좋은 쇼핑 경험은 개인적인 질문에 대답합니다: 이것이 나를 어떻게 보일 것인가?
SPREEAI brings that answer into view. One photo becomes a way to explore a garment on yourself, with the detail and familiarity that make an image feel real.
Behind that moment is years of research, careful engineering, and infrastructure built to keep pace. Our collaboration with Lambda helps bring those pieces together.
모든 세부 사항은 당신의 신뢰를 얻습니다.
이 떨어지는 길. 목걸이의 모양을 보여준다. 좋아하는 작품에 대한 글쓰기. 작은 세부 사항은 많은 의미를 가지고 있습니다.
Our virtual try-on model brings pose, fabric, identity, and garment detail into one generation process. It is trained to understand how clothing changes across bodies and positions while preserving what makes the person recognizable and the garment distinctive.
That is what photorealism asks of us: care at every level, even where the technology is invisible.
더 나은 엔지니어링 창조할 공간이 더 많다.
Working alongside Lambda’s machine learning engineers, our team refined how training data is stored, how experiments are scheduled, and how compute is used on Lambda’s NVIDIA H100 infrastructure.
Lambda’s latest case study reports storage costs reduced by more than 30× and model FLOPs utilization rising from roughly 20% to 43%—a measure of how much available compute becomes useful model work. Per-try-on inference time fell from 23 seconds to under 10.
우리의 엔지니어들에게, 그것은 테스트 및 정화 할 수있는 더 많은 능력을 의미합니다. 구매자에게는 시선을 볼 때까지 기다리는 시간이 덜 되는 것을 의미합니다.
다음에 무슨 일이 일어날지 보세요.
We are building toward richer ways to explore fashion, including layered looks and video try-on. The ambition is simple: give people a clearer sense of what they are choosing, wherever they shop.
램프의 발음을 Lambda 고객 이야기 그리고 기술 깊은 굴곡 경험 뒤에 있는 작업을 더 자세히 살펴보도록 하겠습니다.