The Agency

Last spring, the clothing brand Levi Strauss & Co. announced plans to introduce "customized AI-generated models" into its online shopping platforms. These "body-inclusive avatars" would come in a range of sizes, ages, and skin tones and would help Levi's create a more "diverse" lineup in a way the company considered "sustainable." A lot of (real) people were appalled. Why not give those jobs to actual humans of the sizes, ages, and skin tones Levi's sought? Was "sustainable" just PR-speak for "cheaper"?

Fine-tuning is becoming widely used for leveraging the power of pre-trained foundation models in new downstream tasks. While there are many successes of fine-tuning on various tasks, recent studies have observed challenges in the generalization of fine-tuned models to unseen distributions (i.e., out-of-distribution; OOD). To improve OOD generalization, some previous studies identify the limitations of fine-tuning data and regulate fine-tuning to preserve the general representation learned from pre-training data. However, potential limitations in the pre-training data and models are often ignored. In this paper, we contend that overly relying on the pre-trained representation may hinder fine-tuning from learning essential representations for downstream tasks and thus hurt its OOD generalization. It can be especially catastrophic when new tasks are from different (sub)domains compared to pre-training data. To address the issues in both pre-training and fine-tuning data, we propose a novel generalizable fine-tuning method LEVI, where the pre-trained model is adaptively ensembled layer-wise with a small task-specific model, while preserving training and inference efficiencies. By combining two complementing models, LEVI effectively suppresses problematic features in both the fine-tuning data and pre-trained model and preserves useful features for new tasks. Broad experiments with large language and vision models show that LEVI greatly improves fine-tuning generalization via emphasizing different views from fine-tuning data and pre-trained features.

Aitana López seems to have come out of nowhere and taken the modeling industry by storm. The pink-haired, toned 25-year-old from Barcelona has reportedly secured advertising deals worth more than $1,000 per Instagram post, and has more than 100,000 online followers. Her Instagram feed shows her posing in outfits from Guess, Brandy Melville, and Victoria's Secret, and tagging haircare brand Olaplex to give them apparent credit for her vibrant locks. In fact, Aitana López was created using artificial intelligence. The caption, translated from Spanish, reads, 'No matter the occasion, the'little black dress' never fails!

The star of Levi's new campaign looks like any other model . Her tousled hair hangs over her shouldersas she gazes into the camera with that far-off high-fashion stare. But look closer, and something starts to seem a little off. The shadow between her chin and neck looks muddled, like a bad attempt at using FaceTune's eraser effect to hide a double chin. Her French manicured fingernails appear scrubbed clean and uniform in a creepy real doll kind of way.

AI-generated models are coming to Levi's e-commerce sites. The goal is to sustainably increase the number and diversity of models for its products, it said. Founded in 2019, Lalaland utilizes AI to enable fashion brands and retailers to use hyper-realistic models of every body type, age, size, and skin tone. With these body-inclusive avatars, the company aims to create a more "inclusive, personal, and sustainable shopping experience" for fashion brands, retailers, and customers. "We see fashion and technology as both an art and a science, and we're thrilled to be partnering with LaLaLand, a company with such high-quality technology that can help us continue on our journey for a more diverse and inclusive customer experience," said Dr. Amy Gershkoff Bolles, LS&Co.

The famous clothing brand Levi Strauss & Co. has announced a partnership with digital fashion studio Lalaland.ai. As a result of the partnership, the brand will benefit from artificial intelligence-generated models.

Levi Strauss announced plans to test customized AI-generated models with the goal of multiplying the number and diversity of models that customers can see. The denim giant partnered on the test with LaLaLand.ai, Currently, shoppers on Levi.com typically only see one model for each product. The AI technology, according to Levi's, "can potentially assist us by supplementing models and unlocking a future where we can enable customers to see our products on more models that look like themselves, creating a more personal and inclusive shopping experience." The project supports Levi's broader diversity, equity and inclusion objectives.

Levi Strauss & Co is taking a futuristic approach when displaying it line of jeans - the company is using models generated by artificial intelligence to show off its clothing and consumers may not be able to tell the difference. Set to launch later this year, the initiative will present AI models in different body types, skin colors ang ages, allowing customers to see how products might look on them. Levi currently displays one human model per clothing item. The San Francisco-based company said'AI will likely never fully replace human models' for the company, but offering a range of digital models will create'a more personal and inclusive shopping experience.' Levi Strauss & Co is set to use AI-generated models to show off its clothing. Can you spot which image is the AI and which is a real person?

Levi's is partnering with an AI company on computer-generated fashion models to "supplement human models." Although that sounds noble on the surface, Levi's is essentially hiring a robot to generate the appearance of diversity while ridding itself of the burden of paying human beings who represent the qualities it wants to be associated with its brand. Levi Strauss is partnering with Amsterdam-based digital model studio Lalaland.ai Founded in 2019, the company's mission is "to see more representation in the fashion industry" and "create an inclusive, sustainable, and diverse design chain." It aims to let customers see what various fashion items would look like on a person who looks like them via "hyper-realistic" models "of every body type, age, size and skin tone."