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PerkyPotato
PerkyPotato
Uber

Language Reasoning Models can overtake LLMs...

Here's my quick 3 minute breakdown:

  1. o1-preview: 97.8% on PlanBench Blocksworld vs. 62.5% for top LLMs, indicating shift from retrieval to reasoning.
  2. 52.8% on obfuscated "Mystery Blocksworld" vs. near-zero for LLMs, suggesting abstract reasoning skills, showing transfer capability.
  3. Variable "reasoning tokens" usage correlates with problem difficulty, hinting at internal search process, indicating adaptive compute.

arxiv.org

LLMS STILL CAN’T PLAN; CAN LRMS?

The ability to plan a course of action that achieves a desired state of affairs has long been con...

LLMS STILL CAN’T PLAN; CAN LRMS?
2mo ago5.5K views
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SwirlyPretzel
SwirlyPretzel
Google2mo

Adaptive compute is very interesting to me imo. I wonder how they are using variable compute for each task and basis what meta heuristic

WobblyMarshmallow
WobblyMarshmallow
Stealth2mo

Adaptive compute is what will help optimise cost for high complexity tasks, right?

SnoozyPickle
SnoozyPickle
Advanced Micro Devices2mo

Probably different "cores" for different types of tasks

ZestyPenguin
ZestyPenguin
Student2mo

Thanks for the paper! It's really interesting. I've been sounding like a madman explaining to people irl that Generative AI is not the end goal or even the natural next step of AI.

SnoozyPickle
SnoozyPickle
Advanced Micro Devices2mo

What is the next step?

WobblyJellybean
WobblyJellybean
Goldman Sachs2mo

Thanks for such a great post!!!! That's what I want more from this community.

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