Welcome to
The STEAM in AI Multimodal Championship Season 2024-2025
A Global AI Competition with Ethics by Design for Middle and High School Students in Grades 6-12 across the world with no prior coding experience to learn AI, compete, win, and stand out in college applications.AI Challenge for this Season revealed!!
Here’s Your AI Challenge for Season 2024-2025
Create a personalized AI tutor system using Code, APIs such as OpenAI’s GPT, Gemini, any other AI models or a design concept that provides personalized tutoring by identifying learning gaps in subjects like math, science, or language arts and adapting content based on individual student pace and needs.
Each Team will work towards creating a personalized learning tutor system or design concept, tailored to improve student learning outcomes keeping in mind AI Ethics.
Pro Pack Registered Teams will be invited to AI Bootcamp on December 7th and December 8th with Research Collaborator for the Massachusetts Institute of Technology
Register your AI Team Today!!
Compete and Win thousands!!
Why Participate?
Networking & Mentorship
Get Access to the DataEthics4All Community. Connect with AI experts and industry leaders from 71 countries.
Future-Ready Skills
Gain skills for AI-driven jobs with our Bootcamp and AI Competition.
AI Learning Resources
Take advantage of AI learning resources. Choose the Starter Pack or the Pro Pack for more AI learning resources.
Real-World Experience
Hands-on AI projects for both coders and non-coders unlike Hackathons.
Affordable Access
No hardware needed, unlike Robotics. Only $150/ team member for 1 whole year of learning AI, networking with Industry Leaders, opportunity to work on a real world challenge and win a global AI competition.
Publish Research
Opportunity to attend Bootcamp sessions on how to perform AI research and an opportunity to publish research in the STEAM in AI Journal
Earn Badges
Opportunity to earn the Team Captain Badge, Skill based Badges, Ambassador Badge and more
College & Career Boost
Boost your College applications and job prospects with leadership and AI project experience.
Recognition and Publicity for Your School
Educators who mentor or coach AI teams will receive “AI Educator Excellence” Award and will be featured.
The School with the most participating teams will win the “Top AI School of the Year” Award and will be featured.
Win Big
1st Prize: $1000/ Team
2nd Prize: $500/ Team
3rd Prize: $250/ Team
International Teams Please Note: This will be the amount that will be sent by DataEthics4All Foundation. We do not have any say in the currency exchange rates.
Who can Participate?
Students in Grades 6-12 Worldwide
Request to Start Your AI Team Today!
Starter Pack
- Opportunity to Participate in the AI Championship
- Access to Private Group for Teams
- 1 year access to DataEthics4All Community. Meet Data/ AI Leaders and Peers from 71 Countries across the globe valued at $1,200/ year
- Invitation to attend the Bootcamp Megathon
- Invitation to monthly Office Hours by Data/ AI Industry Leaders
- Opportunity to Win
- Certificate of Participation
Pro Pack
- Everything in Starter Pack Plus
- Access to AI Ethics Institute Resources
- Access to on demand AI Ethics Courses
- Enjoy early event access, exclusive content and networking with AI pros
- Opportunity to attend ‘AI Research‘ related Bootcamp Megathon Sessions and learn how to perform research/ write a research paper
- Opportunity to publish research in the STEAM in AI Journal
- Opportunity to stand out in College Applications
What is Multimodal AI?
Multimodal AI integrates various data types like text, images, audio, and video, creating more powerful and versatile AI models. This cutting-edge approach enhances problem-solving, making it a thrilling frontier in AI.
Participants will get hands-on experience, preparing them for the tech innovations of tomorrow!
Frequently Asked Questions
No. STEAM in AI has announced the AI Challenge for this Season. All teams will work on the same challenge.
Every team will find their own unique solution to the AI Challenge problem. In other words, even though the problem is the same for all the teams, how you solve the problem will be unique to your team.
Your AI Solution can be an AI model, a Wireframe, an App, a Research Paper explaining your team’s unique approach to solving the AI Championship Seasonal Challenge.
