File:Workflow of a machine-learning-based AI system.png
Summary
| Description |
English: This diagram summarizes a typical machine-learning workflow. Data and objectives are used during training to produce a trained model; during deployment (inference), new inputs are processed by the model to produce outputs (e.g., predictions, text, images). |
| Prompt | "Base generation (Nano Banana 2, text-to-image):
Create a clean, neutral, encyclopedia-style infographic (white background, flat vector look, thin lines). Show a left-to-right workflow of a machine-learning–based AI system with five labeled panels: Inputs, Training (development), Trained model, Inference (deployment), Outputs. Use very short labels only (no paragraphs). Avoid marketing-style headlines. Avoid robots or humanoid imagery. Use simple abstract icons (data, database, gears, network nodes, chip). Remove any star rating symbols. Make text large enough to remain readable when scaled down for a Wikipedia thumbnail. Export as PNG (or SVG-like vector style). Key intermediate edit (image-to-image): Remove the top three icons in the INFERENCE (DEPLOYMENT) panel. Final finishing edit (image-to-image; applied to the provided image only): EDIT THE PROVIDED IMAGE ONLY. Keep the layout, panels, icons, typography, colors, borders, and spacing unchanged. Modify only the bottom “new inputs” dashed arrow: Make the dashed line thinner (about 60% of the current thickness). Make dash segments slightly shorter and gaps slightly smaller, with uniform dash spacing and crisp edges (no sketch effect). Keep the arrow subtle: slightly lighter than the main solid arrows. Keep the “new inputs” label as-is (same text, same placement). Keep the arrowhead solid and clean; if possible match the main arrows’ style with a neat outline. Export as a high-quality PNG." |
| Date | |
| Source | Own work |
| Author | Generated and edited with Genspark (Nano Banana 2); prompt drafted with assistance from ChatGPT 5.2 |
Generated and edited using Genspark (Nano Banana 2).
Licensing
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- to remix – to adapt the work
- Under the following conditions:
- attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
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This file is in the public domain because it is the work of a computer algorithm or artificial intelligence and does not contain sufficient human authorship to support a copyright claim.
 The United Kingdom (legislation) and Hong Kong (legislation) provide a limited term of copyright protection for computer-generated works of 50 years from creation. |
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Legal disclaimer Most image-generating AI models were trained using works that are protected by copyright. In some cases, such models can output content with major copyrightable image elements which are identical to or derivative of the original training data, making these outputs derivative works. Accordingly, there is a risk that AI-generated media uploaded on Commons may violate the rights of the authors of the original works. See Commons:AI-generated media for additional details. |
