Hackernews posts about LLM
LLM is a type of large language model that uses artificial intelligence and machine learning algorithms to generate human-like text responses.
- How I use LLMs to learn complex topics (laurentiugabriel.github.io)
- Stealing Reasoning Traces from Proprietary LLM APIs (stolen-thoughts.com)
- Your intellectual fly is open when you use an LLM to author a post (2025) (bcantrill.dtrace.org)
- I trained a small transformer in 1.5hrs and it beats many LLMs (mvakde.github.io)
- I were 17, I'd learn how to build LLMs from scratch (twitter.com)
- Show HN: Needle2: 14MB agentic LLM for phones, wearables, smart home and robots (cactuscompute.com)
- Why your local LLM feels dumber than it is (forum.level1techs.com)
- My agent.md to improve LLM-assisted code quality (fabiensanglard.net)
- LLMs as a Cognitive Virus (arxiv.org)
- Porting my 1993 Amiga game to Godot, with an LLM reading the 68000 assembly (babyloniantwins.com)
- I accidentally turned LLM memory into program analysis (pwning.systems)
- What sort of maths are LLMs good at? (gowers.wordpress.com)
- What happens when an LLM never sees material beyond fifth grade? (littlelearner-ll.github.io)
- Humanising LLM Outputs Is Dumb (kuber.studio)
- Extensible Software in the age of LLMs (jeremymorrell.dev)
- “Next-token predictor” is the wrong mental model for LLMs (gmcgoldr.github.io)
- The efficient frontier of LLM inference (www.baseten.co)
- The shrinking landscape of linguistic diversity in the age of LLMs (www.nature.com)
- Show HN: ThoughtDAG – An editable context graph for LLM conversations (chenxiachan.github.io)
- Changes to Sourcehut's terms of service regarding LLMs (sourcehut.org)
- LLMs: Intelligence vs. Cost (openteams.com)
- LLMs and self-referentiality (scottaaronson.blog)
- Show HN: A tiny LLM running at 21,000 tok/s on a $250 FPGA (Live Demo) (www.mikeayles.com)
- Guess which of these LLM outputs is watermarked (sgoedecke.github.io)