According to God of Prompt on Twitter, an analysis of 2,487 AI research papers reveals that 87% of claimed 'safety advances' are driven by benchmark-specific optimizations such as lower temperature settings, vocabulary filters, and output length penalties. These methods increase benchmark scores but do not enhance underlying reasoning or generalizability. Only 13% of the papers present genuine architectural innovations in AI models. This highlights a critical trend in the AI industry, where most research focuses on exploiting existing benchmarks rather than exploring fundamental improvements, signaling limited true progress in AI safety and significant business opportunities for companies prioritizing genuine innovation (Source: God of Prompt, Twitter, Jan 14, 2026).