Tune AI at HakMIT

đź“… Event Date: September 14th - 15th, 2024

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🌟 Welcome, Innovators and AI Enthusiasts!

Are you ready to redefine the boundaries of AI? Join Tune AI at HackMIT and be part of the challenge that could revolutionize the way we interact with Large Language Models (LLMs).

We’re inviting you to craft groundbreaking, real-world solutions using the cutting-edge capabilities of Tune Studio. Get your creative juices flowing, and show us how you can transform LLM-powered applications!

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đź’° Prizes

  • 🏆 Best Hack on Studio: $2000 cash + $500 API credits
  • đź’ˇ Best Startup Idea on Studio: $1000 cash + $500 API credits
  • đź‘• Free T-shirts and Swags for everyone!

But it’s not just about the prize—it’s about leaving your mark on the AI landscape!

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🎤 Keynote Presentation

Don’t miss our exciting keynote! Get inspired and learn more about the cutting-edge developments in AI and Tune Studio.

Keynote Slides: bit.ly/tune-hackmit-keynote

Make sure to check out the slides for valuable insights, resources and information that could help you in the hackathon!

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The Challenge: Build the Next-Gen LLM Application

Your mission, should you choose to accept it, is to develop a next-gen application powered by LLMs that addresses real-world challenges in creative, impactful, and practical ways. All participants must utilize Tune Studio—whether it’s using our assistants or leveraging fine-tuning capabilities—to build your app.

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How to Participate

  1. Utilize Tune Studio for assistant development or model fine-tuning in your app.
  2. Build something that showcases innovation, practicality, and user impact.
  3. Submit your project via the provided hackathon platform by the deadline.

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🏆 Key Judging Criteria

  • Innovation (30%): Is your idea fresh, unique, and innovative?
  • Technical Implementation (25%): How well does your solution utilize Tune Studio and LLMs?
  • Impact (15%): How does your application solve a real-world problem?
  • User Experience (30%): Is the solution intuitive and enjoyable to use?
  • Bonus: Successfully fine-tune an LLM for an assistant and go above and beyond!

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🛠️ Main Challenges

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🌪️ Challenge 1: RAGnarok

Mission: Brace yourselves for RAGnarok, where knowledge meets chaos in an epic battle of information retrieval! Your task is to create a wiki-style knowledge base that can withstand the onslaught of queries and emerge victorious.

Create a wiki-style article on any topic of your choice. Your assistant will maintain a library of links, reference raw data, and respond to queries by retrieving relevant information. Think of it as a dynamic, evolving knowledge base built using Tune Studio’s fine-tuning and assistant capabilities. Forge a robust Retrieval-Augmented Generation (RAG) system that can dynamically access, process, and deliver information on any topic. Your AI assistant will be the valiant warrior, wielding the power of RAG to vanquish ignorance and triumph over complex queries.

Scoring Highlights:

  • Battle-Ready Retrieval: Accuracy and speed in fetching relevant information from your knowledge base.
  • Contextual Warfare: Ability to understand and respond to queries with pinpoint precision.
  • Adaptive Arsenal: Seamlessly updating and expanding the knowledge base through conversation.

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🧠 Challenge 2: BrainBlend

Mission: Welcome to BrainBlend, where cognitive diversity meets AI unity! Your challenge is to create a harmonious ensemble of fine-tuned Large Language Models (LLMs) that work together like a well-oiled neural network.

Take a synthetic dataset, fine-tune multiple LLMs using Tune Studio, and build an ensemble model. Using Tune Studio, you’ll take a synthetic dataset and fine-tune multiple LLMs, each specializing in different cognitive tasks. Your goal is to blend these AI minds into a singular, powerful intellect capable of tackling a wide array of challenges with unparalleled versatility.

Scoring Highlights:

  • Cognitive Synergy: Seamless collaboration between specialized models for optimal task execution.
  • Intellectual Versatility: Demonstrating proficiency across diverse problem domains.
  • Neural Efficiency: Smart resource allocation and management across the ensemble.

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🎯 Challenge 3: PrecisionTuner

Mission: Enter the world of PrecisionTuner, where less is more and accuracy is everything! Your mission is to develop a system that fine-tunes LLMs with surgical precision, using only the most impactful data.

Develop a system that intelligently selects the most relevant data to maximize LLM performance. Reduce the data volume without sacrificing quality by training your model using only the most impactful data subsets. Instead of force-feeding your model with volumes of information, you’ll create a data diet plan that maximizes performance while minimizing input. Your challenge is to prove that in the world of AI, it’s not about how much you know, but how well you use what you know.

Scoring Highlights:

  • Data Marksmanship: Pinpoint accuracy in selecting the most relevant and impactful training data.
  • Performance Amplification: Achieving significant model improvements with minimal data input.
  • Adaptive Precision: Demonstrating effectiveness across various data types and model architectures.

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🧰 Workshop: Mastering LLM Development with Tune Studio

In this 45-minute workshop, we’ll dive into building, fine-tuning, and deploying cutting-edge LLM applications. This is your chance to gain insider tips, learn best practices, and get ready to take on the Tune AI challenge!

Agenda:

  1. Introduction to Tune Studio and its features
  2. Setting up your environment
  3. Building a basic LLM app
  4. Creating your own Assistant in Tune Studio
  5. Fine-tuning models for real-world use cases
  6. Deployment and scaling best practices
  7. Q&A

What You’ll Learn:

  • How to navigate Tune Studio and its advanced features
  • Practical techniques for effective LLM fine-tuning
  • Strategies to optimize and scale your applications

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đź“š Resources:

We want you to succeed, so we’ve put together the following resources to help you get started:

  1. Tune Studio Documentation: Everything you need to know about using our platform.
  2. Sample Projects: Explore example LLM projects built using Tune Studio.
  3. LLM Fine-Tuning Guide: A step-by-step tutorial for fine-tuning models.
  4. Hackathon Support on Discord: Join our community for real-time support and collaboration.

Whether you’re a seasoned developer or a first-timer, Tune AI is here to help you every step of the way. Let’s create something that pushes the boundaries of what’s possible with LLMs!

Checkout HackMIT Event page.

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