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S1: A $6 R1 competitor?

(timkellogg.me)
851 points tkellogg | 2 comments | | HN request time: 0s | source
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bloomingkales ◴[] No.42949616[source]
If an LLM output is like a sculpture, then we have to sculpt it. I never did sculpting, but I do know they first get the clay spinning on a plate.

Whatever you want to call this “reasoning” step, ultimately it really is just throwing the model into a game loop. We want to interact with it on each tick (spin the clay), and sculpt every second until it looks right.

You will need to loop against an LLM to do just about anything and everything, forever - this is the default workflow.

Those who think we will quell our thirst for compute have another thing coming, we’re going to be insatiable with how much LLM brute force looping we will do.

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zoogeny ◴[] No.42955806[source]
I can't believe this hasn't been done yet, perhaps it is a cost issue.

My literal first thought about AI was wondering why we couldn't just put it in a loop. Heck, one update per day, or one update per hour would even be a start. You have a running "context", the output is the next context (or a set of transformations on a context that is a bit larger than the output window). Then ramp that up ... one loop per minute, one per second, millisecond, microsecond.

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layer8 ◴[] No.42955958[source]
Same. And the next step is that it must feed back into training, to form long-term memory and to continually learn.
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1. zoogeny ◴[] No.42955988{3}[source]
I analogize this with sleep. Perhaps that is what is needed, 6 hours offline per day to LoRa the base model on some accumulated context from the day.
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2. dev0p ◴[] No.42965779[source]
LLMs need to sleep too. Do they dream of electric sheep?