Prototype Phase

Phase Overview 

The Prototype Phase is the entry point for this year’s Nittany AI Challenge. Participants will develop prototypes and submit a video that demonstrates functionality.

Prototype Definition: A prototype is a preliminary version of a product, system, or process that is created to test and evaluate its design and feasibility before it is fully developed and launched. It serves as a model or a tangible representation of an idea. 

Using the prototype definition, your team’s prototype should clearly convey your model or idea. It would be beneficial for you to demonstrate how AI is being used, which is directly aligned with the first criterion in the rubric. For example, if you are using a large language model (LLM), your team will score higher if you demonstrate how it is being used. 

At the start of this year’s Challenge, participating teams will deliver a 5-minute (or less) video demonstration of their prototype, which will be submitted to a panel of judges. The video must be accompanied by supporting information, providing contextual details related to the prototype. The information required for the judging panel includes:

  • Team info – project/MVP title; name, campus, and college of each team member; name, email, and phone number of the primary point of contact.
  • Problem/Opportunity Statement – this should demonstrate that you clearly understand the problem or opportunity you are addressing with AI.
  • MVP Use Case – describe how someone will use the MVP functionality you intend to build and the benefits or impact the MVP will provide.
  • Data availability – detail the data sources leveraged within the prototype as well as the data sources necessary for the MVP.
  • Technology – describe the technology being used in the prototype along with any additional technology planned for the MVP.

In summary, your submission must include the above information, along with the video demonstration. We are not requiring teams to submit code in this Prototype Phase. However, if you have not started creating your prototype, i.e., coding your system, before the January 24 deadline, you are likely going to be playing catchup if your team is selected for the MVP Phase.

Important dates for the Prototype Phase of the Nittany AI Challenge include:

  • Wednesday, January 24, 2024, by noon (ET)Submit your prototype. Important note: you can only do this once. Once the form is submitted, it cannot be edited. 
  • Friday, February 2, 2024 — Prototype winners will be announced.

The reviewers may include a mix of:

  • content or domain experts related to the challenges
  • technical experts fluent in AI/ML capabilities
  • industry representatives
  • Penn State staff and decision makers

Panelists will review the video overviews and completed form information and provide teams the opportunity to answer in an online discussion group. Teams will be responsible for responding to all questions posed by reviewers within a set period prior to the submission of the final reviews.

Video Overview

All teams submitting a prototype for review are required to submit video demonstrations of their working prototypes. The videos must:

  • be no more than 5 minutes in length
  • explain the intent, goals, and potential impact of the solution
  • demonstrate the basic, working functionality of the prototype
  • be available through a YouTube link accessible for viewing by the Challenge reviewers

The production value of the videos will not be factored into the review, but they must clearly and accurately represent the prototype functionality. To help, Media Commons at Penn State provides free One Button Studio options throughout the Commonwealth.

Criteria for Review

The following criteria will be used in the selection process for the Prototype Phase of the Nittany AI Challenge.  View the full rubric (PDF).

Innovation & Technical Merit (10 points) 

  • Does the prototype demonstrate a novel use of AI, or does it improve upon existing solutions in a significant way?
  • Is the underlying AI model robust, accurate, and efficient?
  • How well has the team addressed potential technical challenges and limitations of their solution?

Impact and Relevance (10 points) 

  • Does the prototype address a pressing or significant issue within its chosen area (education, environment, humanitarianism, health)?
  • How scalable is the solution, and what potential does it have to create widespread positive change?
  • Is there clear evidence or data supporting the prototype’s potential impact?

User Experience & Accessibility (10 points)

  • Is the prototype user-friendly, intuitive, and accessible to a diverse range of users, including those with disabilities?
  • How well has the team considered the cultural, socio-economic, and demographic differences of potential users?
  • Are there mechanisms in place to collect user feedback and iterate upon it?

Ethical Considerations (10 points)

  • How well does the prototype address potential ethical concerns, including data privacy, fairness, and transparency?
  • Is there a plan in place to handle unintended consequences or misuse of the technology?
  • Has the team demonstrated an understanding of the broader societal implications of their solution?

Feasibility and Implementation (10 points)

  • How realistic is the prototype’s implementation in real-world scenarios?
  • Is there a clear roadmap for moving from the prototype stage to full deployment?
  • Has the team considered the economic, infrastructural, and regulatory challenges of their solution?