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The recent resignation of a senior AI researcher who described the culture at a leading AI firm as “broken” underscores growing worries about safety and governance in the fast‑moving artificial‑intelligence sector. For quantitative traders, the episode is a reminder that the same pressures—rapid model deployment, limited data, and aggressive performance targets—also affect financial machine‑learning pipelines. Understanding how high‑dimensional methods behave under data scarcity and how to guard against over‑fitting can protect portfolios from hidden model risk. The warning signal from the AI industry The former employee’s criticism centers on two points: insufficient caution in model development and a trajectory that may become “unacceptable” without stronger safeguards....