It is wild that we still ask LLMs to think in plain text — the next 10x is in the latent stream.
Quick Answer
The article argues that relying on plain-text reasoning in LLMs leads to significant information loss.
Quick Take
Future advancements in reasoning quality will likely stem from latent-space reasoning that avoids tokenization, enhancing model performance and efficiency.
Key Points
- Plain-text reasoning in causes information loss.
- Latent-space reasoning could enhance reasoning quality by bypassing tokenization.
- Future advancements may significantly improve model performance.
- Current models may not fully leverage latent-space capabilities.
Article Excerpt
From source RSS / original summaryPlain-text chains of thought are an extraordinary information-loss interface. The next 10x in reasoning quality almost certainly comes from latent-space reasoning that bypasses tokenisation entirely.
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