前OpenAI研究员告诉你为啥AI模型不能光靠堆算力，得砸钱搞专业数据。
前OpenAI研究员Andrew Ho和剑桥研究员Adam Hunt指出，大语言模型正变得专业化，在编码和数学上表现优异，但在其他领域停滞甚至退步。Ho离开OpenAI创办新公司，专注于专业训练数据。他预测AI实验室将在定向数据收集上投入超过1000亿美元，因为仅靠模型规模扩展已无法推动全面进步。
Ex-OpenAI researcher bets $100 billion will flow into training data because scaling alone won't cut it
Former OpenAI employee Andrew Ho and Cambridge researcher Adam Hunt see a growing problem with large language models. Instead of becoming more versatile, the models are becoming more specialized, excelling at coding and math while stagnating or even regressing in other areas. Ho is leaving OpenAI to start a company focused on specialized training data and predicts that AI labs will need to spend more than $100 billion on targeted data collection. The article Ex-OpenAI researcher bets $100 billion will flow into training data because scaling alone won't cut it appeared first on The Decoder .