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Nathan Lambert on AI · ViralLoop

Post by Nathan Lambert on X

Nathan Lambert@natolambert

Open weight base models + incredible ML teams in a specific niche can create immense value. Congrats to all my friends on the cursor research team! (they said they did continued pretraining to enable effective scaled RL, super fun)

280 likes18 repliesPosted Mar 19, 2026

View the original on X Written by Nathan Lambert. 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.
Written from experience rather than as advice, which is harder to argue with.
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 → Landing
Style: Conversational paragraphs at a steady pace.
Tone: personal, energetic
Written for: People building with AI

Analysis by ViralLoop — not written by the original author.

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More from Nathan Lambert

Major restructuring at Gemini (Dean out, Hassabis no longer CEO). This story will be studied forever as the incumbant with all the advantages not being able to get going. P.s. OpenAI accomplished their original goal.

I read the Anthropic open-weight model piece and despite there being nothing new in it, it was a reasonable repeat of their positions, this site will collectively lose their minds for the next 12 hours. p.s. banning distillation is still dumb.

Kimi K3 license. It's inspired by MIT but distinctly non-commercial, where any company making over $20M/yr must get a specific commercial deal (and display Kimi K3 if over 100M users or $20M/mo revenue)

Qwen’s biggest models have never been open weight recently. Something is changing. You can imagine it like… Xi: no you’re not allowed to keep your best model closed anymore, we weren’t succeeding enough. A new era of competition for intelligence (if the benchmarks hold up).

Inkling was somewhat inevitable once Tinker took off -- integration of post-training services across @thinkymachines's entire stack -- and it's one of the best open-model business stories to date. Excited to see it grow and more emerge (some inference companies are next).

Thinky with a ~1T param, 41B active, apache-2 model Benchmarks are a clear step up from Nemotron Ultra (55B active), new best American model, and omni input. A bit behind GLM 5.2 on agentic benchies, and Kimi K 2.6 on multi modal Super exciting! Thank you @johnschulman2 & team