ViralLoop

# The *actual* LLM scaling law. Adding more compute and data to LLMs makes them: - Linearly more expensive, and - Logarithmically more useful. Therefore: - Scaling becomes less useful the more you do it (once you reach a point where cost is non-trivial).

1.1K likes65 repliesPosted Feb 27, 2025

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Viral score

Based on absolute engagement — the platform doesn’t expose follower counts here, so large accounts score higher.

From likes, comments.

Why it worked

Opens with a short, self-contained line that is easy to take in at a glance.
Uses short lines and white space, which makes a long post feel quick to read.
Follows a clear Hook → List → List shape, so the reader always knows where they are.
Short enough to read in full without expanding, which removes a step before the point lands.
Short sentences keep the pace up, so the reader never has to re-read a line.

The mechanics

Hook: Plain observation
Structure: Hook → List → List
Style: Short lines with heavy white space, built to be scanned.
Tone: punchy
Written for: People building with AI

Analysis by ViralLoop — not written by the original author.

Post by Jeremy Howard on X