In unfamiliar market conditions, historical data-driven AI trading bots will falter

Group 1 - Current AI trading bots rely on limited historical data, making them ill-equipped to handle unprecedented market events like significant liquidations and severe selloffs [1] - Human intervention is deemed necessary for effective trading, as AI models struggle with unfamiliar market conditions [1] - Bitget CEO Gracy Chen likened current AI bots to interns, indicating they require supervision despite being faster and cheaper [2] Group 2 - The technology behind large language models (LLMs) and machine learning in trading is rapidly advancing, but many believe human oversight remains crucial, especially during volatile market conditions [3] - Saad Naj, CEO of PiP World, highlighted that 90% of day traders and retail investors incur losses, emphasizing the risks associated with current trading technologies [3] - Naj also noted that human emotions can hinder trading performance, suggesting that AI solutions may outperform human traders [4]