They Lied to You About AI (This Study Proves It)
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LLM Foundations80%
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Vishal Sikka, former Infosys CEO, Oracle board member, and Stanford PhD who studied under John McCarthy (the man who coined "artificial intelligence"), together with his son, published a paper proving fundamental limits of current AI agents and LLMs.
Using settled computational complexity theory from the 1960s, they show why transformer-based models hit a hard ceiling on computation per token due to self-attention, why hallucinations are mathematically unavoidable for certain tasks, and what this means for agentic AI in 2026.
Covers: fixed compute budget per response, solving vs verifying problems, Time Hierarchy Theorem implications, why longer agent chains compound errors, and the gap between hype and architecture reality.
Paper: "Hallucination Stations: On Some Basic Limitations of Transformer-Based Language Models" by Vishal Sikka & Varin Sikka
Keywords: AI agent limits 2026, LLM computational ceiling, transformer architecture constraints, why AI agents hallucinate, autonomous AI reliability, Vishal Sikka AI paper, AGI promises vs reality
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