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The Fifth Elephant Open Source AI Hackathon 2024

GenAI makers and creators contest and showcase

Make a submission

Accepting submissions till 15 Feb 2024, 11:00 PM

Hasura, Bangalore




The Fifth Elephant Open Source AI Hackathon started on 5 January 2024 and reached its finale with a Demo Day event on 12 April 2024, when the winners of the two month long contest were chosen.

The aim of this hackathon was to encourage individuals/teams to apply and incubate innovative AI ideas/use cases and publish them as open source projects.

  • The hackathon contest participants worked with mentors for over two months to refine their ideas, and advance them to a stage where they are viable projects that could be pursued beyond the hackathon.
  • the project teams worked on AI’s application in education, accessibility, creative expression, scientific research, languages, under the overall theme of AI for India.
  • competing projects were judged on impact and relevance, innovation and creativity, technical soundness and code quality, scope of expansion, reusability and ease of adoption.

📋 Read Hack5 V1 Report

As a campaign to raise awareness and drive up developer adoption of AI and open source technologies, the hackathon was a great success. It helped shine light on the agility that open source technology enables for creative and innovative developers.

Open Source AI Hackathon Winners


“...each one of the contestants put in tremendous effort. And we saw the passion in every person, trying to do things not for winning, but about really building your projects. After a long time, I am attending such a hackathon where young folks are so passionate about building. Kudos to all of you”.
- Rukma Talwadker, Jury Member, Senior Principal Scientist at Games 24x7

“I really enjoyed judging all the projects - lot of interesting work. The Fifth Elephant has done a great job with mentoring and curating this hackathon”.
- Tanuja Ganu, Jury Member, Principal RSDE Manager, Microsoft India

“The hallmark of this hackathon was getting younger people to code for a longer period of time as opposed to a typical hackathon which turns out to be about — how do you build the coolest thing in the shortest period of time”.
- Sumod Mohan, mentor.

“What is impressive about this particular hackathon is, it is not just about cool ideas and fancy demos. It is actually about building a product or a software or a model that can live beyond the demo (and contest).”
- Soma Dhavala, team member at Project Seshu

“It was only through putting my ideas to code that I learnt what the specificity of implementing these (LLMs) were. I began my journey with a sense of hope and commitment towards FOSS principles, and the Hackathon only reinforced my belief that collaboration maketh a better product.”
- Sankalp Srivastava, Creator of Project Schematise

Key highlights from the hackathon

During the course of 12 weeks, the hackathon involved:

  1. Started off on 5 January 2024 and invited open source ideas and projects.
  2. Mentorship sessions in February for all project teams. Mentors included Abhishek H Mishra aka Tokenbender, Arvind Saraf, Bharat Shetty, Ramesh Hariharan, Sidharth Ramachandran, Simrat Hanspal, Sumod Mohan and Vinayak Hegde.
  3. The 10 best from 40 applications were chosen for the Demo Showcase.
  4. An involved peer-review process helped further refine projects between March 1st - 15th, followed by extensive rehearsals from April 8th - 10th, 2024.
  5. On Demo Showcase Day - we had project demos from 10 qualifying teams; 5 project winners were chosen on 12 April 2024.

The Prizes

🏆 Five prizes of ₹1,00,000 (One lakh rupees) per theme, were awarded to winning projects.
The prizes for this hackathon have been sponsored by Meta.

Note: Apart from the contest prizes, Microsoft has offered internships to the contestants.


  1. Ashok Hariharan heads data and business intelligence at United Nations Volunteers.
  2. Rukma Talwadker is Senior principal scientist at Games24x7.
  3. Shubha Shedthikere is a Senior Manager in the Data Science team at Swiggy.
  4. Sunil Abraham is the Public Policy Director for Data Economy and Emerging Tech at Meta, India.
  5. Tanuja Ganu is a Principal RSDE Manager at Microsoft Research India.


  1. Abhishek Mishra is a is creator of CodeCherryPop LLM series.
  2. Arvind Saraf is a computer scientist, engineering leader, entrepreneur trained at IIT, MIT and Google.
  3. Simrat Hanspal is currently spearheading AI product strategy at Hasura.
  4. Sumod Mohan is the co-founder and CEO of AutoInfer.


