Sample Code

Creating a full-fledged blockchain integrated with AI for the creation of the BlueQbit Software for the logistic community,  is a complex task that involves multiple layers of technology. On the left is a simplified example that demonstrates the basic components of how such a system might be built using Python. This example will include:

1. **A simple blockchain implementation.**

2. **A basic AI component that could interact with the blockchain.**

### 1. Basic Blockchain Implementation,

The left Image describe Python code demonstrates a simple blockchain with basic functionality:

 `## 2. Basic AI Integration

Next, let's integrate a simple AI component that interacts with this blockchain. For example, the AI can predict the transaction amount based on some data.

We'll use a basic machine learning model to predict transaction amounts, and the predictions will be stored on the blockchain.

 ```

### Explanation:

1. **Blockchain Class**: This simple blockchain allows for the creation of blocks, transactions, and a proof-of-work algorithm. Transactions are stored in the blockchain, and the blockchain can validate proof of work.

2. **AIModel Class**: This basic AI model uses linear regression to predict transaction amounts based on given input data. In practice, this AI could be much more complex, analyzing various factors to make predictions or optimizations related to cargo shipments.

3. **Integration**: The AI predicts a transaction amount, which is then recorded on the blockchain as a transaction. The blockchain continues to function as expected, validating and adding blocks with these AI-generated transactions.

### Further Development:

In a real-world scenario, this would only be a tiny part of the system. You would need:

- A more advanced AI capable of complex predictions (e.g., using deep learning or reinforcement learning).

- A fully decentralized blockchain network with smart contracts (e.g., using Ethereum or a custom blockchain).

- Secure integration with the ERC20 CargoCoin for payments.

- Front-end interfaces for users to interact with the system.

- Additional features like smart contracts, AI-powered route optimization, and more.

This example serves as a foundation to understand how AI and blockchain could be combined in a basic sense.