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Please see the Schedule and Judging Criteria for details.
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Entries for the Google DeepMind x Cactus Compute Global Hackathon hackathon.
Team not found: inkedin
Please see the Schedule and Judging Criteria for details.
We will evaluate all projects based on the following criteria, focusing on the successful implementation of local-first, agentic, hybrid AI systems:
| Criterion | Description | Scoring (1 to 5) |
|---|---|---|
| Functionality & Execution | Did the team ship a working demo that successfully integrates the required components? A score of 5 means the application runs smoothly on-device (mobile/desktop) with zero critical bugs. | 1: Project does not run or is entirely conceptual. 2: Major bugs prevent core functionality from being demonstrated. 3: Runs, but has significant stability or integration issues. 4: Runs reliably, demonstrates core features. 5: Flawless execution, robust on-device performance. |
| Hybrid Architecture & Routing | How effectively was the core challenge—deciding where computation happens (local vs. cloud)—solved? This judges the intelligence of the edge/cloud split. | 1: No clear local/cloud split; all logic is in the cloud. 2: Local execution is present but serves no meaningful purpose. 3: Simple, static routing between local (FunctionGemma) and cloud (Gemini). 4: Intelligent routing based on context (e.g., latency, complexity, connectivity). 5: Sophisticated, dynamic, and optimized routing that showcases seamless fallback/escalation. |
| Agentic Capability & Utility | Does the application demonstrate meaningful agentic behavior (reasoning, tool use, workflow coordination) that benefits from being local-first? | 1: Simple, non-agentic task execution. 2: Agent logic is present but trivial or easily replicated without agents. 3: Demonstrates basic agentic workflow using FunctionGemma. 4: Complex, useful agent workflow that leverages local speed for responsiveness. 5: Groundbreaking agent system that unlocks a new local-first UX pattern (e.g., real-time offline coordination). |
| Theme Alignment (Local-First & Tech Stack) | How deeply and creatively were FunctionGemma and Cactus Compute utilized to achieve local-first goals (latency, privacy, offline capability)? | 1: Does not use FunctionGemma or Cactus Compute, or uses them superficially. 2: Uses the required tech, but the solution would work identically in the cloud. 3: Clearly uses FunctionGemma/Cactus, but the privacy/latency benefits are not central to the demo. 4: Excellent use of FunctionGemma for speed/privacy, with Gemini used effectively for fallback. 5: The entire architecture is fundamentally dependent on the local-first capabilities unlocked by FunctionGemma/Cactus Compute. |
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