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OpenAI宋飏被Meta挖跑了!扩散模型崛起关键人物,加入MSL再会师清华校友赵晟佳

Core Viewpoint - Meta has successfully recruited Yang Song, a prominent researcher from OpenAI, which has raised significant interest in the AI research community due to his notable contributions to diffusion models and generative modeling [1][6][7]. Group 1: Yang Song's Background and Achievements - Yang Song is recognized as a key contributor to the rise of diffusion models and has been a leading figure in OpenAI's Strategic Explorations Team [10][11]. - He graduated from Tsinghua University at the age of 16 and later earned his PhD from Stanford University, where he worked under the guidance of a notable professor [20][36]. - His most famous work includes the development of Consistency Models, which outperform diffusion models in speed and performance, generating images significantly faster [12][14][17]. Group 2: Impact of Yang Song's Work - The Consistency Models developed by Yang Song can generate 64 images of 256×256 pixels in approximately 3.5 seconds, showcasing a substantial improvement over existing models [12][14]. - His research has led to the creation of Continuous-Time Consistency Models, which address stability and scalability issues in earlier models, achieving a training scale of 1.5 billion parameters [15][18]. - The advancements made by Yang Song and his team are considered potential game-changers in the generative modeling field, with discussions suggesting they could "end" the dominance of diffusion models [18][19]. Group 3: Meta's Strategic Recruitment - Meta's recruitment of Yang Song is part of a broader strategy to enhance its AI capabilities by attracting top talent from leading organizations like OpenAI [9][10]. - The move is seen as a significant loss for OpenAI, with many colleagues expressing surprise at his departure [7][6]. - The motivations behind such moves are speculated to extend beyond financial incentives, as many researchers prioritize impactful work and collaboration opportunities [9].