Event ended

Falcon LLMs Hackathon sponsored by GAIA Summary

Falcon LLMs Hackathon sponsored by GAIA image

Hackathon Overview

Our AI hackathon brought together a diverse group of participants, who collaborated to develop a variety of impressive projects based on:

1205

Participants

46

Teams

7

AI Applications

Speakers, Mentors, and Organizers

Shebagi Mitra profile picture
mentor

Shebagi Mitra

Student

    Haneen Salih profile picture
    organizer

    Haneen Salih

    Community Manager

      Donald Nwokoro profile picture
      mentor

      Donald Nwokoro

      Backend Developer

      Dina Shall profile picture
      organizer

      Dina Shall

      Global Community Manager

        Theodoros Ampas profile picture
        mentor

        Theodoros Ampas

        Technical Mentor

        Muhammad  Inaam profile picture
        mentor

        Muhammad Inaam

          Ndim Donald profile picture
          mentor

          Ndim Donald

          NoCode Entrepreneur

          Olesia Zinchenko profile picture
          organizer

          Olesia Zinchenko

          Product Marketing Manager

          Iga Romowska profile picture
          organizer

          Iga Romowska

            null null profile picture
            organizer

            alsu5

              Daniel Duccik profile picture
              organizer

              Daniel Duccik

              Marketing&Visual

              This event has now ended, but you can still register for upcoming events on lablab.ai. We look forward to seeing you at the next one!

              Checkout Upcoming Events →

              Submitted Concepts, Prototypes and Pitches

              Submissions from the teams participating in the Falcon LLMs Hackathon sponsored by GAIA event and making it to the end 👊

              Help to spread the word and share these amazing projects!

              Streamlit
              application badge

              ECOMMERCE Assistant

              A courteous and versatile multimodal chatbot, equipped with sentiment analysis capabilities, excels in responding to user inquiries, providing valuable information, and facilitating a smooth and enjoyable shopping experience.

              FutureTech Mavericks

              FalconLangChain

              Falcon Document Parser

              The document parsing application leverages Falcon LLM to accurately extract data from invoices, aiming to boost efficiency, save valuable time, and minimize manual errors, providing a streamlined and reliable solution for various business needs.

              FalconBytes

              Falcon
              medal

              DOR summarizing tool

              AI tool that can read and summarize recurring Daily operation reports (DOR) used by natural resource extraction companies.

              Green lamp

              FalconLangChain
              medal

              Gaia Mini Med

              "Introducing Gaia Mini Med, an innovative fine-tuned model derived from cutting-edge data sources. Gaia's superior performance stems from its advanced training methodology, surpassing other falcon fine-tunes in accuracy and effectiveness."

              Team Tonic

              Falcon

              AiLingo-your personalized language speaking coach

              We specialize in the application of LLM within educational delivery, especially in the context of one-on-one, real-time, and personalized language learning platforms. Individuals can send voice messages to an AI respondent in various scenarios.

              Ailingo

              GPT-3.5OpenAI
              medal

              Falcon Barsita

              Falcon Barista is a proof of concept (POC) of an order-taking bot with speech capabilities. It can converse with customers and take their orders in a coffee shop or any restaurant, potentially saving labor costs for the restaurant industry.

              Deep Dream

              FalconBERT
              medal
              Streamlit
              application badge

              LLM-based hierarchical data extraction

              LLM allow to extract features from their own parameters in a hierarchical way. This in turn allows to improve ML algorithms such as object recognition, but also reduce LLM's size and training time in the future with new architectures.

              NoLimits

              FalconLangChain