AI Art

Explore how CLIP, an innovative AI model by OpenAI, generates objective aesthetic scores for artwork. Discover its implications for the art world, from democratizing art evaluation to uncovering new talent and enhancing art education.

Generative art with AI is a collaborative process that involves giving the AI direction while accepting its inherent unpredictability. AI models learn from large datasets of images, producing unique outputs by transforming random or user-defined input seeds. Chaos and entropy play different roles in various AI model architectures, impacting the sensitivity to input changes, but also introducing diversity in the generated outputs. Embracing the unpredictability of AI-generated art can lead to the creation of innovative and unexpected works, pushing the boundaries of creativity beyond human limitations.

Discover the power of divergent perspectives in AI with entropic shaping and chain of thought. Learn how these contrasting approaches embrace uncertainty and seek precision to drive innovation in problem-solving and creative endeavors.

Accessing Latent Space is like entering a universe of limitless invention, where AI can create anything. It is an interactive voyage that uncovers the immensity of this space, highlighting the importance of human creativity in perfecting its outputs. Despite its vastness, there are still gaps and restrictions, reminding us of the need for human input in the creative process.

CLIP Score measures similarity between AI-generated image and text caption, useful for computer vision and language tasks. CLIP allows models to understand visual-textual relationships and perform image captioning and retrieval. To compute CLIP score, use pre-trained CLIP model to produce embeddings and calculate cosine similarity.

In AI-generated art and storytelling, camera positions can enhance the emotional resonance of your creation. Experimenting with various camera angles can effectively express emotions and support your narrative. This guide explores different camera positions in cinematography, their effects on storytelling and how to adapt them for AI Art and Generative AI platforms.

Estimating the potential outputs of stable diffusion is crucial in understanding its generative capabilities. The size of its latent space determines its capacity for information storage, system complexity, and the probability of copyright collisions. It is challenging to calculate the size of latent space, but having a clear goal in mind when using stable diffusion is essential.

Discover how the Red Cat Series helps reveal the limitations and strengths of Midjourney's artistic capabilities, while showcasing its innovative approach to generating portraits and creative problem-solving. These striking images of red cats, each symbolizing a particular profession or type, are set against neutral, post-industrial backdrops that create an arc of tension and intrigue. In the creation of the Red Cat Series, Midjourney utilized advanced techniques, including outpainting, prompt engineering, and creative problem-solving, to achieve the desired aesthetic.

The rise of AI-generated art and NFTs could create a more diverse and accessible art market. However, there are concerns about oversupply and the impact on prices. Despite this, the open nature of AI art and NFTs could reinforce each other and democratize art investment.

AI artists explore the Latent Space, a compressed knowledge model. It refers to all potential outputs allowed by the model. Our creative output, experience, and ideas exist in the infinite latent space.