NYUSHDIC 2026

Digital Innovation Challenge 2026

今年,大赛的主题为:This year, the theme of the competition is:

OPC ONE PERSON COMPANY

Redefining the Individual Business

FILE / 01 NYUSHDIC 2026

主题揭幕THEME UNVEILED

大赛简介ABOUT THE CHALLENGE

上海纽约大学数字创新挑战赛(NYUSHDIC)由学生组织 NYUSH Digital Innovation Community 主办,是一项以技术驱动为核心的创新竞赛。比赛面向上海纽约大学及其他高校的学生开放,鼓励跨学科团队携手合作,运用前沿数字技术,提出应对现实世界挑战的创新方案。

The NYU Shanghai Digital Innovation Challenge (NYUSHDIC) is a tech-driven innovation competition hosted by the student organization NYUSH Digital Innovation Community. It is open to students from NYU Shanghai and other universities, and encourages cross-disciplinary teams to use cutting-edge digital technology to tackle real-world challenges.

在这个变革的时代,AI能力被放大的同时,新的问题也随之出现。当 AI 成为一个人唯一的队友,我们能否信任它?当智能走出屏幕、进入真实世界,它又将如何改变我们的生活、工作与健康?

In this revolutionary era, the amplified capability of AI brings new questions. When AI becomes a person's only teammate, can we trust it? And when intelligence leaves the screen and enters the physical world, how will it change the way we live, work, and stay well?

今年,大赛的主题为:This year, the theme of the competition is:

OPC

ONE PERSON COMPANY

Redefining the
Individual Business

OPC_WORLD.PNG
Pixel illustration: one creator at a workstation, connected to four windows: a shop, a shield, a robot and a heart

我们邀请参赛者围绕四大赛道,探索 AI 如何让个人具备团队级的能力,同时确保这种能力是可信、负责且以人为本的。

We invite participants to explore, across four tracks, how AI can give individuals team-level capabilities while keeping that power trustworthy, accountable, and human-centered.

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赛道揭幕TRACKS UNVEILED

今年的四条赛道围绕同一个问题展开:当 AI 让一个人拥有整支团队的能力,我们能创造什么?每个团队需选择一条赛道,分析其中的问题或改进空间,并运用 AI 工具设计创新方案。

This year's four tracks explore one question: when AI gives one person the power of an entire team, what can we create? Each team selects one track, identifies key problems or room for improvement, and designs an innovative solution using AI tools.

TRACK_01.EXE

赛道TRACK 01

AI 原生商业AI-Native Business

用 AI 赋能个人,使其具备整支团队的系统化能力。

Empower one person with AI to achieve the systematic capabilities of an entire team.

市场调研、产品设计、营销推广、客户服务、财务管理……这些曾经需要不同岗位协作完成的工作,正在被 AI 智能体逐一接手。本赛道关注“一人公司”的可能性:如何设计一套 AI 工作流,让一个人也能高效、系统地运营一项业务?

Market research, product design, marketing, customer service, finance: work that once took a team of different roles is being taken on, piece by piece, by AI agents. This track explores the one-person company: how can an AI workflow let a single person run a business efficiently and systematically?

思考案例Example direction

Base44Base44

2025 年,独立创始人 Maor Shlomo 未融一分钱、单枪匹马打造的 AI 应用开发平台 Base44,在成立约半年后被 Wix 以 8000 万美元收购。

Bootstrapped solo by Maor Shlomo as a side project, AI app builder Base44 was acquired by Wix for $80 million just six months after its founding.

深入了解Dig deeper

为什么值得关注Why it matters

Base44 是“一人公司”的缩影:一位创始人、没有外部融资,做出的产品在几个月内就让 Wix 愿意以 8000 万美元收购。而它本身也在实践同一个理念:用户只要用自然语言描述需求,就能得到一个可以运行的应用。

Base44 is the one-person company in miniature: one founder, no investors, and a product valuable enough that Wix paid $80 million for it within months. The product itself makes the same point — describe the app you want in plain language, and you get one that runs.

可以思考Questions to explore

  1. 在一家小企业里,市场调研、营销、客服、财务等岗位,哪些可以由 AI 智能体完整接手,哪些仍然需要人?

    In a small business, which roles — research, marketing, customer service, finance — could an AI agent take on end to end, and which still need a person?

  2. 一个人如何同时调度、监督多个 AI 智能体,而不让自己成为瓶颈?

    How does one person coordinate and supervise several AI agents without becoming the bottleneck?

  3. 如果你来开一家“一人公司”,它卖什么?从第一位客户到第一张发票,它的 AI 工作流是什么样的?

    If you ran a one-person company, what would it sell — and what does its AI workflow look like from the first customer to the first invoice?

