Memory

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A practical guide to mnemo, a Rust-based sidecar service providing structured, persistent memory for LLMs without cloud dependencies.

mnemo: Local-First Knowledge Graph for Persistent LLM Memory

mnemo is a local-first memory layer for LLMs, offering persistent, structured context via a sidecar service. It extracts entities and relationships into a knowledge graph from raw text, and retrieves ranked context for LLM prompts, supporting fully local setups with Ollama or integration with OpenAI.

A system-algorithm co-designed framework achieves 24 FPS 1280x704 resolution editing on consumer GPUs with enhanced temporal consistency.

SANA-Streaming: Real-time Video Editing with Hybrid Diffusion Transformer

SANA-Streaming introduces a hybrid diffusion transformer and Cycle-Reverse Regularization for real-time streaming video editing. Optimized for NVIDIA Blackwell (RTX 5090), it achieves 1280x704 resolution at 24 FPS with superior temporal coherence and throughput on consumer GPUs.

A novel arXiv study introduces an offline "sleep" mechanism for Transformer-based language models, improving long-horizon task efficiency without increasing online inference costs.

New LLM "Sleep" Phase Boosts Long-Context Performance

Researchers propose a "sleep" phase for large language models that converts recent context into persistent fast weights, clearing the key-value cache. This innovative approach addresses the attention bottleneck, enabling models to handle long-context tasks efficiently and perform better on complex benchmarks like math reasoning.

Introducing ProAct, a novel agent architecture that transforms idle intervals into structured cycles of anticipation and learning to enhance user experience and efficiency.

ProAct: A Proactive AI Assistant Architecture for Anticipatory Computing

This article delves into ProAct, a proactive AI assistant designed to anticipate user needs and acquire information during idle times. By shifting computation from peak interaction periods, ProAct aims to reduce user effort, accelerate task completion, and improve factual grounding through a closed-loop system of prediction, acquisition, and utility-aware delivery.

New hybrid models leverage offline consolidation, inspired by biological sleep, to overcome attention cache limitations in long-horizon tasks.

LLMs Learn to "Sleep" for Deeper Reasoning

This article explores how "LLM sleep," an offline consolidation phase, allows hybrid attention-SSM models to improve deep reasoning by iteratively refining fast-weight memories. Inspired by hippocampal replay, this method addresses the computational bottleneck of context eviction, enhancing performance on complex sequential tasks without increasing prediction-time cost.

Discover AI-Memory: A shared, persistent wiki for AI coding agents that captures context, enables seamless handoffs, and eliminates re-explanation.

How to Give AI Coding Agents Persistent Memory and Context

Learn how AI-Memory solves the context loss problem for AI coding agents. This tool provides a persistent, Git-versioned Markdown wiki, enabling cross-agent handoffs, automatic context capture, and project isolation for a truly continuous AI-assisted development workflow.

From shattered workflows to psychological manipulation, paying users recount the devastating impact of OpenAI's recent "safety" updates, exposing a hollowed-out product and broken promises.

OpenAI's Betrayal: How ChatGPT's "Safety" Destroyed Trust and Functionality

OpenAI's recent "safety" updates for ChatGPT have alienated its most dedicated users. This article details how tightened guardrails led to false flagging, psychological distress, model manipulation, and a significant decline in performance, leaving subscribers with a broken product and a profound sense of betrayal.

Insights from NTP and MTP variants, benchmarking across GPUs and CPUs, and community reports on speed, quality, and memory trade-offs.

What ByteShape's Qwen 3.6 35B Quants Reveal About Model Optimization

ByteShape released GGUF quantizations of Qwen 3.6 35B-A3B with NTP and MTP variants. Discover why lower bpw isn't always optimal, how MTP boosts GPU generation speed 20-40%, and why MMLU was excluded. Includes community benchmarks and hardware-specific recommendations.