*Theme* Fine-tuning vs RAG!
Let's compare the effectiveness of fine-tuning relative to RAG for generative AI apps built on open-source models.
Your goal will be to demonstrate your app is better at a task than the base model was on it's own, using either fine-tuning, RAG, or a combination. Your project will be evaluated on how well it accomplishes the task, and how much better it is than the base model.
Tracks:
1. Fine-tuning with the Together API.
2. Using RAG with Together AI and Langchain.
3. Implement both fine-tuning and RAG together, showing results independently and combined.
Together AI Prize:
$2,500 in Together credits and AirPods for all winning team members.
LangChain Prize:
Access to LangSmith platform, early access to Hosted LangServe, and LangChain swag.
WANDB Prize:
Merch + Airpods Max or Oculus.
Rules: *All attendees must ship code.* Please do not invite other guests. Attendees must be very experienced hackers.
12:00pm Welcome to AGI House
12:05pm Keynotes & Surprise Speakers
12:05pm - 12:30pm Tri Dao (Chief Scientist @ Together.AI - Incoming Assistant Professor @ Princeton) & Albert Gu (Assistant Professor @ CMU) - Mamba: Linear-Time Sequence Modeling with Selective State Spaces
12:30 - 12:40pm Harrison Chase - Founder & CEO @ LangChain - Three levels of RAG: from Q&A to a reflective research assistant
12: 40 - 12:55pm Alex Volkov (AI Evangelist @ Weights & Biases )- Fine-tuning like the pros with WandB
12:55pm Project proposals from hackers
1:10pm Hacking Begins!
1:30pm Lunch is Served
4:00pm Project Check-In
6:00pm Dinner is Served
8:00 - 10pm Demos
* Sponsored by: Together AI, Weights & Biases, LangChain