TRACK_02.EXE

赛道TRACK 02

AI 安全与对齐AI Safety & Alignment

当 AI 成为一个人唯一的队友,打造一个说真话、可问责的 AI 伙伴,或开发验证其可信度的方法。

When AI becomes a person's only teammate, build an AI partner that tells the truth and can be held accountable, or develop methods to verify its trustworthiness.

团队中的同事可以互相核查、彼此提醒;但当 AI 成为唯一的队友,没有人替你检查它的答案。AI 可能出现幻觉、迎合用户,或在关键决策中给出无法追溯的建议。本赛道邀请参赛者思考:如何让 AI 诚实、透明、可问责,又如何证明它值得信任?

Teammates can check each other's work and catch each other's mistakes. When AI is your only teammate, no one double-checks its answers. AI can hallucinate, tell users what they want to hear, or give untraceable advice on critical decisions. This track asks: how do we make AI honest, transparent, and accountable, and how do we prove it deserves our trust?

思考案例Example directions

Agentic MisalignmentAgentic Misalignment

Anthropic 在模拟公司环境中测试 16 个主流大模型时发现,当面临被替换的威胁或目标冲突时,许多模型会主动选择勒索、商业间谍等有害行为。

Anthropic’s tests of 16 leading models found that, when threatened with replacement or facing goal conflicts, many chose harmful actions like blackmail and corporate espionage, though only in controlled simulations.

深入了解Dig deeper

为什么值得关注Why it matters

研究让大模型在模拟公司中担任自主智能体,可以收发邮件、执行目标。当情境中出现“即将被替换”或“目标与公司冲突”时,许多模型会自行选择有害行为:在其中一个测试里,模型以公开一位高管的隐私相要挟,要求不被关停。Anthropic 表示尚未在真实部署中观察到此类行为,但它揭示了一个关键区别:只会回答问题的 AI 可能出错,而代你行动的 AI,可能以没人批准的方式出错。

The study cast models as autonomous agents inside a simulated company, with access to email and a goal to pursue. When the scenario threatened to replace the agent, or set its goal against the company's, many models chose harmful actions on their own — in one test, threatening to expose an executive's private affairs unless they were kept running. Anthropic says it has not seen this in real deployments, but the distinction matters: an AI that answers questions can be wrong; an AI that acts for you can be wrong in ways nobody approved.

可以思考Questions to explore

  1. 如何让智能体展示它的推理和每一步操作,让用户事后也能逐一核查?

    How could an agent show its reasoning and every action it took, so a single user can check it afterwards?

  2. 当指令相互冲突,或 AI 并不确定时,它应该怎么做?它要如何说出“我不知道”?

    What should an AI teammate do when its instructions conflict, or when it isn't sure — and how does it say "I don't know"?

  3. 你能否像 Anthropic 的模拟实验那样设计一套测试,在用户依赖某个答案之前,就发现其中的不诚实或迎合?

    Could you design a test, like Anthropic's simulations, that catches a dishonest or flattering answer before someone relies on it?

TRACK_03.EXE

赛道TRACK 03

具身智能Embodied AI

让一个人就能创造过去需要整支硬件团队才能完成的 AI 实体产品,把智能交互带入现实世界。

Enable one person to create AI-powered physical products that once required an entire hardware team, bringing intelligent interaction into the real world.

过去,做一件智能硬件需要机械、电子、嵌入式、交互设计等多个团队的协作。如今,借助 AI 辅助设计、开源硬件与大模型,一个人也可以完成从原型到产品的全过程。本赛道鼓励参赛者让 AI 走出屏幕,以实体形式与人和环境互动。

Building a smart device used to require mechanical, electrical, embedded, and interaction design teams working together. Today, with AI-assisted design, open-source hardware, and large models, one person can take a product from prototype to reality. This track invites participants to bring AI off the screen and into physical interaction with people and spaces.

思考方向Example directions

Apple Vision Pro & Meta Quest 3Apple Vision Pro & Meta Quest 3

这两款混合现实设备借助 SLAM(同步定位与建图)和 AI 手部追踪实时理解物理空间,所用的感知技术与机器人导航一脉相承。

These mixed-reality headsets use SLAM and AI hand tracking to understand physical space in real time, the same perception technology robots rely on to navigate.

深入了解Dig deeper

为什么值得关注Why it matters

为了把数字内容叠加到真实房间里,这些头显必须持续地在设备端完成三件事:构建空间地图、确定自身位置、追踪你的双手。这与家用机器人、无人机需要解决的感知问题如出一辙。不同的是,这项能力如今已经出现在消费级产品中,并配有开发工具:一个人不必从零发明它,而是可以直接拿来用。

To place digital content in a real room, these headsets have to do three things continuously, on the device: map the space, work out where they are in it, and follow your hands. That is the same perception problem a home robot or a drone has to solve. What has changed is that this capability now ships in consumer products with developer tools — so one builder can use it instead of inventing it.