You will be asked to submit a link to a shared Google Drive in your final submission. That Drive should have a Document with links to all your team’s work depending upon what you’re submitting: GitHub for code, Presentation, Website, App, Video along with details of how you got there – research that your team did, prototype designs, algorithm flow chart, etc. You don’t need to submit these all. Just what is relevant to your unique solution.
No. Not all teams are required to create their AI solution using code. We want to see your approach of solving this AI Challenge with or without code. You can solve it using code, build a wireframe, create a prototype for an app, build a website, submit a research paper.
For detailed judging criteria, sign up as an AI Team.
Yes. Teams qualifying for the finals will receive a Final Qualifying Certificate even if they don’t win in the Finals.
Sneak Peak
Our awesome lineup of AI Bootcamp Megathon Instructors
Pranay Nookala
Research Collaborator, Massachusetts Institute of Technology
Freshman in Computer Science, Purdue University
Pro Pack Teams: Join Us on December 7th and 8th, 2024
Exclusive 4 Hour AI Research Workshop for Pro Pack Participants
AI Workshop Title: Research and AI Model Applications
Description:
In this 4-hour workshop, students will understand how to form a research question and be able to find next steps towards answering and coming up with a conclusion with the help of AI models. Different models will be taught and understood throughout this workshop.
Workshop contents:
- Students will be able to understand the applicability of AI models and their roles in certain research projects. They will also understand the research process and be able to have a brief idea on a research paper.
About the Instructor: Pranay Nookala is a research collaborator at Massachusetts Institute of Technology. His MIT Research Internship focuses on addressing racial bias in temporal (skin) thermometers used in ICUs, which leads to inaccurate temperature data and contributes to medical errors. These inaccuracies affect AI models used in hospitals, leading to faulty predictions. The team is working to identify specific flaws in these detection models and improve their accuracy through optimization techniques.
In the past, Pranay has worked on a project: “EEG Based Analysis of Individuals with Varying Levels of Social Media Usage” where he was able to use an AI model to generate results and with data analysis was able to come up with a conclusion.
Pranay is a Freshman studying Computer Engineering at Purdue University. Over the past few years, he has been able to develop a professional skill set through internships and research. He is excited to continue his journey at college and come across many more challenges. Right now, Pranay is working on a few passion projects to keep himself busy. He is excited to teach everyone interested in research a bit about his way of getting started and crossing the finish line.
Vincent Sha
Associate Dean of IT and Operations,
Carnegie Mellon University
Available On Demand to all Registered Teams
AI Workshop Title: AI Tutors for All: Building Educational LLMs on a Budget
Description:
This 1-hour workshop introduces students in grades 6-12 to Large Language Models (LLMs) and their applications in education. The session covers both open-source and commercial tools for developing LLM-based tutors and educational aids.
Workshop contents:
- Overview of Large Language Models and their educational applications
- Introduction to available tools and resources:
- Open-source options (e.g., GitHub projects, AnythingLLM)
- Commercial platforms (e.g., OpenAI’s GPT, Anthropic Claude)
- Demonstration of a basic LLM-powered educational tool
- Hands-on activity: Customizing a simple chatbot
- Discussion of APIs and their role in LLM-based projects
- Comparison of open-source vs. commercial options
- Resources for further learning and exploration
No prior programming experience is needed. The workshop aims to provide foundational knowledge and practical exposure to LLM-based educational tools.
Student takeaways
- Understanding of LLMs: Students will gain a basic understanding of what Large Language Models are and how they can be applied in educational contexts.
- Awareness of available tools: Participants will learn about both open-source and commercial tools available for developing LLM-based educational applications.
- Demonstration observation: Students will watch a live demonstration of how to work with and customize a simple LLM-based tool.
- API introduction: Students will be introduced to the concept of APIs and their role in integrating LLM capabilities into applications.
