Nvidia and WPP, the world's largest advertising company, have announced a partnership to use generative AI to create stunning and realistic content for brands and campaigns. Generative AI is a branch of artificial intelligence that can produce new images, sounds, and texts from existing data, such as photos, videos, and audio.
Nvidia's CEO Jensen Huang said: “WPP is one of the most influential companies in the world. They have the vision to see how AI will transform their industry and the scale to make it happen. We're thrilled to partner with them to create the future of content creation.”
The partnership will leverage Nvidia's Omniverse platform, which is a cloud-based collaboration tool that allows creators to work together in real-time across different software applications. Omniverse also provides access to Nvidia's powerful GPUs and AI frameworks, such as StyleGAN and GauGAN, which can generate photorealistic faces and landscapes with a few clicks.
WPP will use Omniverse to create content for its clients across various industries, such as automotive, fashion, retail, and entertainment. For example, WPP can use generative AI to create virtual models for fashion shows, or to design realistic car interiors for automotive ads. WPP can also use generative AI to personalize content for different audiences and markets, or to test different creative options before launching a campaign.
Nvidia and WPP claim that generative AI will revolutionize the content creation industry by reducing costs, increasing efficiency, and enhancing creativity. They also say that generative AI will enable new forms of storytelling and expression that were not possible before.
WPP's CEO Mark Read said: “Nvidia's technology is at the forefront of innovation in AI and graphics. By combining their capabilities with our creative talent and global reach, we can offer our clients a unique service that will set new standards for creativity and effectiveness.”
Generative AI Becoming Standard Across Tech Industries
Generative AI is a type of artificial intelligence (AI) system that can create new content, such as text, images, or audio, from existing data. Generative AI models learn the patterns and structure of their input training data, and then generate new data that has similar characteristics. Generative AI can be used for various purposes, such as in creative fields like art, music, and writing, or in practical fields like healthcare, finance, and gaming. However, generative AI can also pose some ethical and social challenges, such as creating fake or misleading content that can harm people or society.
There are many recent products that include generative AI, especially in the fields of software development, content creation, and advertising. Some examples are:
- ChatGPT, a free chatbot that can generate an answer to almost any question it's asked, powered by GPT-4.
- Bing Chat: Microsoft's AI search tool that uses elements of GPT-4 and Microsoft's own AI to generate search responses.
- GitHub Copilot, a code completion tool that can suggest and write code for developers, powered by GPT-4.
- Bard, a chatbot that can generate natural language responses to any query, powered by Google's LaMDA foundation model.
- DALL-E, a tool that can create images from text descriptions, powered by GPT-4.
- Stable Diffusion, a tool that can create high-resolution images from sketches or prompts, powered by latent diffusion.
- Midjourney, a tool that can create realistic 3D scenes from text descriptions, powered by latent diffusion.
- Copilot, a tool that can automate tasks within Microsoft's work apps, such as Word, Excel, PowerPoint, Outlook, and Teams, powered by GPT-4.
- Duet AI, a tool that can assist users with various tasks within Google's work apps, such as Docs, Sheets, Slides, Gmail, and Meet, powered by Google's MUM foundation model.
- Google Ads Creative Studio, a tool that can help advertisers create campaigns, generate copy, and build variations of images using generative AI.
Last Updated on August 4, 2023 2:05 pm CEST by Markus Kasanmascheff