About The Fifth Elephant

The Fifth Elephant is a community of practitioners, who share feedback on data, AI and ML practices in the industry. If you like the work that The Fifth Elephant does and want to support its activities - review of Papers, Books, building the innovation ecosystem in India through hackathons and conferences - contribute by picking up a membership.


💬 Post a comment with your questions here, or join The Fifth Elephant Telegram group and the WhatsApp group.

Follow @fifthel on Twitter.

📞 For any inquiries, call The Fifth Elephant at +91-7676332020.

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Hosted by

The Fifth Elephant hackathons

Supported by


All about data science and machine learning

Venue host

Welcome to the events page for events hosted at The Terrace @ Hasura. more


Providing all founders, at any stage, with free resources to build a successful startup.

Akshat Gupta



Submitted Jan 24, 2024

Problem Statement

As GenAI is on its path to revolutionise the way most things are done, we propose an innovative application of it. For the last many years, we have witnessed AI assistants that mostly assist with specific day to day activities like writing, setting up an alarm, etc, and mode of communication if typically either via chat or voice commands.
We have designed a Music Assistant called Musickiya that will help music producers and composers across the world to do rapid sampling and mixing. We are proposing a Digital Audio Workstation (DAW) integrated assistant that will take inputs from the user and will provide beats, samples, chord progression etc. right inside the arrangement view which they can blend as per their creativity.


Producing and mixing a song in a DAW can take quite some time ranging from a few hours to as long as a few weeks. It’s an art that takes about 4-5 years to master and still would require a lot of thinking and experimentation to get the right sounding one.
Some common activities that are performed in a DAW are:

  1. Digital audio processor (record, edit, and mix audio digitally)
  2. MIDI sequencer (record, edit and mix MIDI notes)
  3. Virtual instruments (receives MIDI info and translates it to different instrument sounds)
  4. Music notation (turn MIDI notes into printable sheet music)
    Sampling a beat from a piece of sound.

Specifically, activities like figuring out the right virtual instrument, preset etc. that matches the feeling that the producer has for the song can be time taking and manual process. Also, buying costly sound engineered sample packs can be a turn off for budding producers.

An AI assistant can help with these bottlenecks and speed up the production time by at least 10x. Also, the integration of this assistant will be pretty simple with their traditional workflow as it will only just help with the mundane and repetitive manual processes.

Specifically, the functionalities of the assistant are:

  1. Audio to Audio Generation: Convert one piece of music like a chord progression in guitar to another instrument like piano conditioned by a prompt.
  2. Chords (Text/MIDI) to Audio Generation: Convert chords in text or MIDI format like a chord progression in guitar to another instrument like piano conditioned by a prompt.
  3. Prompt to Audio Generation: Get samples of music directly using a prompt.
  4. Lyrics Generation: Get lyrics using a prompt.
  5. Lyrics to Vocal Generation: AI sings the given lyrics and small clip of singing to replicate voice
  6. Noise Reduction: Suppress noise in the given noisy audio.

If we talk about scalability, this AI assistant will have AI models backing it which can run in the cloud or even on premise too as DAW’s GUI and some plugins are already GPU-accelerated. The assistant will stream the audio generated directly in the GUI for the user to review quickly. The proposed solution is scalable across devices along with multiple suggestions for a given use case. As per the initial experiments, it takes ~30 sec to generate 30 seconds of music. This amount can be reduced further after some optimisations.


We will develop our own plugin for one of the DAWs out there and integration our python programme with it.
The models leveraged to build the solutions are:

  1. OpenAI Jukebox: Generative Model for Music
  2. MusicGen: Meta’s Generative Model for Music
  3. MusicGen Chord: Modified version of MusicGen Melody model

Future Scope/ Roadmap

Adding multimodal inputs, so that the music generated is the closest from what is expected from the user, be it the input in terms of music, text, image and video. Initial approach will be to create this as a standalone tool, and then integrate in the DAWs

Github Roadmap - https://github.com/akshatagkgp/fifth-el-hackathon

Participants - Akshat Gupta, Shyam Choudhary


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Make a submission

Accepting submissions till 15 Feb 2024, 11:00 PM

Hasura, Bangalore

Hosted by

The Fifth Elephant hackathons

Supported by


All about data science and machine learning

Venue host

Welcome to the events page for events hosted at The Terrace @ Hasura. more


Providing all founders, at any stage, with free resources to build a successful startup.