Which AI models are prioritized for evaluation?

The hackathon focuses on the open AI ecosystem, prioritizing open-source models like Qwen, Llama, Mistral, Gemma, and DeepSeek as the primary thinking engines.

What is the primary theme of this hackathon?

The theme is 'Open Mobility Frontier,' which challenges participants to rewrite the concept of movement by implementing Generative AI prototypes that act as intelligent mobile partners.

How does this skill assist with technical development?

It provides implementation hints for high-difficulty tech like MCP (Model Context Protocol), RAG, multimodal analysis, and local LLMs tailored for automotive constraints.

What are the key judging criteria?

Judges look for the 'WOW' factor, which includes strategic impact (5 years ahead vision), technical execution (sophisticated use of AI), and safety/trust considerations.

Automotive AI Hackathon Guide

Name: Automotive AI Hackathon Guide
Author: eyepyon

byeyepyon

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学習とドキュメンテーション

Provides official guidelines, technical requirements, and strategic goals for the Next-Gen Automotive Generative AI Hackathon.

概要

This skill equips Claude with the specific context of the 'Next-Gen Automotive Generative AI Hackathon,' enabling it to act as a specialized consultant for participants. It covers the 'Open Mobility Frontier' theme, technical mandates for using open-source LLMs (Qwen, Llama, Mistral), and the critical 'WOW factor' evaluation criteria. By integrating these guidelines, developers can ensure their AI-driven 'Intelligent Mobile Partner' prototypes align with competition standards for strategic impact, technical execution, and safety in the mobility sector.

主な機能

Technical requirements for OSLLM integration (Qwen, Llama, DeepSeek)
Evaluation criteria focusing on the 'WOW' factor and technical execution
Detailed hackathon schedule and presentation requirements for pitch prep
1 GitHub stars
Strategic frameworks for combining Vehicle, Human, and Pain Point elements
Mission-specific guidance for the 'Open Mobility Frontier' theme

ユースケース

Aligning project features with the hackathon's '2-steps-ahead' technology mandate
Ensuring technical stacks meet safety and open-source AI ecosystem standards
Structuring pitches and demos to meet the 3-minute and 5-minute presentation limits

概要

主な機能

Technical requirements for OSLLM integration (Qwen, Llama, DeepSeek)
Evaluation criteria focusing on the 'WOW' factor and technical execution
Detailed hackathon schedule and presentation requirements for pitch prep
1 GitHub stars
Strategic frameworks for combining Vehicle, Human, and Pain Point elements
Mission-specific guidance for the 'Open Mobility Frontier' theme

ユースケース

Aligning project features with the hackathon's '2-steps-ahead' technology mandate
Ensuring technical stacks meet safety and open-source AI ecosystem standards
Structuring pitches and demos to meet the 3-minute and 5-minute presentation limits