by 0x46c02de46629a2babe7c9ba1d9ebf0804d4f99aa (adi)
Should the following Tier 4: up to $60,000 USD, 6 months vesting (1 month cliff) grant in the Platform Contributor category be approved?
Abstract
DCLBuilderAI is a tool to generate scenes and other assets using natural language prompts (ex: create a scene with a park and a bench). Within seconds, it will generate the scene using the prompt as docstring, and a multi-layout view will display both the code for the scene and the preview. Users will be able to edit the code and preview it on the fly. For convenience, we’ll also add the option to connect your wallet and publish the scene to your land. We’ll be using Codex(an immensely powerful GPT-3 programming model) and Tensorflow for the project. We’ll later add support for using DALL-E in the scenes too.
Watch this video preview of one use case that we got working by feeding in some examples from the SDK: DCLBuilderAI - YouTube
Grant size
56,000 USD
Beneficiary address
0x46c02dE46629a2bAbe7c9ba1D9EBF0804d4f99AA
Email address
Description
Codex is the model behind GitHub copilot and a GPT-3 derivative which is itself trained on more than 170B parameters, making it ideal for code-generation. This is already starting to gain popularity in the industry (emerging projects: Deep Learning Trends: top 20 best uses of GPT-3 by OpenAI)
Decentraland can benefit a lot from leveraging these OpenAI tools. Builders will be able to save thousands of hours spent on manually creating scenes, assets, avatars, etc.
Here are some basic use cases we’re planning to integrate with our tool:
Generating Custom Entities, Components, Actions
- Run primary queries like “create a scene with a lot of trees” and secondary queries like “add a moving bird everytime a tree is clicked”
- Actionable scenes like “create a drunk zombie”, “add unicorns next to the zombie”, “a jumping shark”, “a jumping shark with a drunk zombie”, etc.
- Event based assets like “party rooms”, “sports avenue”, “cube jumper”, etc.
For the scenes, there will be a split pane, with an editor, and a previewer - code generated through the prompt will be visible on the editor, and the user will be able to see its preview on the previewer, manipulate it, provide feedback, and even publish it to their land by connecting their wallet on DCLBuilderAI. We’ll be using SDK7 for enhanced performance/usability for our project.
We’ll create a separate pipeline to ingest all the available training data from decentraland scenes repo, SDK, and other public sources, and feed it into the codex da vinci model, fine-tuning for it to work with DCL (and generate valid output) will happen through OpenAI as well. On top of this, by giving the users the option to provide feedback on the accuracy of the results, we’ll be able to optimize feedback loops, decrease statistical errors like type-IIs, and just deliver better content. The model, training, fine-tuning, and api will be part of codex and will come from OpenAI whereas Tensorflow will be used for the data ingestion pipeline process.
Note that this tool will not be assisting with minting and listing assets on the DCL marketplace but will be providing an editor and preview option for working with assets. Besides, the results are not guaranteed to be 100% accurate and will hopefully improve over time with the help of the feedback loop.
Specification
The project will require working with a number of key services such as OpenAI, Tensorflow, MetaMask, DCL SDK7, and other web development frameworks/tools. The tool will be used through a web app developed using React for frontend and Node for backend. Setting up and maintaining the infra will cost ~$12K a year.
Using OpenAI for training/usage would be expensive as well - we plan on using the da vinci language model – one of the most powerful ai models – to deliver state of the art results for our customers.
OpenAI cost for running queries: $0.0200 / 1K tokens (which is roughly ~750 words)
In order to make the tool more accessible to the community, we’ll use up to $8k in funding to fund its usage so that users in the DCL community can play around with it for free. Once we’ve exhausted this funding, we will directly charge the end users to foot in the costs for their use cases.
The rest of the funds will be used as dev salary for our team - we all have skillsets in NLP prompt engineering/model training/data pipelines but would like to bring on board one data scientist/engineer too to help speed up the project development.
The project will be open-source and we’ll also try to partner with existing projects to help with components like publishing to the lands or making the previewer generate the scene as changes are made to the editor on the fly. We will later also work toward adding support for using DALL-E with GPT-3 to generate 3D models from text.
Breakdown of Costs:
Work | Cost |
---|---|
OpenAI Project Community Access to DCL | $8K |
Web Tooling, Infra for frontend and backend, maintenance of project | $12k |
Total Salary | $32k |
Misc. Expenses | $4k |
Personnel
Aditya - Software Engineer
Tave - Software Engineer
We’re both full-stack software engineers with prior experiences at companies like Amazon/Microsoft with exposure to large-scale AI/ML-based projects, and are also the team behind a peer-to-peer rental marketplace project called RentParcel delivered through a successful grant (Democratize Access to Decentraland for Renting, Marketing, and Hosting Events). We’ve been involved with several DCL landowners in the last 1 year, generating value for them by securing land rentals.
Roadmap and milestones
We plan to complete the project within six months, here are the goals we’re setting:
- Months 1-2: Work on developing the data ingestion pipeline, model training, prompt engineering, fine-tuning, creating backend for accessing OpenAI APIs for Codex.
- Month 3: Work on the UI for the web app that will use the tool, create scenes, other assets, previewer, and publish option to the lands.
- Month 4: Work on integrating the backend with the frontend.
- Months 5-6: Work on adding option to connect wallet, publish to land, and beta-testing the project, and granting access to the community.