Titans + MIRAS: Helping AI have long-term memory
research.google uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Learn more We strive to create an environment conducive to many different types of research across many different time scales and levels of risk. Our researchers drive advancements in computer science through both fundamental and applied research. We regularly open-source projects with the broader research community and apply our developments to Google products. Publishing our work allows us to share ideas and work collaboratively to advance the field of computer science. We make products, tools, and datasets available to everyone with the goal of building a more collaborative ecosystem. Supporting the next generation of researchers through a wide range of programming. Participating in the academic research community through meaningful engagement with university faculty. Connecting with the broader research community through events is essential for creating progress in ev
Titans + MIRAS: Helping AI have long-term memory Skip to main content Titans + MIRAS: Helping AI have long-term memory December 4, 2025 Ali Behrouz, Student Researcher, Meisam Razaviyayn, Staff Researcher, and Vahab Mirrokni, VP and Google Fellow, Google Research We introduce the Titans architecture and the MIRAS framework, which allow AI models to work much faster and handle massive contexts by updating their core memory while it's actively running. Quick links Titans paper MIRAS paper Share Copy link × The Transformer architecture revolutionized sequence modeling with its introduction of att
Explore this link on the map →related reading
- [2501.00663] Titans: Learning to Memorize at Test Timearxiv.org
- Aman's AI Journal • Primers • Ilya Sutskever's Top 30aman.ai
- NL.pdfabehrouz.github.io
- Reimagining LLM Memory: Using Context as Training Data Unlocks Models That Learn at Test-Time | NVIDIA Technical Blogdeveloper.nvidia.com
- Why We Need Continual Learning | Andreessen Horowitza16z.com
- On the Tradeoffs of SSMs and Transformers | Goomba Labgoombalab.github.io
- Mamba: The Easy Wayjackcook.com
- Memory makes computation universal, remember?thinks.lol
- [2111.00396] Efficiently Modeling Long Sequences with Structured State Spacesarxiv.org
- Extending Context is Hard | kaiokendevkaiokendev.github.io
- Explore | alphaXivalphaxiv.org
- Subquadratic — How SSA Makes Long Context Practicalsubq.ai