杨震原：2021 年字节团队曾训出大语言模型，但当时 “没眼光”

Core Insights - ByteDance has been actively exploring technology since its inception, focusing on large-scale machine learning systems for recommendation algorithms [1][5][34] - The company has made significant advancements in AI, particularly with its AI dialogue assistant "Doubao" and its leading position in the Chinese MaaS market through Volcano Engine [2][34] - ByteDance is investing heavily in XR technology, aiming to enhance user experience through improved hardware and software solutions [22][30] Group 1: Technology Development - In 2014, ByteDance set an ambitious goal to develop a recommendation system with a feature scale of one trillion, leveraging large-scale machine learning [5][9] - The company initially underestimated the potential of large language models, but quickly pivoted to invest in this area starting in 2022, leading to successful applications [34][35] - ByteDance has developed a stable training system called MegaScale, achieving a floating-point operation utilization rate exceeding 55%, which is 1.3 times higher than mainstream open-source frameworks [34] Group 2: AI and Machine Learning - The company has recognized the importance of large-scale data for creating valuable models and algorithms, particularly in the context of real-world applications [10][34] - ByteDance's AI dialogue assistant "Doubao" has become the most popular in China, showcasing the company's success in AI applications [2][34] - The company is also exploring advanced AI models, including the Seed Edge plan, which focuses on cutting-edge research in large models [35] Group 3: XR Technology - ByteDance acquired the Pico team in 2021 to enhance its XR capabilities, focusing on both content and foundational technology [22][30] - The company aims to achieve a pixel density (PPD) of nearly 4000, significantly higher than existing products, to improve clarity in XR experiences [26][29] - ByteDance is developing a dedicated consumer electronics chip to address processing bottlenecks in mixed reality applications, achieving a system latency of around 12 milliseconds [31][30]