How I Create Consistent Characters with DALL-E 3 in ChatGPT.

How I Create Consistent Characters with DALL-E 3 in ChatGPT..

Overview

Author(s): Kris Ograbek

Originally published on Towards AI.

And why I’m so excited about it?
AI-Augmented Artist. Image by the author generated with ChatGPT & DALL-E 3.

“If you want your children to be intelligent, read them fairy tales. If you want them to be more intelligent, read them more fairy tales.” Albert Einstein

This introduction will be personal, so feel free to skip it if you’re here just for the technical guide.

As a dad, I’ve been dreaming about creating illustrated books for my kids.

I want the books to teach my kids important and valuable things but in a fun way.

But here’s my problem: I’m a terrible designer. I can’t create illustrations. I draw or paint like… Read the full blog for free on Medium.

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Published via Towards AI

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AI Applications

One AI application for businesses facing the choice between open-source and proprietary models to deploy generative AI is natural language processing (NLP) for customer service or support chatbots. Businesses can utilize generative AI models to develop chatbots that can understand and respond to customer queries in a more human-like manner. The choice between open-source and proprietary models can impact the accuracy, scalability, and customization capabilities of the NLP models deployed in these chatbots.

Additionally, another AI application is the development of recommendation systems. Generative AI models can be used to create personalized recommendations for products or content based on user behavior and preferences. The choice between open-source and proprietary models can affect the quality of the recommendations, as well as the ability to tailor the recommendation system to specific business needs.

Furthermore, businesses can leverage generative AI for content generation, such as automated text summarization, language translation, and creative writing. The choice between open-source and proprietary models can influence the linguistic fluency, coherence, and originality of the generated content.

In each of these applications, the decision between open-source and proprietary models for generative AI deployment can significantly impact the performance, interpretability, and ethical considerations of the AI systems utilized by businesses.