essenceX

4 ms·

1. 1.▲
   The Engineering Constraints of Distributed LLM Inference over the Open Internet(siliconandsoul.substack.com)

   2 points by essenceX 5mo ago|0 comments
2. 2.▲
   An analysis and chain of thoughts Continual learning,memory and context problem(siliconandsoul.substack.com)

   1 points by essenceX 9mo ago|1 comments
3. 3.▲
   by essenceX 9mo ago

   Tried connecting the dots between continual learning, memory, and context limits in LLMs, and how this lines up with ideas from the Nested Learning paper. The core gap seems to be the same: models can process more tokens, but they still don
4. 4.▲
   by essenceX 2y ago

   Reasoning in llms have catered long discussions...and since building word squares takes iterative reasoning and backtracking I thought let's ask llms to do it..The results were fascinating...Deepseek showcased profound reasoning wherea
5. 5.▲
   by essenceX 2y ago

   I recently tested the reasoning capabilities of LLMs by providing them with prompts to build word squares, a problem requiring iterative reasoning and backtracking. The results were fascinating! It was insightful to observe how these models