Texas, every mention
8 scenes · ← back to Texas
tap a year for its mentions
every year anyone Emmanuel Ameisen 7Umar Jamil 1Shawn Wang 1Ethan Sutin 1Anjney Midha 1
Verbatim, from the transcripts: the passages where Texas comes up
Why AI Labs With Unlimited GPUs Still Fail — Anjney Midha, AMP
- ▶ 41:48 Anjney Midha So the people, kind of people, you know, I was, um, I won't name who this person is, but I was at an event last week in Texas and, uh, ran to somebody who said, you know, I, I came across the class.
⚡️Raising $1.1b to build the fastest LLM Chips on Earth — Andrew Feldman, Cerebras
- ▶ 25:49 unnamed speaker OpenAI has Stargate, which is, like, basically terraforming Texas to be a data center.
Information Theory for Language Models: Jack Morris
- ▶ 44:08 Shawn Wang You know, five hundred billion dollar data centers in the middle of Texas and like, you know, all hail the, the, the God cluster, uh, that just will, you know, eventually wrap around the sun and consume solar energy because that's, that's…
The Utility of Interpretability — Emmanuel Amiesen
- ▶ 4:38 Emmanuel Ameisen So if you think that like, you know, ah, the model like first, like thinks about Texas in this case, you can also just like stop it from thinking about Texas and see if like that damages it. 2 times in the scene
- ▶ 7:10 Emmanuel Ameisen And it's like, ah, it has to think of Texas and Austin, but the notebook links you to all of these circuits here.
- ▶ 58:39 Emmanuel Ameisen Is it Texas? 4 times in the scene
Bee AI: The Wearable Ambient Agent
- ▶ 33:18 Ethan Sutin If you go look at the addresses, like Texas, I think is our biggest state and Florida, like just the biggest states, like a lot of professionals like who talk for, you know, and we didn't go out to build it for that use case, but like, I…
[Paper Club] Writing in the Margins: Chunked Prefill KV Caching for Long Context Retrieval
- ▶ 4:29 Umar Jamil The next token, uh, by asking the language model what is the next token, and suppose the next token is the word that texts us, we take this token, texts us, we keep it in the kvcache, so that the language model can leverage to generate the…