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Technical exploration and thoughts · 655 articles
AI Research #121: DeepSeek-OCR Research Directions
Frontier approaches and engineering implementation for DeepSeek-OCR (2025, including 3B parameter direction). Summarizes research directions including...
AI Research #119: DeepSeek-OCR PyTorch FlashAttn 2.7.3 In...
Comprehensive guide for DeepSeek-OCR local/private deployment based on Python 3.12, PyTorch 2.6.0, Transformers 4.46.3 and FlashAttention 2.7.3. Includes ~3B parameter model inference, deployment o...
AI Research #120: DeepSeek-OCR from 0 to 1 - Getting Star...
Complete getting started path and engineering essentials for DeepSeek-OCR (as of 2025), covering environment setup (Python/PyTorch 2.x, Transformers 4.x), model loading, output parsing, parameter e...
AI Research #118: Embodied AI Mobile-ALOHA - Mobile + Dua...
Mobile-ALOHA: An open-source mobile manipulation solution combining mobile chassis and dual-arm collaboration. Uses whole-body teleoperation for low-cost...
AI Research #117: Tesla FSD Vision Analysis - Multi-camer...
Detailed analysis of Tesla's 3D rendering (Occupancy Network): multi-camera spatiotemporal fusion → voxel occupancy → bird's eye coordinates. Explains why it...
AI Research #116: Tesla HW3.0 vs HW4.0 - Camera Resolutio...
Comprehensive comparison of Tesla HW3.0 and HW4.0 hardware: camera resolution upgraded from 1.2MP to 5MP with better HDR/night vision; FSD computing power...
AI Investigation #108: Complete Robot Model Training Proc...
Full robot training pipeline: pre-training, fine-tuning (LoRA), reinforcement learning, imitation learning, and human feedback for safe autonomous decision-making.
AI Investigation #107: RL and Robot Training Data Format ...
Data formats and development processes in robot and reinforcement learning systems, including time series trajectories, state-action pairs, offline RL data,...
AI Investigation #106: Robot Learning Data Collection Too...
Core data collection methods and application scenarios, covering over ten methods from manual entry, sensor collection, web crawlers, API calls, log collection...
AI Investigation #105: Robot Learning Data Collection - F...
Data collection is a critical step in robot learning development, covering demonstration video collection, trajectory recording, state-action pair generation, and data quality control strategies.
AI Investigation #104: From Model Training to Robot Deplo...
AI model deployment optimization guide: ONNX conversion, TensorRT/OpenVINO inference engines, quantization (FP16/INT8), and real-time robotics applications.
AI Investigation #103: Embodied AI Technology Landscape
Comprehensive overview of embodied AI tech stack: hardware (GPU, sensors, actuators), software (ROS, simulation), and algorithms (deep learning, RL, VLA models).
AI Investigation #102: Intelligent Robotic Arms, Autonomo...
Different types of robots have huge differences in structure, tasks and control methods, so AI algorithm adaptation strategies also need to be tailored.
AI Investigation #101: Modern AI Methods - VLA, RT-1, RT-...
Modern AI robot control methods are undergoing a major transition from reinforcement learning and imitation learning to multimodal agents driven by large models. The combination of Vision-Language-...
AI Investigation #100: Modern AI Methods - Reinforcement ...
Modern AI methods for robot control cover Reinforcement Learning (RL), Imitation Learning (IL), and Transformer-based large model methods. Reinforcement...
AI Investigation #99: Sensor Fusion Technology - Camera, ...
Sensor Fusion is a core technology in autonomous driving, robotics and smart security. Through multi-sensor data fusion of cameras, LiDAR, radar, IMU,...
AI Investigation #98: Visual SLAM - ORB-SLAM, RTAB-Map, V...
Visual SLAM is a technology that achieves autonomous positioning and environment mapping without relying on LiDAR, using only cameras. By extracting environmental features (corners, edges, textures...
AI Investigation #97: SLAM Algorithm Comparison and Appli...
Multi-sensor fusion and SLAM are core technologies for robot perception and navigation. By fusing IMU, GPS, wheel odometry, LiDAR, visual odometry and other...
AI Investigation #96: Robot Scenario Testing - From Extre...
Complete guide to robot scenario testing, covering three dimensions: environment testing, load testing, and anomaly testing. Traditional manual testing has...
AI Investigation #95: Robot Scenario Testing - From Extre...
Before robots enter practical applications, systematic scenario testing must be conducted, covering boundary conditions like extreme weather, complex terrain,...