LLMs have no structural place for non-knowledge
The article discusses the current trajectory of artificial intelligence and the potential for alternative approaches. It highlights Apple's focus on local models and dedicated hardware as a departure from the trend of centralization in AI. The author proposes a mathematical framework, VOID Theory, to explore the implications of these changes on the materiality of machine intelligence.
- ▪The technology industry is increasingly dependent on larger models and centralized cloud computing.
- ▪Apple has chosen to focus on local AI models and dedicated neural hardware, contrasting with other major tech companies.
- ▪The author has developed VOID Theory, which examines the relationship between computational cost, materiality, and the architecture of AI.
Opening excerpt (first ~120 words) tap to expand
What Your Model Will Never AdmitBetter living through honesty — or the lie at the heart of all large-scale modelsKonrad WojnowskiMay 17, 20261ShareWhat I am proposing in this text is a philosophical speculation — but one that tries to stay as close to the ground as possible. In fact, I am less interested in speculation itself than in a very practical question: is the current trajectory of artificial intelligence really the only possible one?Today, nearly the entire technology industry behaves as if the answer were obvious. Larger and larger models. Larger and larger data centers. Deeper and deeper dependence on the cloud. More and more computation performed somewhere far away from the user — inside infrastructures they neither see, control, nor increasingly even attempt to understand.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Hacker News (Newest).
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