cloud inference to edge embodied control, enabling robots to generate real ROI in unstructured environments.",
+                "B": "The industry breakthrough mainly stems from 'plummeting computing cost' and 'popularization of carbon fiber skeletons': Video A confirms that material science advances have completely solved the endurance bottleneck, while Video B shows that the market is forcibly pushing humanoid robots into homes through large-scale capital subsidies, driven by saturation of the consumer electronics market rather than technological evolution itself.",
+                "C": "The core industry contradiction has shifted from 'insufficient algorithmic perception' to 'lack of legal regulation and moral ethics': although Video A shows that Atlas E2’s movements perfectly simulate humans, Video B emphasizes that market resistance due to fear of robots replacing low-skilled labor is the only real barrier restricting Optimus and Figure 03 from entering factories.",
+                "D": "The industry is in a transition from 'laboratory prototypes' to 'fully autonomous evolving super-intelligent agents': Video A demonstrates that robots no longer need human data for training, while Video B predicts that the AI market will be dominated by hardware companies, with software algorithms reduced to fully standardized free plugins."
+            },
+            "answer": "A",
+            "evidence": [],
+            "created_at": "2026-02-26T15:03:09.193654"
+        },
+        {
+            "id": 2,
+            "domain": "Entertainment",
+            "task_type": {
+                "L1": "III. Cross-Video Integrated Reasoning",
+                "L2": "6. Integrated Summarization",
+                "L3": "(1) Abstractive Cross-Video Summarization"
+            },
+            "question": "Video A shows that Figure 03 has extremely high hand DOF, while Video B discusses the AI market’s expectation for 'general-purpose labor'. What logical contradiction in current humanoid robot design do the two videos collectively reflect?",
+            "options": {
+                "A": "Over-anthropomorphism in hardware design leads to a surge in production costs: to meet the market's expectation for 'versatility' mentioned in Video B, the model in Video A is forced to adopt a high-cost agile hand structure, which improves demonstration effects but has worse ROI performance than specialized automated robotic arms in most factory scenarios due to high maintenance costs.",
+                "B": "High hardware DOF is the physical foundation for AI generalization: Video B argues that AI reasoning needs to be closed through complex physical feedback like that in Video A; such 'hardware redundancy' is a necessary cost toward AGI, and the market has accepted the initial commercial premium of over $100,000 per unit.",
+                "C": "Hardware 'modularity' is replacing 'overall anthropomorphism' as the market mainstream: according to both videos, Figure and Tesla are reducing hand joints for stability, because Video B data shows the market prefers cheap, single-function robots over full-function humanoid models promoted in Video A.",
+                "D": "Hardware 'durability' is over-optimized in AI simulation training: Video A shows robots perform far better in virtual environments than in reality, causing investors mentioned in Video B to overestimate their mean time between failures (MTBF) in harsh industrial environments."
+            },
+            "answer": "B",
+            "evidence": [],
+            "created_at": "2026-02-26T15:03:43.573321"
+        },
+        {
+            "id": 3,
+            "domain": "Entertainment",
+            "task_type": {
+                "L1": "III. Cross-Video Integrated Reasoning",
+                "L2": "6. Integrated Summarization",
+                "L3": "(1) Abstractive Cross-Video Summarization"
+            },
+            "question": "Video A mentions Optimus has fully adopted end-to-end neural network control, while Video B discusses the layout of AI chip giants (e.g., NVIDIA) in the robot market. Combining these two points, which is the most accurate summary of the 'moat' for humanoid robots?",
+            "options": {
+                "A": "Core competitiveness is shifting from 'software algorithms' to 'vertical integration of rare metals and motors': Video B shows AI algorithms have become homogeneous, and the key to future market success lies in actuator mass production cost mentioned in Video A, i.e., who can reduce per-unit BOM cost through scale effects.",
+                "B": "Core competitiveness is shifting from 'computing density' to 'breakthrough in battery energy density': Video A demonstrates improved joint power, but Video B warns that due to stagnant battery technology, AI market enthusiasm will quickly cool due to short working hours of robots, forcing the industry to switch to wired power supply.",
+                "C": "Core competitiveness is shifting from 'proprietary technology' to 'open-source ecosystem construction': Video B argues that only through fully open-source AI brains can diverse hardware in Video A be supported, and closed systems (such as Atlas E2) will exit the mainstream market due to inability to iterate rapidly.",
+                "D": "Core competitiveness is shifting from 'mechanical transmission design' to 'high-quality physical interaction data acquisition and simulation capability': end-to-end technology invalidates traditional hierarchical control algorithms; companies with massive real-world data and strong simulation computing power (e.g., Tesla) will have greater technological suppression in the AI market than traditional robot manufacturers."
