TruEra Challenge: Build LLM Applications

Let's Kick it Off! We are starting the stream with a Hackathon opening, an introduction to lablab.ai from the NewNative co-founder, and a schedule overview.

Hackathon Kick-Off Stream

Join Anupam Datta, Co-founder, President, and Chief Scientist at TruEra, as he kicks off the Hackathon with insightful opening words, setting the tone for an engaging exploration into TruEra Challenge: Build LLM Applications with Google Vertex AI.

TruEra Opening Words

Let's dive into the platform and its features that will be useful for Hackathon participants.

Hackathon Guide and Platform Walk-through

Join the workshop with Michael Davis, Customer Engineer at Google and Anupam Datta, co-founder, President, and Chief Scientist at TruEra.

Google Cloud x TruEra Workshop: Running LLM-based Evals with PaLM 2

Join us for an insightful workshop featuring Josh Reini, DevRel Engineer at TruEra, and Yujian Tang, Developer Advocate at Zilliz.

Build and Iterate with Advanced Index Construction: Chunking, Range Search and more

General Q&A session on Discord

In this workshop on December 4, Shayak Sen, CTO of Truera, and Laurie Voss, VP of Developer Relations at LlamaIndex, will explore the building and evaluation of multimodal GenAI apps using the RAG Triad model. 

Building and Evaluating Multimodal GenAI Apps: RAG Triad is All you Need

Submissions Deadline

Extended Submission Deadline💻

TOP-5 teams will be invited to pitch their ideas for Hackathon judges - to define the Hackathon winner!

Finalists Stream

DeJaNi is a compound combining elements Desik, Jayanth, Nivaas.

DeJaNi

Mandava Desik

Santosh Jayanth Amara

Idea:
We plan to the better use the outputs generated by current LLMs by letting the users' to make the chat with LLM public. This chat once public will become visible to all users' within the platform who can then like, share, comment on the chats. Based on the Data liked by each user, we can personalize their own chats by leveraging the user traits or interests. Given the chats are now backed by human vote, their is an increased chance for less hallucination. We also plan to enable SEO for the chats so that if any user generated a good output for a question, the same output can be later used for other folks. 

Impact:
We think that the Idea which we're proposing here can be helpful to any LLM creator and can help them create a business model. As of today, AI Startups need a lot of funding to build LLMs' and we think out Idea can help them generate model in some form. Additionally companies like HuggingFace who work on open source can also leverage this Idea to generate a revenue which they can spend into their open source initiatives. We also think that HuggingFace can create an open source social media so that users' can also understand what Data is being collected and on what basis is the recommendation being done. 

Prototype done as part of Hackathon:
We've build a website which displays the outputs generated by the LLM. We also added features such as Like, Comment. Given personalization is an ongoing active research problem, for now to show how personalization can be done, we've Engineered a custom prompt where the user's traits will considered and based on this, the user's output is personalized. 

For better understanding, we've mentioned everything within our Demo

Leveraging existing outputs generated by LLMs to:
1. Let users make their chats with LLM public within the LLM creator's platform
2. Let other users add comments, likes on the public chats
3. Leverage Data from the user traits to enable personalization

"DeJaNi team on TruEra Challenge: Build LLM Applications Hackathon"

Team Idea

Submission