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  3. vivo蓝河操作系统创新赛-蓝河AI创新应用开发
OpenAtomLLMAdvancedRegistration unverified

vivo蓝河操作系统创新赛-蓝河AI创新应用开发

A advanced llm competition requiring roughly 25–70 hours for an end-to-end practice run.

Difficulty
Advanced
Estimated effort
25–70 hours
Registration deadline
To be confirmed
Compute
Free GPU OK
OverviewPreparationSource

Overview

Who this competition fits

Advanced practitioners with experience in machine learning. Requires strong technical foundations and comfort with complex ML pipelines.

Read the original official blurb
vivo蓝河操作系统是面向通用人工智能时代自研的下一代智慧操作系统,创新性地使用Rust语言编写操作系统,并基于vivo蓝心大模型的智慧赋能,实现了自主、可控、先进、安全的智慧解决方案。 随着人工智能技术的蓬勃发展,与人工智能技术相结合的应用也将为用户带来新的智能体验。未来,操作系统在人机交互方式、应用生态繁荣等方面也将发生变革,操作系统的开发将更加注重智能化、协同化和个性化等服务型功能,开发范式将发生转变。如何结合操作系统特性开发出具有创新性的应用,具备一定挑战性。 Official category: 实战竞技赛. Organizers: vivo. Participants: 1999999.

Preparation

From registration to a first submission

  1. 01

    Python

  2. 02

    scikit-learn or similar ML library

  3. 03

    data analysis with pandas

Before you commit: Requires solid machine learning fundamentals and good experimental methodology. The competitive landscape is strong, with many experienced teams.

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 19, 2024

Entry assessment

est.
15

Prepare before joining

Overall fit estimate

Beginner fit15/100
Learning value67/100

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.

View data stateClose
Source page verifiedMetric confirmedReviewed
Source published
Sep 19, 2024
Source created
Sep 19, 2024
Published on this site
Aug 1, 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.