Aran Komatsuzaki on AI

Apple presents OpenELM - An efficient LM family with open-source training and inference framework - Performs on par with OLMo while requiring 2x fewer pre-training tokens repo: t.co hf: t.co abs: t.co

233 likes5 repliesPosted Apr 24, 2024

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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 concrete numbers instead of vague claims, which makes it credible and quotable.
Uses short lines and white space, which makes a long post feel quick to read.
Follows a clear Hook → List → Landing shape, so the reader always knows where they are.
Ends on a short line that is easy to quote and repeat.
The opening line stands alone, so it reads completely before the post is expanded.

The mechanics

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

Analysis by ViralLoop — not written by the original author.

Topics

AI Health Engineering

Post by Aran Komatsuzaki on X