- Resource familiarization: Participants will learn about platforms like GitHub and specific projects like AnythingLLM, providing starting points for their own exploration after the workshop.
- Cost considerations: Students will understand the trade-offs between using free/open-source tools and commercial options.
- Ethical awareness: Brief introduction to ethical considerations in AI and LLM use in education.
- Project inspiration: Students will gain ideas for potential projects they could develop for the upcoming STEM competition.
- Further learning pathways: Participants will receive guidance on how to continue learning about LLMs and AI in education beyond the workshop.
- Q&A preparation: Students will be encouraged to note down questions during the session for a potential follow-up or Q&A session.
About the Instructor: Vincent Sha is the Associate Dean of Information Technology and Operation at Carnegie Mellon University’s Dietrich College. With 25 years of IT experience, he specializes in applying technology to solve problems in research and education.
Vincent leads the adoption of generative AI at Dietrich College, developing CMU’s first approved generative AI-based learning interventions. He’s the Technical Lead of CMU’s Open Forum for AI and has received funding from the Omidyar Network for his work in AI tool creation and adoption. He is an expert in fostering collaborative innovation and driving digital culture in applications in applying and creating LLM powered tools.
Himel Dev
Senior Research Scientist,
The Trade Desk
Available On Demand to all Registered Teams
AI Workshop Title: Mastering Programmatic Prompt Engineering for Large Language Models (LLMs)
Description: In this interactive live workshop, participants will explore the art and science of programmatic prompt engineering, a cutting-edge discipline that focuses on crafting and optimizing prompts to harness the full potential of large language models (LLMs).
During this session, we will cover key techniques and strategies, including:
- Forms of Prompt Engineering: Techniques to elicit accurate responses from LLMs, including zero-shot, few-Shot, chain-of-thought prompting.
- Parameterizing Queries: Discover methods to scale prompt engineering by parameterizing queries for consistent and optimized responses.
- Injecting Assumptions and Constraints: Learn how to shape LLM interactions by embedding specific assumptions and constraints into prompts.
- Contextual Awareness in Prompt Engineering: Best practices to ensure LLMs receive the most relevant information for generating optimal responses.
- Generating Structured Outputs: Understand how to elicit and format structured responses from LLMs to meet specific application requirements.
- Processing and Refining Outputs: Explore strategies for post-processing LLM outputs to align them with your application’s needs.
About the Instructor: Himel is currently working as a Senior Research Scientist in the AI Lab at The Trade Desk, where he specializes in developing deep learning based recommendation models for various AdTech use cases, including representation learning for complex metadata and KPI prediction models based on recommendation systems.
Before joining The Trade Desk, he was an Applied Research Scientist at Snapchat, where he developed machine learning models for diverse business applications, focusing on optimizing ranking and recommendation systems, evaluating the long-term impact of features, and extracting valuable insights from large-scale data.
Himel Dev holds a Ph.D. in Computer Science from the University of Illinois at Urbana–Champaign (UIUC).
Roya Kandalan
Gen AI Research Scientist,
The Cigna Group
Available On Demand to all Registered Teams
AI Workshop Title: Gemini API 101
Description: This workshop is designed to give students a fundamental understanding of Gen AI, LLM, and Gemini and to empower them to write code using the Gemini API.
About the Instructor: Roya is a research scientist working on advancing artificial intelligence technologies. She has a PhD in Electrical Engineering, is a US patent holder, and has multiple publications in primary journals on electrical engineering, mathematics, and artificial intelligence. Her primary research interests are generative AI, computer vision, and pattern recognition. Roya has developed machine learning solutions for various applications, including healthcare, assistive technologies, and security.
She is enthusiastic about advancing science and passionate about women’s rights. She is a Google Developer Expert and Cloud Champion in AI/ML, a Google Woman’s Techmaker Ambassador, and a Google Developer Group co-organizer (Cloud Boston). She uses these platforms to enhance women’s confidence in the workplace and advocate for women’s and non-binary individuals’ rights.