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Post by Ethan Mollick on X

Ethan Mollick@emollick

Here’s the CTO of Microsoft saying that the abilities of AI are going to continue to scale for the foreseeable future & exponential growth continues. Since MS is training the models, he knows more about what the impact of more compute will be than almost anyone. Worth noting.

593 likes29 repliesPosted May 21, 2024

View the original on X Written by Ethan Mollick. Captured Sep 4, 2026.

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Why it worked

Ends on a short line that is easy to quote and repeat.
Short enough to read in full without expanding, which removes a step before the point lands.

The mechanics

Hook: Plain observation
Structure: Hook → Landing
Style: Conversational paragraphs at a steady pace.
Tone: plain, matter-of-fact
Written for: People building with AI

Analysis by ViralLoop — not written by the original author.

Topics

AI Growth Health

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More from Ethan Mollick

Had early access to Gemini 3.8 Flash, it is a very good Flash model, but not equivalent to a frontier model, though. Here is Gemini 3.8 Flash's version of the shader with the same prompts (which it provided very quickly)

Had early access to Claude Fable 5.1. Its a real advance in long-run work that requires judgement and taste, but less of an advance in the Claudish. Here is a game from Fable 5.1 with retro graphics where you run an accurate space ship inspired by FTL t.co

The METR report on Hugging Face is really good and important but people are now comfortably ascribing way too many human motivations & personalities to the agents involved based on a CoT study made by overwhelmed & time-pressured researchers. Anthropomorphism can get in our way.

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If alignment issues are becoming big enough that OpenAI is willing to commit 20% of research inference compute to chain-of-thought monitoring, that suggests that alignment issues are becoming a pretty serious concern. We really need universal policies & standards across labs.

Oh no, we aren’t going to go back to this sort of prompting again, are we? I would love Anthropic to test if it actually works robustly, because our experiments (with slightly older models) found it did not.

Ethan Mollick on AI · ViralLoop