Lightly Blog

Introducing LightlyTrain: Better Vision Models, Faster - No Labels Needed

LightlyTrain lets you pretrain vision models on your own unlabeled data — no labels needed. Improve performance on classification, detection, and segmentation tasks while reducing labeling costs and speeding up deployment. Compatible with popular architectures like YOLO, RT-DETR, and ResNet, LightlyTrain adapts models to your domain and integrates easily into existing pipelines — fully on-premise and scalable to millions of images.

NVIDIA Blackwell B200 vs H100: Real-World Benchmarks, Costs, and Why We Self-Host

The B200 is up to 57% faster for model training than the H100, up to 10x cheaper to run when self-hosted, and we’ve broken down all the costs, performance metrics, and power consumption data inside.

The 101 Introduction to Multimodal Deep Learning

Discover how multimodal models combine vision, language, and audio to unlock more powerful AI systems. This guide covers core concepts, real-world applications, and where the field is headed.

The Engineer's Guide to Self-Supervised Learning

Learn what self-supervised learning is and how engineers can use it to train AI models with minimal labeled data. This guide explores key techniques, real-world applications, and the benefits of self-supervised learning in computer vision and machine learning.

12 Best Data Annotation Tools for Computer Vision (Free & Paid)

Discover the 12 best data annotation tools for computer vision, including both free and paid options. This guide covers top labeling software for image and video annotation, helping AI teams improve model accuracy and efficiency.