Summary
Researchers developed a new coding benchmark using esoteric programming languages like Brainfuck and Befunge-98 to accurately assess AI models' true reasoning abilities, rather than just pattern matching. This benchmark revealed that even top models like GPT-5.2, O4-mini, and Gemini, despite advanced prompting, achieved a mere 11% success rate. The findings suggest current AI models heavily rely on training data patterns and struggle significantly with novel problem-solving.
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