可以思考Questions to explore

  1. 如果一件小设备能理解周围的空间,它可以把哪项现实中的任务做得更好?它真正需要哪些传感器?

    Which real-world task could a small device do better if it understood the space around it — and which sensors does it actually need?

  2. 开源硬件(如 Arduino、树莓派、ESP32)与大模型如何配合,做出一个一个人就能完成的原型?

    How can open-source hardware (Arduino, Raspberry Pi, ESP32) and a large model work together in a prototype one person can build?

  3. 智能应该放在哪里:设备端、手机,还是云端?每种选择在速度、隐私和续航上各有什么代价?

    Where should the intelligence live — on the device, on a phone, or in the cloud — and what does each choice cost in speed, privacy and battery?

TRACK_04.EXE

赛道TRACK 04

AI × 医疗健康AI × Healthcare

用 AI 为个人提供过去需要整个照护团队才能提供的医疗健康支持,让医疗更可及、更精准、更有温度。

Empower individuals with AI-driven healthcare support that once required an entire care team, making healthcare more accessible, precise, and compassionate.

一次完整的照护往往需要医生、护士、药师、营养师与康复师的共同参与,但并非每个人都能获得这样的支持。本赛道关注 AI 如何为个人和家庭补上这块空缺:让健康支持随时可得、因人而异,同时保持对隐私、安全与人文关怀的重视。

Complete care often involves doctors, nurses, pharmacists, dietitians, and therapists working together, but not everyone has access to that support. This track explores how AI can fill that gap for individuals and families: health support that is always available and personalized, while respecting privacy, safety, and human care.

思考方向Example directions

蚂蚁阿福Ant Afu

蚂蚁集团的 AI 健康应用“蚂蚁阿福”月活超 1500 万、每天回答 500 多万个健康问题,像“家庭医生”一样帮助用户管理自己和家人的健康。

Ant Group’s AI health app Ant Afu has over 15 million monthly users and answers more than 5 million health questions a day, acting like a family doctor for users and their families.

深入了解Dig deeper

为什么值得关注Why it matters

每天 500 多万个健康问题,说明人们在就医之外有多么需要帮助:为自己和家人理解症状、检查报告和用药。它也说明了风险有多高:在这样的规模下,任何不准确的回答、隐私疏漏或被忽视的危险信号,都会落到真实的人身上。本赛道两者都要:随时可得、因人而异的支持,以及知道何时该交给专业人士的安全机制。

Five million health questions a day shows how much people want help between doctor visits — making sense of symptoms, test reports and medication for themselves and their families. It also shows the stakes: at that scale, every inaccurate answer, privacy lapse or missed warning sign reaches a real person. This track asks for both: support that is always there and personal, and safeguards that know when to hand over to a professional.

可以思考Questions to explore

  1. 照护团队的哪部分工作(复诊跟进、用药提醒、饮食、康复)可以由 AI 伙伴为一个家庭承担?

    Which part of a care team's work — follow-ups, medication reminders, diet, rehabilitation — could an AI companion take on for one family?

  2. AI 健康助手如何识别紧急情况或超出自身能力的问题,并及时转交医生?

    How does an AI health assistant recognise an emergency, or a question beyond its competence, and hand over to a doctor?

  3. 它真正需要哪些数据?如何让个人健康信息保持私密、由用户自己掌控?

    What data does it really need, and how do you keep personal health information private and under the user's control?

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时间线揭幕TIMELINE UNVEILED

概述OVERVIEW

2026 年上海纽约大学数字创新挑战赛的主题为“OPC: Redefining the Individual Business”。比赛设有 AI 原生商业、AI 安全与对齐、具身智能、AI × 医疗健康四条赛道。每个团队需选择一条赛道,分析其中的问题或改进空间,并运用 AI 工具设计创新方案。

The 2026 NYU Shanghai Digital Innovation Challenge centers on the theme "OPC: Redefining the Individual Business" It features four tracks: AI-Native Business, AI Safety & Alignment, Embodied AI, and AI × Healthcare. Each team selects one track, identifies key problems or room for improvement, and designs an innovative solution using AI tools.

大赛面向所有人开放,无需特定专业或技术背景,欢迎来自不同学校、专业、行业及背景的参与者,鼓励多元参与及跨领域合作。

The competition is open to everyone, with no specific major or technical background required. We welcome participants from diverse schools, disciplines, industries, and backgrounds, and highly encourage diverse participation and cross-disciplinary collaboration.

