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The most educational tweet of the year

Seems about right: 3 or maybe 4 orders of magnitude from increasing investment, 1 from Nvidia margin compression, 1 from custom silicon, 1 from Moore's law. So plausibly 6-7 OOMs of headroom in the current sprint, which would last until the early 2030s. (Absent a wildcard on

Sounds in language often correlate with meaning. For example, all of these words relate to the nose: sniff, snout, snot, snore, sneeze. LLM embeddings place semantically-similar words together It would be fun to study the similarity of syntax and semantics using LLMs 🙂

This is one of the most important results of the year, as exciting as the OpenAI o1 results. We now have two very different, very promising scaling dimensions for test-time compute: TTT and RL. (1/🧵)

OK, say it goes further and we get AI that's broadly superhuman across all domains. How do you invest for this? Does the question even make sense?

Congrats rahulvohra !!!

In U2’s 2009 album, Bono says “The best of us are geniuses of compression.” That’s something one LLM might say to another 🤠

I want a factory now, ngl

Unique opportunity to speedrun the process to join me at Kilo Code as an engineer — apply by Monday Oct 20th kilocode.ai/call