# Deepmind Ace

- **Event:** [OpenEnv Hackathon SF](https://cerebralvalley.ai/e/openenv-hackathon-sf)
- **When:** Mar 7 at 9:00 AM – Mar 8 at 12:00 AM (PST)
- **Where:** Shack15, San Francisco, CA
- **Placement:** Finalist
- **Team:** [Pranav Patel](https://cerebralvalley.ai/u/pranavp), [Himalaya Dua](https://cerebralvalley.ai/u/thebigdataguy)
- **GitHub:** https://github.com/himalayadua/VRAM
- **Website:** https://colab.research.google.com/drive/10onKNOy2ITdwphsfpvTJaOR4nexqULlh?usp=sharing
- **Demo video:** https://youtu.be/atz2ys6L_j8
- **Hugging Face:** https://huggingface.co/spaces/himalayadua/VOYAGER
- **Gallery:** https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery/50

Voyager-VRAM is a long-horizon workplace simulator where LLM agents must navigate a realistic office environment ( emails, Slack, shared drive, spreadsheets, calendars ) using 31 tools to complete multi-step project management tasks like preparing client briefs, resolving calendar conflicts, and reconciling budgets. 

On top of the environment we layer a Voyager-inspired learning system (skill library, working memory, episodic memory) with three types of memory probes (episodic, semantic, working), directly targeting the memory consolidation problem that current research (MEM1, Memory-R1) is trying to solve.

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Markdown version of https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery/50. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt