According to LessWrong, researcher Fernand0 defends a contrarian position: AI alignment research should pursue foundational theory, not incremental improvements to current systems. Using a Newton analogy, Fernand0 argues that 1666 scholars studying cooling coffee or falling objects missed what Newton understood—that deeper mathematical principles like differential equations were needed. Similarly, Fernand0 contends, purely empirical work on today's AI systems might miss the core alignment challenge. If fundamental new principles must be discovered, incremental tweaks won't suffice.

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