Some people seems to not get this: LLMs do not need to be the ASI themselves
Summary
The article argues that LLMs do not need to become ASI themselves; they can research and develop new AI models that might not be LLMs, leading to ASI through narrow super-intelligence.
Similar Articles
Can AGI be achieved with LLMs alone?
This post explores the debate among top AI figures regarding whether LLMs alone can achieve AGI or if additional breakthroughs like world models are required.
So were Illya and Yan Lecun both wrong? (LLMs are generalising.)
The article discusses whether AI critics Ilya Sutskever and Yann LeCun were wrong about LLMs not reaching human intelligence, as there is emerging evidence of LLMs generalizing across domains.
Choose what LLMs can and can’t do well
The article highlights that LLMs excel at ambiguous judgment tasks but are mediocre for consistent computation, advocating for task specialization in multi-agent systems.
LLMs Aren't Inevitable
A blog post arguing that the claim 'AI is inevitable' is a thought-terminating cliché, exploring what inevitability means for technologies and why LLMs likely don't meet those criteria given contingent social and cultural structures.
LLMs and Self-Referentiality
The article discusses how self-referentiality, once thought essential for AI, was not explicitly required in building advanced LLMs like GPT 5.6 Pro, challenging earlier ideas from thinkers like Douglas Hofstadter.