일상생활속 금융, 증권이야기

AI, especially large language models (LLMs), continues to advance rapidly, but its limitations and issues are becoming increasingly apparent. AI, especially large language models (LLMs), continues to advance rapidly, but its limitations and issues are becoming increasingly apparent. Recent studies highlight that merely training AI on vast amounts of data is not sufficient. AI faces various problems such as data collapse, memory loss, and reasoning ability deficiencies. Let’s explore how these issues impact AI development. Recent research emphasizes the importance of data quality in AI, especially for LLMs. An experiment conducted by researchers at Oxford University found that when AI trains on data generated by other AI, the model's performance deteriorates significantly. This phenomenon, termed 'AI collapse,' occurs because AI continuously learns from repetitive and potentially low-quality information, resulting in degraded output quality. Another significant issue is ...