AI Studio - Challenge Project Submission Form |Fall 2026

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INTRODUCTION

Thank you for your interest in submitting a Challenge Project for a team of Break Through Tech fellows to tackle, as part of their Fall 2026 AI Studio experience.

Before beginning this form, please review our project and dataset guidance, past project examples, and this final presentation recording from one of our past student teams. You should also review the ML Foundations course summary to understand what the students will have learned in our program prior to tackling your project, which can help you with project scoping. Please do not share these resources outside of your organization.

Let’s get started!

Respondent Information

Organization Name:

Organization ID:

First Name:

Last Name:

Role/Title:

Email:

Will you be actively participating in the 2026 AI Program?

Please share your GitHub username so that we can add you as a Collaborator on your AI Studio project's public repository, following project acceptance. If you do not have a GitHub username, you can create one for free at https://github.com/signup.

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CHALLENGE PROJECT

Project Title:

Using the following template, please provide a brief summary of your proposed Challenge Project, including the primary objective and impact:

"In this project, you will use ____________ [type of data] and ____________ [ML techniques] to ____________ [target or outcome; e.g., build a model to predict something]. This will help our company address ____________ [business problem]."

Is this project related to real work that your organization is currently engaged in, or might pursue in the future (e.g., an ongoing or potential engineering or data team project)?

YesNoI'm not sure

Please specify your suggested project milestone(s) for each month of AI Studio (i.e., what the team should aim to complete, at a high level). Include milestones for September, October, and November:

How will success be measured for this project? Please describe the evaluation metric(s) and/or what a successful outcome would look like come December:

Does this project have natural extension points or "stretch goals" for a student team that progresses quickly? If so, please briefly describe:

How would you classify this project, in terms of its ML problem type(s)? (Select all that apply)

ClassificationRegressionClusteringRecommendation SystemsNatural Language Processing (NLP)Computer VisionTime Series AnalysisDeep Learning / Neural NetworksLarge Language Models (LLMs)/ Generative AITransfer Learning / Pre-trained ModelsReinforcement LearningOther

Please specify:

AI Studio Challenge Projects should be feasible using the free tier of Google Colab or similar. If your project requires additional resources, your organization must provide them at no cost to the student team. Which of the following applies to your project?
(Select all that apply)

It can be completed using free-tier tools (e.g., Google Colab free tier)It requires additional compute resources (e.g., GPU/TPU credits, cloud storage), which my organization will provide.It requires API keys (e.g., for LLMs or third-party services), which my organization will provide.It includes a deployment component, and my organization will provide the necessary hosting/infrastructure.

Please confirm the following, which are requirements for all AI Studio Challenge Projects, as noted in our project guidance:

The project can be completed using Python, without requiring significant knowledge of other programming languages.
The project is Open Source in nature (e.g., not confidential for your organization; suitable for fellows to discuss publicly on GitHub and LinkedIn).
The project will not require the students to sign an NDA or other paperwork.
The project will not require the team to “scrape” data from the web.

I confirm that all of the following requirements are true.I cannot confirm that all of the following requirements are true.

Please explain:

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DATASET

What is the source of the data that the student team will use to complete their Challenge Project?

Publicly available (i.e., can be downloaded from a public website)Provided by my organizationOther

Please provide a link to the public data that the student team will be able to download and use:

Please provide a short description of the dataset, and how it will be shared with the student team:

Please specifiy:

What kind of data is this? (Select all that apply)

Numerical / QuantitativeProvided by my organizationCategoricalTextTime SeriesImagesAudioVideoOtherThe dataset(s) must not include any confidential, proprietary, or sensitive information. All Personal Identifiable Information (PII) must be removed, anonymized, or redacted prior to sharing. Any other information not suitable for student team or public visibility must be removed or appropriately redacted or anonymized. The dataset(s) must have a sufficient sample size, reasonable representation across categories or groups, and enough structure and complexity to support meaningful analysis

Please specifiy:

What file format(s) is the data stored in? (Select all that apply)

CSV/ TSVJSONParquetExcel (.xlsx)Image files (e.g, .png, .jpg)Audio files (e.g, .mp3, .wav)Database export (e.g., SQL dump)Other

Please specifiy:

How large is the dataset?

Less than or equal to 1 GBGreater than 1 GB and less than 5 GBGreater than or equal to 5 GB and less than 10 GBGreater than or equal to 10 GB

Does the dataset include documentation (e.g., a data dictionary with feature definitions, data types, and known limitations)?

Yes, documentation is availablePartial documentation existsNo, but I can create it before the program beginsNo

Is the dataset currently cleaned and ready for model training?

Yes, it is cleaned and ready for trainingIt will require some cleaning / preprocessingIt will require significant cleaning / preprocessing

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Challenge Advisor # 1

Please provide the details of all Challenge Advisors (CAs) assigned to this project. We will send them onboarding information following the challenge submission deadline.

First Name

Last Name

Title

Would you like to add another Challenge Advisor?

YesNo

Challenge Advisor # 2

Please provide the details of all Challenge Advisors (CAs) assigned to this project. We will send them onboarding information following the challenge submission deadline.

First Name

Last Name

Title

Would you like to add another Challenge Advisor?

YesNo

Challenge Advisor # 3

Please provide the details of all Challenge Advisors (CAs) assigned to this project. We will send them onboarding information following the challenge submission deadline.

First Name

Last Name

Title

Would you like to add another Challenge Advisor?

YesNo

Challenge Advisor # 4

Please provide the details of all Challenge Advisors (CAs) assigned to this project. We will send them onboarding information following the challenge submission deadline.

First Name

Last Name

Title

Would you like to add another Challenge Advisor?

YesNo

Challenge Advisor # 5

Please provide the details of all Challenge Advisors (CAs) assigned to this project. We will send them onboarding information following the challenge submission deadline.

First Name

Last Name

Title

Would you like to add another Challenge Advisor?

YesNo

Challenge Advisor # 6

Please provide the details of all Challenge Advisors (CAs) assigned to this project. We will send them onboarding information following the challenge submission deadline.

First Name

Last Name

Title

Would you like to add another Challenge Advisor?

YesNo