Event ended

Open Source AI Hackathon Summary

Open Source AI Hackathon image

Hackathon Overview

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

515

Participants

53

Teams

4

AI Applications

Speakers, Mentors, and Organizers

Olesia Zinchenko profile picture
organizer

Olesia Zinchenko

Event Manager & Mentor at lablab.ai

Mathias Asberg profile picture
organizer

Mathias Asberg

founder

    Anastasiia Strakhova profile picture
    organizer

    Anastasiia Strakhova

    Event Specialist at NewNative

      Simon Olson profile picture
      organizer

      Simon Olson

      Founder

      Pawel Czech profile picture
      organizer

      Pawel Czech

      Co-founder/Partner

        Fabian Stehle profile picture
        organizer

        Fabian Stehle

        Dev at NN

        Liza Marchuk profile picture
        organizer

        Liza Marchuk

          Hai Nghiem profile picture
          speaker

          Hai Nghiem

          Full Stack Developer

            Prizes

            Hackathon Winner

            • SWAG from lablab.ai

            Finalists

            • SWAG from lablab.ai

            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 β†’

            Submitted Concepts, Prototypes and Pitches

            Submissions from the teams participating in the Open Source AI Hackathon event and making it to the end πŸ‘Š

            Help to spread the word and share these amazing projects!

            medal

            Copilot-J

            CoPilot-J is an open-source GitHub Copilot-X an alternative for VSCode. It can chat with code, generates, explains, and refactors code using LocalAI, and is compatible with any open-source model (ggml compatible). for the implementation We have 2 main components, the first one is VS code plugin that does all the interaction, it is able to chat with models, send code to the conversation, or detect code snippets from the conversation. the second part is go-skynet/LocalAI which does all the magic of serving AI models, in this demo, we’re using wizard-lm inference to demo the plugin, but you can use any ggml model to use it. the repo is up here: https://github.com/badgooooor/localai-vscode-plugin.git PS. Initially we thought we'd use GPT4ALL-J hence the name Copilot-J πŸ˜‚

            Copilot-J

            Streamlit
            application badge

            Pitch Analyzer

            Pitch Analyzer allows you to receive a complete pitch from a startup in text format, analyzes the content, and then simulates a conversation between a potential investor and the founder of the startup, answering all questions based on the delivered pitch, or inferring an answer if You can't find the appropriate information. All this is with the intention of preparing the founders for specific questions that they may receive at this type of event if they wish to attract and receive funds for their projects. Currently, training to make good pitches for founders is complicated by time, sometimes at a cost that startups in earlier stages cannot, and sometimes not adapted to the types of startups that participate, therefore, Pitch Analyzer is the ideal solution for it.

            Pitch Analyzer

            CAMELOpenAILangChain

            RageGPT

            Have you ever been wronged by someone, and you wanted to yell and scream at them, but you held back? You know it's not fair, but you don't want to risk the consequences. Enter RageGPT! It's an AI that lets you yell and scream at an AI of your adversary, without any consequences. You can type in all caps, swear, and say anything you want. No one will know! Or use it to practice negotiations for a pay raise or promotion. Or practice debating your boss / teacher / parent. Anything! Want to confront a former lover but not sure what to say? Try it out at RageGPT and see what happens? Great no-consequence practice for important life-changing events.

            Mr Barnard Room 12

            ChatGPT

            DocSearch AI

            Users often struggle to find the most relevant and useful documents related to their needs due to Inefficient keyword-based search and Lack of query context. Our solution to this problem is building a tool call Doc Search AI. It is an AI Document Searching tool that addresses the shortcomings of traditional search methods and offers users a more effective and efficient way to find relevant documents by leveraging advanced AI techniques. Doc Search AI will takes users query as input, then using large language model (we use GPT2 open source model) to expand the users' document queries in more details, and use other AI techniques like keywords extraction and vectorize the search query to improve the quality of search so that the results return to users will be more relevant to what users want.

            kopi c peng

            GPT-3