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OpenAtomGeneral MLAdvancedRegistration unverified

AI+科研及具身智能开源挑战赛

A advanced general ml competition requiring roughly 24–80 hours for an end-to-end practice run.

Difficulty
Advanced
Estimated effort
24–80 hours
Registration deadline
To be confirmed
Compute
CPU only
OverviewPreparationSource

Overview

Who this competition fits

适合已有可开源AI项目、能够组队完成产品化交付的科研AI开发者、机器人/硬件工程师和Agent应用开发者。科研赛道需要能在真实科研场景验证模型、工具或框架;具身赛道需要实际硬件平台或明确硬件规范;Agent赛道需要处理社区问答数据、模型微调与API或Web部署。

Read the original official blurb
当前,全球正迎来以人工智能为核心的科技变革,AI正重塑科研范式、加速科学发现,并推动机器人与智能制造等物理智能系统的跃迁。开源已成为AI创新与扩散的关键引擎。赛事聚焦科研创新、具身智能与开发者服务三大方向,倡导“以赛促建、以赛促用、以赛促创”,鼓励全球开发者围绕真实场景开发高质量、可复现、可复用的开源项目,推动AI技术从单点突破迈向系统集成,从封闭研发走向开放协同,助力构建可信、共享、可持续的国产AI开源生态。 Official category: 实战竞技赛. Organizers: 魔搭社区,阿里云. Competition code: 2025OAC043. Participants: 5.

Preparation

From registration to a first submission

  1. 01

    开源项目文档编写

  2. 02

    实验复现与评测

  3. 03

    Python与AI模型开发

  4. 04

    模型部署

  5. 05

    技术演示视频制作

  6. 06

    路演答辩

Before you commit: 难点不只是做出模型,而是交付可审查、可复现、可开源的完整项目:代码、文档、示例、实验或测试报告,以及对应赛道的真实应用验证、硬件/仿真演示或可部署答疑系统。入围后还需参加线下路演,作品完整性和展示效果会直接增加准备工作。

Source

How this page was assembled

Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.

Official competition page
OpenAtom
Last checked
Sep 15, 2025

Entry assessment

est.
30

Prepare before joining

Overall fit estimate

Beginner fit30/100
Learning value60/100

Confirm eligibility and time commitment before moving into formal preparation.

Entry eligibility needs official confirmation

Open official pageSign in to saveOpen guide

Data and review state

Separate what is confirmed from what still needs review. Official rules and deadlines win.

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Source page verifiedMetric confirmedReviewed
Source published
Sep 15, 2025
Source created
Sep 15, 2025
Published on this site
Jul 21, 2026

Official metric is not published on the OpenAtom competition listing; verify scoring on the competition page.

reward_value_usd is a rough CNY→USD estimate (×0.14) for ranking only; use reward_summary for the official prize text.