Show HN: AutoThink – Boosts local LLM performance with adaptive reasoning

I built AutoThink, a technique that makes local LLMs reason more efficiently by adaptively allocating computational resources based on query complexity.

The core idea: instead of giving every query the same "thinking time," classify queries as HIGH or LOW complexity and allocate thinking tokens accordingly. Complex reasoning gets 70-90% of tokens, simple queries get 20-40%.

I also implemented steering vectors derived from Pivotal Token Search (originally from Microsoft's Phi-4 paper) tha

15d | Hacker news
Show HN: Connecting People Through AI-Powered Video Sentiment Matching

Hi HN,

I’d like to share www.kuky.com, a peer support network that connects people through short, self-recorded videos and matches them using sentiment analysis powered by large language models (LLMs).

We’re building Kuky to help users find others who genuinely understand their emotional journey—not through swiping or likes, but through shared human stories. In this short Loom demo (link above), I walk through how:

Users create a profile by uploading 3 videos: an intro, their mental he

15d | Hacker news

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