{"repo":"ai-in-pm/Titans---Learning-to-Memorize-at-Test-Time","free":true,"listed":false,"github":"https://github.com/ai-in-pm/Titans---Learning-to-Memorize-at-Test-Time","clone":"git clone https://github.com/ai-in-pm/Titans---Learning-to-Memorize-at-Test-Time.git","description":"Multi-agent demo platform for Titans (arXiv:2501.00663) — neural networks that learn to memorize at test time. 7 AI agents, native desktop UI.","language":"Python","stars":337,"topics":["ai","ai-agent","test-time-compute","titans","anthropic","deep-learning","llm","memory-augmented-neural-networks","openai","python"],"license":"MIT","category":"ai-agents","readme_excerpt":"🧠 Titans: Learning to Memorize at Test Time An interactive multi-agent demonstration platform for the landmark Titans architecture — the first neural network to learn how to memorize at test time. --- ✨ What Makes This Special The Titans paper introduces a groundbreaking memory architecture that learns what to remember during inference — no more fixed context windows. This repository brings those ideas to life with: - 7 specialized AI agents , each embodying a different perspective on the Titans architecture - Native desktop UI with real-time telemetry, interactive charts, and live visualization - Side-by-side agent collaboration — watch how GPT-4, Claude, Mistral, Groq, Gemini, Cohere, and Emergence reason about the same memory problem - Zero-friction setup — runs with a single command, even if only one API key is configured --- 🚀 Quick Start Windows users: Run titans.bat (handles path setup automatically) or launch titans.exe for a bundled, dependency-free experience. --- 🤖 The Seven Agents Each agent explores a distinct component of the Titans architecture through a different LLM lens: # Agent Provider Titans Role --- ------- ---------- ------------- 1 Neural Memory Module OpenAI (GPT-4) Core long-term memory model 2 Memory as Context Anthropic (Claude) Attention-based context memory 3 Memory as Gate Mistral Gating mechanism for memory flow 4 Memory as Layer Groq Per-layer memory integration 5 Experimental Validation Google Gemini Benchmarking & ablation analysis 6 Inno","default_branch":null,"files":null,"tree":[],"storefront":"/r/ai-in-pm","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ai-in-pm/Titans---Learning-to-Memorize-at-Test-Time/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}