Silicon Valley Is Obsessed With the Wrong AI

The article argues that Silicon Valley's focus on scaling large language models (LLMs) represents a brittle technical foundation that may not justify the trillion-dollar datacenter investments being made, and suggests alternative approaches like Tiny Recursion Models (TRMs) could achieve AI competence where LLMs fail while requiring dramatically lower computational costs. The author contends that while AI possesses genuine value, the industry has conflated scaling LLMs with inevitable progress without examining fundamental technical vulnerabilities or exploring more efficient alternatives.

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