Former OpenAI employee Andrew Ho and Cambridge researcher Adam Hunt have identified a growing issue with large language models. As these models become increasingly specialized, they excel in areas like coding and math but struggle in other domains. In response, Ho plans to launch a company focused on creating specialized training data. He predicts that AI labs will need to invest significantly in targeted data collection, potentially exceeding $100 billion, to improve the versatility of their models. This shift in focus highlights the limitations of relying solely on scaling to improve AI performance.
AI Model Limitations Spark Demand for Targeted Training Data
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