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The mechanics

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Analysis by ViralLoop — not written by the original author.

Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞) on AI · ViralLoop

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Post by Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞) on X

Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)@teortaxesTex

This is also what @ylecun means when saying that GPT-4 or "GPT-5000" doesn't have a cat's understanding of the world and can't anticipate simple physical causal chains not present in texts. It's easy to mock his dismissive takes – but, incredibly, there is evidence behind them.

223 likes21 repliesPosted Apr 11, 2024

View the original on X Written by Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞). Captured Sep 4, 2026.

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

From likes, comments.

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.
Opens on a negative, which reads as a warning and is harder to ignore than a claim.
Quotes someone directly, which makes the moment concrete rather than summarised.

The mechanics

Hook: Plain observation
Structure: Hook
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

Posts built the same way

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Hi! I'm one of the prompt writers that worked on this ad. It's a lot harder than people think! Prompts that my team used include: -make it funny -make it epic AND funny -funnier!!! Please be nice to my team as many of them will be laid off/replaced by AI

More from Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)

Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)

> The depth of the computation graph for our present frontier models, including Astra, is within a factor of two of GPT-4. so <240 layers? Makes sense, hardware punishes anything deeper, and training becomes harder too… But… been a while since we really Stacked More Layers.

Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)

This is important too Two more notes: - they don’t call models “exp” or “preview” as a joke. 3.2-exp was half a generation behind 3.2. Vision-Full will go crazy - nothing said on open weights so far

Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)

Defeated with cheap rewriting, definitely defeated if you train a rewriter against a reconstructed detector. Amusing GAN project actually But at least will help Pangram to deal with the low effort slop

Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)

DeepSeek: «We plan to raise the overall pricing for DeepSeek API services in the near future, with a significant increase expected. Please plan your usage accordingly» Oof. They originally promised price *cuts* in H2. given the market situation… they are heavily overloaded.

Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)

Ok these are pretty good scores …though some crucial agentic ones (NL2Repo, DeepSWE, Agent's Last Exam, AutomationBench) are surprisingly close to the new V4-Flash. But it has vision and it's a big boy. Also, for the first time ever, we'll see @htihle test Qwen-Max. interesting.

Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)

I really admire them. I respect the projects of other open teams too, but NOBODY comes close to DeepSeek's purism. For them, this really is the whole vision. No subscription promos, no clauses, no announcement at all. No mind games. «Intelligence. Too cheap to meter. Today. MIT»