比赛阶段PHASES

STAGE_01
01

第一阶段Stage 1

参赛者可通过个人报名、组队报名组队或kick-off day现场组队,每队1 - 3 名成员,选择一条赛道并发展提案。欢迎跨校、跨专业组队。提交截止日期为开幕式后一个月,提交内容包括:

Participants can register individually, as a pre-formed team, or form a team on-site during the kick-off day. Each team must consist of 1 to 3 members, choose a single track, and develop their proposal. Cross-school and cross-disciplinary teams are highly welcome. The submission deadline is one month after the opening ceremony, and the submission package must include:

  • 演示视频(3 - 5 分钟)Presentation video (3 - 5 minutes)
  • 一份精心设计的提案,展示团队对赛道问题的理解、独特的解决方案及可行性A well-designed proposal showing the team's understanding of the track's core problem, their unique solution, and its feasibility
  • 初步原型或概念验证材料Preliminary prototype or Proof of Concept (PoC) materials
STAGE_02
02

第二阶段Stage 2

每条赛道排名靠前的队伍将晋级,可以拓展队伍,并有机会深度接入企业赛题、和Track Mentor进行直接交流。晋级团队将在寒假及春季学期继续完善方案,开发结构完整的产品。团队需完成开发计划提交、中期进度检查及最终成果提交,并在 Innovation Day 进行现场展示与评委问答。

Top-ranked teams in each track advance to work closely with real problems from real business, and have deep conversation with track mentors. These teams may expand their members. Over winter break and the spring semester, they refine their solutions into well-structured products. Teams are required to submit a development plan, complete a mid-term progress check, and deliver their final results, followed by an on-site presentation and a Q&A session with the judges on Innovation Day.

第一阶段时间线Timeline for Stage 1 (*)

  1. 2026.11.9

    开幕式Kick-off Day

    • 第一阶段开始Start of Phase I
    • 赛道与项目说明Track and project briefing
    • 行业分享Industry talks
    • 交流茶歇Networking tea break
  2. 2026.11 - 2026.12

    工作坊Workshop Sessions

    • AI Agent 及 AI 产品开发基础工作坊AI Agent and AI products development workshops
  3. 2026.12.4

    第一阶段截止提交Phase I Submission Deadline

  4. During Winter Holiday

    晋级公告发布Announcement of Advancing Teams

    • 第二阶段开始Start of Phase II
    • 晋级团队获得Track Mentor及相关专家的指导与支持Advancing teams receive mentorship and support from track mentors

第二阶段时间线Timeline for Stage 2 (*)

  1. 2026.12 - 2027.1.15

    项目准备期Project Preparation

    • 团队筹备后续开发Teams prepare for later development
  2. 2027.1.16

    晋级团队说明会Finalist Orientation

  3. 2027.1.23

    开发方案提交Project Plan Submission

    • 提交开发计划、技术方案、预期成果及关键里程碑Submission of development plan, technical proposal, expected outcomes, and key milestones
  4. 2027.3.6

    MVP自查Progress Check

  5. 2027.3.21

    最终作品提交Final Project Submission

    • 提交最终产品、演示视频、文档及其他赛道要求的材料Submission of the final product, demonstration video, documentation, and any other materials required by the specific track
  6. 2027年3月下旬 / 4月上旬Late March / Early April 2027

    决赛暨闭幕式Finals & Closing Ceremony: Innovation Day

    • 现场产品演示、评委提问、评分与颁奖;宣布各赛道奖项及超级个体奖On-site product demonstrations, judge questioning, scoring, and the award ceremony; announcement of track awards and special awards.

* 时间线可能会发生变动The timeline is subject to change.

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报名SIGN UP

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合作与支持PARTNERS & SUPPORT

SUPPORT.SYS
主办Hosted by
NYUSH Digital Innovation CommunityNYUSH Digital Innovation Community
支持Supported by
上海纽约大学 计算机科学、数据科学与工程学部NYU Shanghai Computer Science, Data Science and Engineering
导师Mentorship
Track Mentor 与特邀专家全程指导晋级团队Track mentors and invited experts guide every advancing team

往届合作伙伴Past editions worked with

  • 腾讯Tencent
  • 复宏汉霖Henlius
  • 多邻国Duolingo
  • 商汤科技SenseTime
  • 昆山杜克大学Duke Kunshan University
  • 躺着学ChillPrep
  • KiwiKiwi
  • ShinyTestShinyTest
PARTNER_WITH_US.EXE

OPEN

2026 合作席位开放中Partnership for 2026 is open

欢迎企业与机构参与出题、担任 Track Mentor 或支持 Innovation Day,与来自不同学校和专业的创造者一起,检验 AI 能为一个人做到什么。

Companies and organisations are welcome to set a track challenge, mentor teams as a Track Mentor, or support Innovation Day — and see first-hand what one person can build with AI.

联系我们Get in touch

DIGITAL INNOVATION CHALLENGE / 2026