Co-Pilot Playground
Last updated
Last updated
Welcome to the Co-Pilot Playground, a dynamic environment within the Emvide platform where you can explore and experiment with the AI capabilities designed to enhance your lifecycle assessment (LCA) process. This section will guide you through using the Co-Pilot's powerful search and compose features, enabling you to efficiently find environmental indicators and decompose complex products.
In this video, you will learn how to:
Access the Co-Pilot Playground from the left-hand menu.
Use Co-Pilot Search to find the best environmental indicators for your LCA.
Utilize Co-Pilot Compose to decompose complex products into component parts.
Accessing the Co-Pilot Playground:
Navigate to the Co-Pilot Playground from the left-hand menu within the Emvide platform.
The Playground is your starting point for exploring the AI’s capabilities in a risk-free environment.
Co-Pilot Search:
Purpose: Co-Pilot Search uses semantic search to identify the best environmental indicators for your LCA.
Example: Start by searching for a basic material, such as aluminium. Enter the name "aluminium" and a description like "aluminium ingot."
Results: Co-Pilot Search will return the top matches, such as "aluminium production primary ingot" from Canada, indicating the best option based on your search terms.
Benefit: This feature saves time by quickly identifying the most relevant environmental indicators.
Co-Pilot Compose:
Purpose: Co-Pilot Compose adds an extra layer of decomposition and analysis, breaking down complex products into their component parts.
Example: Using the mountain bike example, search for a "wheel." Enter a description like "typical wheel for a bicycle."
Initial Search Result: You may get a less relevant result, such as "Transport Passenger Bicycle," indicating environmental impact for transportation, not the wheel itself.
Refining the Search: Specify units of measurement (e.g., one wheel) and use Co-Pilot Compose to decompose the wheel into components like metal, rubber, lubricating oil, etc.
Decomposition: The system will break down the wheel into materials such as aluminium alloy (0.8 kg), rubber, steel, and estimate associated CO2 factors and energy use during production.
Adjustment: The accuracy of decomposition depends on the detail in your descriptions. More detailed inputs yield better results.
Reviewing and Adjusting Results:
Example: After Co-Pilot Compose completes its analysis, review the decomposed list of products.
Materials Breakdown: Check the components identified by the AI, such as aluminium alloy, rubber, and steel, and their estimated weights and CO2 factors.
Process Estimation: Review the AI’s estimation of production processes, like electricity usage during manufacturing.
The Co-Pilot Playground allows you to:
Perform rapid searches for environmental indicators.
Decompose complex products into detailed components.
Save time and improve accuracy in your LCA process.
By using the Co-Pilot Search and Compose features, you can enhance your understanding and efficiency in conducting LCAs. Remember, the more detailed your input descriptions, the more accurate the AI’s output will be.
Explore the specific functionalities of Co-Pilot within different nodes and reporting by following the links below:
This page provides a comprehensive guide to using the Co-Pilot Playground, helping you understand and utilise the AI capabilities within the Emvide platform.