AI-Made Influencers: Blueprint to Craft Virtual Influencer
How to disrupt Influencer Marketing with AI
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The Industry Revolution
Miquela is a testament to the potential of virtual personalities in modern marketing. She's a fabricated 19-year-old Brazilian-American model, singer, and influencer intricately designed to captivate and charm the digital populace. Her journey – from a social media experiment to a Time Magazine-recognized influencer – is revolutionary. Her creators, Trevor McFedries & Sara Decou, have harnessed her virtual presence to secure collaborations with luxury brands like Prada and Calvin Klein and tech giants like Samsung, showcasing her diverse appeal; she's living proof that virtual influencers are a goldmine. Simple brand integration costs around $9k per post!
Have you ever wondered how virtual influencers like Lil Miquela rake in over $500K a year? It sounds like fiction. Big brands are ready to pay digital people to promote their products.
Compared to traditional influencers, virtual influencers are obviously more cost-effective but can be monetized as well, and what is most important is there is no limit in production!
The only bottleneck in creating virtual influencers was expensive graphic design (before 2023). Hosting a virtual influencer could cost a company a couple thousand grand a year plus the cost of hardware/graphic cards. This year, it became more accessible than ever.
Let's pull back the curtain on making your AI influencer from scratch!
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Step-by-Step Guide: Create Your AI Influencer
Creating your own Lil Miquela might sound like a tech wizard's job, but with today's tools, anyone can do it. Here is proof:
1. Find the Face:
• We will use Tensor Art. It's an entirely free service with multiple models to generate the images. (Be careful some content on the Tensor Art platform may be NSFW)
At first sight, it will look very familiar with other ai image generators. There is input for writing prompt and for negative prompt,image2image, select model and Aspect ratio. But there are some good features inside: LoRA and add ControlNet.
LoRA stands for Locally-Optimized Representations for Adaptive Diffusion Models. It is a technique that is used to improve the quality of images generated by diffusion models. LoRA works by creating a local representation of the image that is being generated. This local representation is then used to guide the diffusion model in generating the image.
ControlNet is a technique that is used to control the generation of images by diffusion models. ControlNet works by creating a network of nodes that represent different aspects of the image being generated. These nodes can then be used to control the generation of the image, such as the style, color, and composition.
It turns out you can control the position of characters.
Select the Juggernaut-aftermath model for ultra-realistic results. You can also find other Realistic models on Tensor Art and download them if you dislike using that platform.
Now simply run this model, and you’ll have the interface like this one:
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