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Generative AI Playbook by PromptxAI, MorphicShot, Product Prompt, Midjourney, Contents.com, Components AI, Claude Prompts are the best paid / free generative ai definition tools.
Generative AI is a subset of artificial intelligence that focuses on creating new content, such as text, images, audio, or video, based on learned patterns and rules from existing data. It has gained significant attention in recent years due to advancements in deep learning techniques and increased computational power.
Core Features
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Midjourney | Explore hundreds of AI art styles | To use Midjourney, simply copy the prompt, swap the subject, and drop it into your favorite generator. It's completely free! | |
Contents.com | content ideation | Login to the platform, choose from a variety of tools such as AI Chat, AI Writer, AI Art, Audio ↔ Text, and AI Translation to support your content creation needs. Generate high-performing, original, and SEO-optimized content for your digital channels. | |
Components AI | Visually design custom design tools, generative components, pages, and sites |
Free Free Basic features with limited access
| Build custom design tools without writing any code. Create responsive components, pages, and sites that you can use in any type of web project. Style markup templates with curated themes or your own design tokens. |
Generative AI Playbook by PromptxAI | Collection of popular examples of Generative AI | To use the Generative AI Playbook, you can explore the popular examples provided, such as content generation, content ingestion, and trends impacting the future of work. You can also access the extended playbook with a generic framework that includes prompt management, LLM models, content enhancement, and other tools. Additionally, you can learn about prompt engineering techniques to optimize the performance of Generative AI applications like ChatGPT, DALL-E, and Midjourney. The playbook also provides accelerator notebooks and code libraries to help you start working with Generative AI. | |
Claude Prompts | Text generation | To use Claude Prompts, craft specific and clear instructions or context for the model, input them into a chosen platform or tool, then generate and refine text outputs iteratively based on the model's responses. | |
MorphicShot | AI-powered profile picture generation | To use MorphicShot, follow these steps: 1. Login or create an account. 2. Upload 5 different selfies or photos of yourself or another person with various angles. 3. Wait while the AI builds your studio based on the uploaded photos. 4. Create a perfect prompt to guide the AI in generating the desired profile pictures. 5. Pay $12 to access the studio and receive 30 profile pictures in various styles, all in upscale 4K definition. | |
Product Prompt | No coding required | 1. Sign up for an account. 2. Create a project and input your product data. 3. Compose prompts using the intuitive interface. 4. Generate AI outputs based on the prompts. 5. Iterate and refine your prompts to achieve desired results. |
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Marketing and advertising: Generating personalized ad copy and images
Entertainment: Creating new video game assets, such as characters and environments
Healthcare: Generating synthetic medical images for training diagnostic models
Education: Developing adaptive learning content and assessments
Users have praised generative AI tools for their ability to inspire creativity and streamline content creation processes. However, some have raised concerns about the potential for generating biased or low-quality content, emphasizing the need for human oversight and curation. Overall, users find generative AI to be a powerful tool when used responsibly and in conjunction with human expertise.
A user interacts with a generative AI-powered chatbot that creates personalized responses based on the conversation history
An artist uses a generative AI tool to create new visual designs and patterns for their work
A customer engages with a generative AI-based virtual assistant that offers tailored product recommendations
To use generative AI, follow these steps: 1. Collect and preprocess a large dataset of the desired content type (e.g., images, text). 2. Choose an appropriate generative AI model architecture, such as a GAN or VAE. 3. Train the model on the dataset, allowing it to learn patterns and rules. 4. Use the trained model to generate new content by providing it with a seed or input. 5. Evaluate and refine the generated content based on the desired quality and diversity.
Enables the creation of novel and unique content
Reduces the time and effort required for manual content creation
Allows for the exploration of creative possibilities and variations
Enhances data augmentation techniques for improved model performance