Types of Generative AI Tools You Should Know

Introduction

Generative AI is revolutionizing how we create and interact with content—producing everything from lifelike images to expressive text and AI-generated videos. These technologies are reshaping industries, unlocking new creative possibilities, and personalizing experiences at scale. Platforms like Glance are leading this evolution, using generative AI to deliver dynamic, real-time content and transforming how users discover, shop, and engage—right from their mobile screens and smart TVs through the Glance AI app. In this guide, we’ll explore the different types of generative AI tools, how they work, and why they’re shaping the future of digital creation.

What is Generative AI?

Generative AI is a subset of artificial intelligence focused on creating new content—whether it’s images, text, music, or video—by learning from existing datasets. Unlike traditional AI models, which make predictions or classifications based on data, generative AI produces entirely new data.

This technology has a wide range of applications, from automating content creation and personalizing experiences to enhancing creativity in art, entertainment, and design. Whether you are a marketer, a designer, or a content creator, generative AI tools have the potential to enhance productivity and creativity.

Types of Generative AI Models

Generative AI tools can be categorized into different types, depending on the content they create. Below are the most popular types of generative AI models that are reshaping content creation:

1. Generative AI Image Creators

Generative AI image creators are tools that can produce realistic or artistic images from textual descriptions or other forms of input. These tools are primarily based on Generative Adversarial Networks (GANs), which learn the features of images from vast datasets and use this knowledge to generate entirely new visuals.

Popular Tools:

• DALL·E 2: An AI model that generates images based on text descriptions. Known for producing highly detailed and creative visuals.
• Midjourney: Specializes in generating artistic and surreal images with a unique visual style.
• Stable Diffusion: A more flexible open-source model that allows users to create high-quality images based on textual input.

Use Cases:

Generative AI image creators are used by graphic designers, marketing teams, and digital artists to generate marketing visuals, product designs, concept art, or even album covers.

2. Generative AI Text Generators

Text generation tools use deep learning models to create human-like text. These AI tools can generate anything from blog posts to dialogue, poems, or marketing copy. They are typically based on transformer models, such as GPT-3 and GPT-4, which are capable of understanding context and producing coherent text.

Popular Tools:

• ChatGPT (GPT-4): A conversational AI capable of generating coherent text, answering questions, and providing explanations.
• Jasper AI: Primarily used for marketing content, it can generate blog posts, social media captions, and ad copy.
• Copy.ai: A tool designed for quick, high-quality content generation for businesses, from product descriptions to blog posts.

Use Cases:

These generative AI text tools are widely used in content marketing, customer support automation, and creative writing, helping businesses scale their content production efforts.

3. Generative AI Video Tools

Generative AI video tools are still emerging but are rapidly gaining popularity. These tools use AI algorithms to generate videos, often by combining text, image, or audio inputs. One of the most common techniques is DeepFake technology, which manipulates video content to create realistic synthetic media.

Popular Tools:

• Synthesia: This tool can create AI-generated videos with virtual avatars that speak scripts provided by users. It’s widely used for training videos, corporate communication, and educational content.
• Runway ML: A versatile tool that allows for advanced video editing, background removal, and video generation.
• Pictory: A video generation tool that can automatically turn long-form blog posts into short, engaging videos.

Use Cases:

AI video tools are used for creating explainer videos, advertisements, educational content, and even personalized videos for audiences in real time.

4. Generative AI Music and Audio Tools

Generative AI music tools create original music compositions or replicate human voices by learning from existing music and voice recordings. These tools are particularly popular for creating royalty-free music for videos, games, and podcasts.

Popular Tools:

• Jukedeck: AI-generated music that can be personalized based on genre, mood, and tempo.
• Descript: Allows users to generate voiceovers or mimic a specific voice.
• Boomy: Creates instant music tracks with just a few clicks.

Use Cases:

Content creators, podcasters, and filmmakers use AI music and audio tools to enhance their work with unique soundtracks, voiceovers, or background scores.

5. AI Code Generation Tools

AI tools for code generation help developers write code faster and with fewer errors. These tools use machine learning to understand and predict the next steps in the code-writing process.

Popular Tools:

• GitHub Copilot: Provides AI-generated code suggestions in real time based on the context of the code being written.
• Tabnine: An AI-powered code completion tool that helps developers write clean and efficient code.
• Amazon CodeWhisperer: A tool by AWS that generates code based on natural language commands.

Use Cases:

Developers use these tools to speed up their coding process, debug issues, and automate repetitive tasks, enhancing productivity and reducing errors.

Comparison of Popular Generative AI Tools

Below is a comparison table showcasing some of the top generative AI tools across different content types:

How Generative AI Models Work

Generative AI models are built on complex algorithms that learn patterns from vast datasets. These models, like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), work by analyzing data, identifying patterns, and generating new outputs based on that learning.

For instance, GANs consist of two neural networks—the generator and the discriminator—which work together to produce high-quality content. The generator creates content, while the discriminator evaluates it, pushing the generator to improve its output continually.

Benefits of Generative AI Tools

1. Increased Efficiency: Generative AI tools can automate repetitive tasks, saving time for content creators.
2. Enhanced Creativity: AI models generate unique content, enabling creators to explore new artistic directions.
3. Cost-Effective: With AI tools handling content creation, businesses can reduce their reliance on large teams of designers, writers, and videographers.
4. Personalization: AI-powered tools can tailor content to specific audiences, improving engagement.

Challenges of Generative AI

While generative AI offers numerous advantages, it also comes with challenges:

• Ethical Concerns: The potential misuse of AI, such as creating deepfakes or fake news, raises significant ethical issues.
• Bias: AI models can inherit biases from the data they are trained on, leading to skewed or unfair outputs.
• Data Privacy: The use of personal data to train AI models raises privacy concerns that need to be addressed.

The Future of Generative AI Tools

The future of generative AI is bright, with advancements in AI models leading to even more realistic and innovative content creation. Expect more powerful multimodal AI tools capable of handling text, image, video, and audio simultaneously.

Generative AI tools will continue to empower creators, businesses, and developers to produce high-quality content with unprecedented speed and efficiency, opening up new opportunities across industries.

Conclusion

Generative AI tools are transforming how we approach creativity and content generation. From AI image creators to video generators, these tools are making it easier and faster to create high-quality content, revolutionizing industries ranging from marketing and entertainment to education and technology. As these tools evolve, we can expect even more innovative and personalized content to emerge, making it an exciting time for creators and businesses alike.

By understanding the different types of generative AI tools and their applications, you can choose the right tools to enhance your creative and business processes. Embrace the power of AI and explore the vast possibilities that lie ahead.

FAQs

What are the main types of generative AI tools?

The main types include image generators, text models, video creators, music/audio tools, and code generators. Each is designed to create content in its respective format using AI-powered algorithms.

What are generative AI images?

Generative AI images are visuals created by artificial intelligence models trained on large datasets. These tools can generate new images based on text prompts or learned visual patterns, often producing highly realistic or artistic results.

What is the best generative AI image creator?

Some of the most popular and effective generative AI image creators include DALL·E 2 (known for photorealism), Midjourney (famous for artistic styling), and Stable Diffusion (an open-source powerhouse for flexible image generation).

Can generative AI create videos?

Yes, it can. Tools like Synthesia and Runway ML are leading the way in AI-generated video content. They can produce explainer videos, and avatar-led presentations, and even edit or enhance video content automatically.

Where can I find a list of generative AI models?

You can find extensive lists of generative AI models on platforms like Hugging Face, Papers With Code, and other AI research directories. These platforms categorize tools for tasks like image generation, natural language processing, audio synthesis, and more.