Evaluating long-term memory limits in stateless LLM chatbots — feedback needed [

<!-- SC_OFF --><div class="md"><p>I organize everything by topic (work, study, documents, buying, recipes, etc.), and each topic stays in one long chat. Over time, those chats

<!-- SC_OFF --><div class="md"><p>How do you guys deal with long context, for example while coding, when you’re going back and forth for adjustments or fixing some errors and

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s1brq3/wmb100k_open_source_benchmark_for_ai_memory/"> <img alt="WMB-100K – open source benchmark for AI

<!-- SC_OFF --><div class="md"><p>I’ve been building Signet, an open-source memory substrate for AI agents.</p> <p>The problem is that most agent memory systems are still

<!-- SC_OFF --><div class="md"><p>I ask that because I was thinking about if that may be valuable in the future once llms improve more. </p> <p>Let’s imagine a perfect future

<!-- SC_OFF --><div class="md"><p>The news about Ulysses Sequence Parallelism enabling million-token contexts is fascinating for local LLMs. While the potential for deeper context

<!-- SC_OFF --><div class="md"><p>Hi there!</p> <p>My question(-s) are at the bottom, but let me tell you what I am trying to do and how, first:</p> <p>For my work-in-progress

<!-- SC_OFF --><div class="md"><p>Hello everyone,</p> <p>I’m looking for an AI that runs entirely locally on my PC, without needing an internet connection.</p> <p>I’d like it to