Task management system with AI PMO

Using Web3 and SHYFT, the currency is managed within the project and participants can use wallets and NFTs to build their own currency system.

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Inspiration

The inspiration for this project was to create a task management system that utilizes artificial intelligence to efficiently manage projects.

What it does

The Task Management System with AI PMO is a project management tool that uses machine learning algorithms to analyze data and make predictions about project outcomes. It helps project managers to prioritize tasks, improve resource allocation, and increase productivity.

How I built it

The system was built using Python and various machine learning libraries such as scikit-learn and TensorFlow. The frontend was developed using React, while the backend was built using Node.js and Express.

Challenges I ran into

One of the major challenges was training the machine learning models with sufficient data. We also faced some difficulties in integrating the frontend with the backend.

Accomplishments that I'm proud of

We are proud of building a functional project management tool that can significantly improve the efficiency of project management. We were able to successfully integrate machine learning algorithms into the system, which can make accurate predictions about project outcomes.

What I learned

We learned a lot about machine learning algorithms and their applications in project management. We also gained valuable experience in frontend and backend development.

What's next for Task management system with AI PMO

In the future, we plan to improve the accuracy of the machine learning models by incorporating more data sources. We also plan to add more features to the system, such as automated reporting and risk management.

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Updates

posted an update —

First, here is an idea of what data should be stored in web3 and what should be stored in web2DB, such as pinecone.

Data to be stored on Web3: Data that must be public and tamper-proof. For example, currency transaction history within a project, ownership and status of tasks, rewards for task completion, etc.

Data to be stored in Pinecone: Data used by the AI PMO for analysis and recommendations. This could include task details, progress, time required to accomplish, team member performance data, etc. Such data can be used with Pinecone's vector search feature to efficiently retrieve relevant information. In this way, by separating data to be stored in Web3 and Pinecone according to the type of data and its use, the effectiveness of the data can be maximized.

MVP (Minimum Viable Product) for Idea 1*.

  1. Basic Task Management Functions: Create a system with basic project management functions such as creating tasks, assigning tasks, and managing progress.

  2. AI PMO: Create a basic chatbot using GPT to periodically check the status of tasks and implement the ability to report it via Twitter, etc. Also, when a new task is registered, we will create a function to check the detailed data and determine the point of the task (each of these functions is expected to be the main point of this demo). 3.

3.Currency system in the project: Create a currency system in the project using SHYFT based on the points attached to the GPT above, and implement a function to pay in digital currency for the accomplishment of tasks.　

Main Tasks for Idea 1.

  1. Determining the value of the in-project currency: The issue is how to determine the value of the in-project currency. This could vary depending on the success of the project, the difficulty of the task, the importance of the task, etc. We plan to utilize ChatGPT here, so the quality of data input into ChatGPT is important.

  2. AI Accuracy: An AI PMO created using GPT must be able to determine task progress with sufficient accuracy and report appropriate information. This could require significant time and resources to train and refine the chatbot.

  3. managing bias: AI will reflect biases in the training data. For example, certain task types or specific projects may be over-prioritized. It is important to manage bias appropriately to ensure fair weighting.

In summary, the task management and reward system itself already exists in other DAOs, so the differentiation point for this project is how to incorporate ChatGPT below.

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