AI-GENERATIVE.ORG runs on the AI-Generative Platform.See how it works →
Follow the developments, releases, research, and ideas shaping how generative AI is built, adopted, and governed.
Source-led reporting and analysis, selected for consequence and relevance.
LinkedIn is a powerful tool for professionals to connect with potential employers, clients, and colleagues. A strong LinkedIn profile can help you stand out from the competition and land your dream job
Generative AI is a type of artificial intelligence that can be used to create new content, such as text, images, and music. This content can be personalized to the individual user, based on their interests, preferences, and past behavior.
Generative AI has the potential to revolutionize the way we work, and it could lead to significant changes in the future of jobs. On the one hand, generative AI could lead to the automation of many jobs that are currently done by humans.
Generative AI is a rapidly evolving field that is having a major impact on the arts. Artists are using generative AI to create new forms of art that are more abstract, experimental, and challenging than traditional art.
With generative AI, you can create realistic images, generate creative content, and improve your writing skills. So what are you waiting for? Start exploring the world of generative AI today!
Google Cloud today announced a number of new generative AI capabilities, including a new API for generating text, an image generation tool, and a chatbot platform. These new capabilities make it easier for businesses to build and deploy generative AI applications.
NVIDIA today announced the launch of Omniverse Avatar, a platform for creating realistic virtual humans. Omniverse Avatar uses generative AI to create avatars that can see, speak, converse on a wide range of subjects, and understand naturally spoken intent.
Google has recently announced a new text-to-image AI model called Imagen. Imagen is capable of creating photorealistic images from text descriptions. This is a significant improvement over previous text-to-image models, which often produced images that were blurry or unrealistic.