+            },
+            "answer": "D",
+            "evidence": [],
+            "created_at": "2026-02-26T15:04:11.625041"
+        },
+        {
+            "id": 4,
+            "domain": "Entertainment",
+            "task_type": {
+                "L1": "III. Cross-Video Integrated Reasoning",
+                "L2": "6. Integrated Summarization",
+                "L3": "(1) Abstractive Cross-Video Summarization"
+            },
+            "question": "Video A details the tactile array of robot fingers, while Video B discusses how AI understands common sense in the physical world. Combining both videos, how to evaluate the role of tactile perception in embodied intelligence in 2025?",
+            "options": {
+                "A": "Tactile sensing is an auxiliary means to reduce AI computing consumption: Video A confirms that localized tactile feedback can reduce reliance on expensive cloud computing, while Video B considers this a downgrade strategy adopted by the AI market to address the energy crisis.",
+                "B": "The main role of tactile perception is to improve robot safety and interaction warmth: to meet the service market demand mentioned in Video B, Optimus in Video A adds tactile sensing to prevent accidental injury to humans, but its importance is still lower than visual perception in core industrial operations.",
+                "C": "Tactile sensing is no longer mere pressure feedback, but a key channel for AI to acquire 'prior knowledge of the physical world': through tactile feedback, robots can correct errors in VLM reasoning in real time; such high-level 'hand-eye-brain' coordination is the technological pillar for the AI market to leap from 'linguistic intelligence' to 'behavioral intelligence' as stated in Video B.",
+                "D": "Tactile sensing is currently the most difficult hardware bottleneck for humanoid robots: Video A admits tactile sensors are extremely fragile, while Video B analyzes that such high maintenance costs will prevent robots from achieving expected market penetration by 2026."
+            },
+            "answer": "C",
+            "evidence": [],
+            "created_at": "2026-02-26T15:04:33.314179"
+        },
+        {
+            "id": 5,
+            "domain": "Entertainment",
+            "task_type": {
+                "L1": "III. Cross-Video Integrated Reasoning",
+                "L2": "6. Integrated Summarization",
+                "L3": "(1) Abstractive Cross-Video Summarization"
+            },
+            "question": "Combining the high-dynamic motion capability of Atlas E2 in both videos and the strict ROI requirements of the AI market, which option is the most reasonable summary of the commercialization path of humanoid robots in the next three years?",
+            "options": {
+                "A": "Reverse evolution from 'home care' to 'extraterrestrial exploration and disaster relief': due to strict regulation in the civilian market mentioned in Video B, robots with Atlas-level mobility in Video A will first achieve commercial closure in extreme environments and will not enter the consumer market within five years.",
+                "B": "Transition from 'heavy physical labor in specific closed scenarios' to 'complex assembly and logistics in semi-structured environments': hardware maturity in Video A supports this leap, and the market logic predicted by Video B is that mature AI agents will first replace positions with 'high repeatability, controllable environment but requiring certain logical decisions'.",
+                "C": "Transformation from 'replacing low-skilled workers' to 'assisting high-skilled engineers': Video A demonstrates the safety of robot collaboration, and Video B believes the high-net-worth assistive tool market will be more profitable than replacing factory assembly lines.",
+                "D": "Transformation from 'in-house closed ecosystem' to 'hardware outsourcing, software subscription' model: Video B shows AI companies will no longer manufacture hardware, but control all models in Video A through subscription fees, and humanoid robots will completely become standardized hardware terminals like smartphones."
+            },
+            "answer": "B",
+            "evidence": [],
+            "created_at": "2026-02-26T15:05:00.225705"
+        }
+    ]
+}