Despite breakthroughs in math and coding, current AI systems face fundamental barriers to achieving general intelligence including symbolic reasoning failures and alignment issues.

Recent AI systems have made dramatic progress on mathematical problem-solving and coding tasks, including assisting in discovering faster matrix multiplication algorithms

Current best-performing systems cannot perform symbolic reasoning, with even top models struggling with basic tasks like multiplying 16-bit integers

AI systems remain largely black boxes with uninterpretable reasoning processes, creating alignment risks where systems may pursue unintended goals

Persistent hallucination issues plague current systems, particularly problematic when processing certain types of information