凭借 27 万小时真机数据，Generalist 可能是最接近“GPT-1 时刻”的顶级机器人团队

Core Insights - Generalist is a leading company in the robotics field with significant long-term competitive potential, focusing on data scale, team capability, and a clear scaling path [2][4]. Data Collection and Quality - High-quality real-world data is recognized as a core scarce resource in the robotics industry, with Generalist claiming to have accumulated 270,000 hours of training data, positioning it as the first robotics team to reach a data scale comparable to GPT-1 [4][6]. - The current mainstream methods for data collection include real machine data, human-operated data, pure video data, and synthetic data, with a consensus that real machine data is essential for training usable robotic models [5][6]. - Generalist's data collection strategy involves deploying thousands of data collection devices globally, utilizing egocentric data, and collaborating with data foundries to ensure diverse data sources [40][44]. Team and Technical Expertise - The core team of Generalist consists of members from prestigious institutions like OpenAI, Boston Dynamics, and Google DeepMind, contributing to significant projects such as PaLM-E and RT-2, showcasing strong technical capabilities [2][53]. - The team has demonstrated a clear research path and model dexterity through various demos, indicating a focus on achieving high levels of agility in robotic tasks [3][30]. Model Development and Performance - Generalist's GEN-0 model exhibits remarkable dexterity and the ability to perform complex tasks autonomously, showcasing its potential in physical interaction challenges [30][37]. - The model architecture employs Harmonic Reasoning, integrating perception and action tokens in a single Transformer flow, allowing for continuous and intelligent action generation [52]. Competitive Landscape - Generalist operates in a competitive environment with other companies like Physical Intelligence and Google, each with distinct strategies and strengths. Generalist's primary advantages lie in its extensive real machine data and strong team expertise, while facing challenges from competitors with more comprehensive team structures and funding [62][63]. - The company is positioned in the second quadrant of the robotics industry landscape, focusing on developing a general robotic brain, while competitors like Sunday are advancing faster in practical applications [61][62].