Awesome Generative AI – Comprehensive Guide to AI Tools and Resources
Awesome Generative AI
A curated list of modern Generative Artificial Intelligence projects and services.
Generative Artificial Intelligence is a technology that creates original content such as images, sounds, and texts by using machine learning algorithms that are trained on large amounts of data. Unlike other forms of AI, it is capable of creating unique and previously unseen outputs such as photorealistic images, digital art, music, and writing. These outputs often have their own unique style and can even be hard to distinguish from human-created works. Generative AI has a wide range of applications in fields such as of art, entertainment, marketing, academia, and computer science.
Contributions to this list are welcome. Before submitting your suggestions, please review the Contribution Guidelines to ensure your entries meet the criteria. Add links through pull requests or create an issue to start a discussion. More projects can be found in the Discoveries List, where we showcase a wide range of up-and-coming Generative AI projects.
Article summarizing the capabilities and limitations of the GPT-3 model, and its potential impact on society. By Alex Tamkin and Deep Ganguli, February 5, 2021.
A comprehensive examination of the generative AI industry, offering a historical perspective and in-depth analysis of the industry ecosystem. By Sonya Huang, Pat Grady and GPT-3, September 19, 2022.
Article about the rise of generative AI, particularly the success of the Stable Diffusion image generator, and the associated controversies. New York Times, October 21, 2022.
Article about the growing hype and investment in generative AI startups, with various industries exploring its potential applications. Wired, October 27, 2022.
Announcement of the release of DALL·E 2, an advanced image generation system with improved resolution, expanded image creation capabilities, and various safety mitigations.
Announcement of the public release of Stable Diffusion, an AI-based image generation model trained on a broad internet scrape and licensed under a Creative ML OpenRAIL-M license.
Announcement of ChatGPT, a conversational model trained to answer follow-up questions, admit mistakes, challenge incorrect premises, and reject inappropriate requests.
Open-source coding assistant that runs on your laptop.
Open Source Local
Comparing AI Coding Assistants
As AI coding tools continue to evolve, developers now have multiple options to choose from. Here’s how some of the leading tools compare:
Tool
Best For
Pricing
Key Features
GitHub Copilot
Professional developers
$10/month or $100/year
Integrated with VS Code, JetBrains IDEs, and Neovim; Advanced code completion; Context-aware suggestions
Amazon CodeWhisperer
AWS developers
Free for individual use
Integrated with AWS Cloud9; Security scanning; Code references
Cursor
Fast prototyping
Free, Pro: $20/month
Built on VS Code; Chat interface; GPT-4 integration
Codeium
Individual developers
Free for individuals
Supports 20+ languages; IDE integrations; Fast autocomplete
Agents
What are AI Agents?
AI agents are autonomous systems that can perceive their environment, make decisions, and take actions to achieve specific goals. Unlike regular AI models that respond to single prompts, agents can perform complex sequences of tasks, reason about information, and use tools to accomplish objectives with minimal human intervention.
Lighting: Describe the lighting conditions (e.g., golden hour, dramatic, soft)
Composition: Indicate framing, perspective, or camera angle
Example Prompt
“A serene mountain lake at sunrise, with a small wooden cabin on the shore, mist rising from the water, ultra-detailed digital painting, dramatic lighting, in the style of Thomas Kinkade, 4K resolution”
Open source text-to-video and image-to-video model by Stability AI.
Audio
Generative AI is revolutionizing audio production across music, voice synthesis, sound effects, and audio enhancement.
From creating original compositions to cloning voices and restoring audio quality, these tools are transforming how we create and interact with sound.
The rise of AI audio tools, particularly voice synthesis and cloning, raises important ethical concerns that creators and users should be aware of:
Consent: Always obtain explicit permission before cloning someone’s voice.
Impersonation: Voice cloning can be misused for fraud, misinformation, or impersonation.
Transparency: Disclose when AI-generated voices are used in content.
Copyright: Consider rights implications when generating music similar to existing artists.
Watermarking: Support efforts to watermark AI-generated audio for detection.
Many reputable AI audio companies have implemented safeguards and terms of service to prevent misuse, but responsible usage remains the responsibility of creators.
Other
Beyond text, image, video, and audio, generative AI is making significant impacts across various other domains and applications.
This section explores innovative use cases and specialized applications of generative AI technology.
Open-source implementation of vision-language capabilities.
Open Source
Learning Resources
This section compiles high-quality resources for learning about generative AI, from beginner-friendly courses to advanced research papers.
Whether you’re just getting started or looking to deepen your expertise, these resources will help you understand the technology behind generative AI.
Open-source communities and repositories focused on generative AI.
Free
More Lists
Looking for more curated resources on generative AI and related topics?
Check out these other awesome lists that provide specialized collections in various domains.
