AI slop isn't just tacky and uninspired. It can get you sued.
Generating fake AI faces that resemble real people, or using someone's likeness without permission, is creating new legal and reputational risks for brands.
So we built @mirrormirror_ai as part of a16z @speedrun, a marketplace where brands can digitally book real models and creators to generate AI content using their likeness, with their permission.
Brands browse and book identity-verified talent, agree on usage rights, and generate content within those terms. Every approved image comes with a signed license and embedded provenance.
We're seeing brands produce lookbooks and campaign visuals up to 10x faster, with up to 90% cost savings. Meanwhile, models and creators can earn additional income from their digital likeness without having to show up for another shoot.
Everyone is racing to make AI generation faster, cheaper, and more realistic. But there's still a huge missing piece: how do you license the rights to the people appearing in AI-generated content at scale?
That's why I'm excited about what we're building. Not just another AI generator, but the licensing and rights infrastructure for AI-generated content.
mirrormirrorai.com
In the latest PyTorch 1.12 Release, we shared TORCHREC V0.2.0. Highlights include:
EmbeddingModule + DLRM benchmarks.
A set of benchmarking tests showing performance characteristics of TorchRec’s base modules and research models built out of #TorchRec. bit.ly/3vlgV5x
@decisiontree7 Hi @decisiontree7 , I work on torchrec and we would welcome any feedback you have! We are actually starting discussions with Merlin (cc @Even_Oldridge ) about how our libraries can best work together. If you're interested in connecting, let me know and we can VC
Introducing TorchRec, a PyTorch domain library for building and deploying modern production recommendation systems, enabling multi-trillion parameter models. Learn more: pytorch.org/blog/introduci…
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