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AI's true innovation lies in vectorization, not LLMs, experts say

By PulseAugur Editorial · [1 sources] ·

The core innovation in AI is not the large language models themselves, but the underlying vectorization technology that encodes language, images, and videos into high-dimensional spaces. These embeddings capture complex relationships that are not explicitly taught, representing a significant leap beyond rule-based AI. While current efforts focus on optimizing LLMs as interpreters for these vector spaces, the true potential lies in improving these semantic structures to accelerate AI development. AI

IMPACT Focusing on vectorization and semantic structures could unlock new capabilities beyond current LLM applications.

RANK_REASON The item is a discussion post on Reddit about the perceived core innovation in AI, rather than a primary announcement or research paper.

Read on r/singularity →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI's true innovation lies in vectorization, not LLMs, experts say

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The item is a discussion post on Reddit about the perceived core innovation in AI, rather than a primary announcement or research paper.
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COVERAGE [1]

  1. r/singularity TIER_2 English(EN) · /u/User4f52 ·

    Real futuristic stuff isn’t LLMs: it’s the vectorization. I think the next leap will come from embedding/improving the semantic structure itself

    <!-- SC_OFF --><div class="md"><p>Honestly, the main thing that interests me in this AI wave isn't the chatbots or the text generation. It's the vectorization.</p> <p>The fact that we can take language and encode it into a point in some high-dimensional space, and words, images a…

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