> I think this is it. LLM responses feel like the unconsidered ideas that pop into my head from nowhere. You have to look at the LLM as the inner voice in your

> I think this is it. LLM responses feel like the unconsidered ideas that pop into my head from nowhere. You have to look at the LLM as the inner voice in your head. We've kind of forced them into saying whatever they think due to how we sample the output (next token prediction), but in new architectures with pause tokens, we let them 'think' and they show better judgement and ability. These systems are rapidly going to improve and it will be very interesting to see. But this is another reason why I think they've surpassed human intelligence. You have to look at each token as a 'time step' in the inner thought process of some entity. A real 'alive' entity has more 'ticks' than what their actions would suggest. For example, human brains can process up to 10FPS (100ms response time), but most humans aren't saying 10 words a second. However, we've made LLMs whose internal processes (i.e., their intuition) is already superior. If we just gave them that final agentic ability to not say anything and ponder (which researchers are doing), their capabilities will increase exponentially > The other thing that makes me feel like we're 'getting there' is using some of the fast models at groq.com. Unlike perhaps many of the commentators here, I've been in this field for a bit under a decade now, and was one of the early compiler engineers at Groq. Glad you're finding it useful. It's amazing stuff.