How Does Generative AI Work?
Generative AI tools like LLMs typically follow four cyclical steps beginning with the training phase.
- Training Phase: Generative AI tools undergo training, utilizing vast datasets to learn and recognize complex patterns.
- User Interaction: Individual users engage with generative AI tools typically via textual prompts, providing specific input that guides the generative process.
- Data Synthesis: Upon receiving an input, the AI processes it in conjunction with its pre-existing knowledge base derived from its training.
- Generated Output: The AI tool then produces a unique output that mirrors the learned patterns from its training data. This output can occur in various forms such as text, images, audio, or video content.
If Generative AI was a Baker
Another way to think about it is the Baker Analogy:
Image generated with Adobe Firefly, September 2024
- Training Phase: Imagine a baker who spends years perfecting their craft. They study countless recipes, learn various techniques, and experiment with different ingredients.
- User Interaction: Picture a customer walking into the bakery and requesting a specific type of cake. The customer provides details about their preferences, such as flavor, size, and decoration.
- Data Synthesis: The baker then takes the customer’s request and draws on their extensive knowledge and experience to create a unique recipe.
- Generated Output: Finally, the baker bakes the cake, which is a unique creation based on the customer’s specifications and the baker’s expertise.
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