Under the Hood of Creativity: A Look Inside the Workings of Generative Models

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Under the Hood of Creativity A Look Inside the
Workings of Generative Models
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For centuries, creativity has been considered a
hallmark of human intelligence. The ability to
generate new ideas, concepts, and artistic
expressions has fueled innovation and progress
throughout history. However, with the rise of
artificial intelligence (AI), a new player has
entered the scene, blurring the lines between
human and machine creativity.
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At the core of generative AI lies the concept of
machine learning. Generative models are trained
on massive datasets of existing content, like
text, images, or code. This training process
involves feeding the model with countless
examples, allowing it to identify underlying
patterns and relationships within the data.
Imagine a generative model trained on a vast
library of paintings.
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The working of generative AI doesn't stop at
simply creating content. These models can further
be fine-tuned to respond to specific prompts and
user inputs. Imagine instructing a generative
model to create an image of a "cat wearing a hat
on a moonlit night." By incorporating textual
prompts into the generation process, we unlock
targeted creativity, allowing users to guide the
model towards their desired outcome.
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