Google Lens is powered by a combination of computer vision, optical character recognition (OCR), and machine learning technologies. At its core, it uses convolutional neural networks (CNNs) to analyze images and detect objects, text, and patterns. For text recognition, Google Lens integrates OCR capabilities similar to Google’s Tesseract, enhanced with deep learning for higher accuracy across diverse fonts and languages. Additionally, the app uses Google's vast knowledge graph and cloud-based AI services to provide contextual information, such as identifying landmarks or extracting details from scanned documents. These technologies enable Google Lens to perform tasks like real-time translation, product identification, and augmented reality applications.
What is the technology behind Google Lens?
- AI & Machine Learning
- Natural Language Processing (NLP) Basics
- Accelerated Vector Search
- GenAI Ecosystem
- The Definitive Guide to Building RAG Apps with LangChain
- All learn series →
Recommended AI Learn Series
VectorDB for GenAI Apps
Zilliz Cloud is a managed vector database perfect for building GenAI applications.
Try Zilliz Cloud for FreeKeep Reading
What is the difference between federated learning and edge computing?
Federated learning and edge computing are two distinct concepts that address different challenges in data processing and
How do AI agents leverage transfer learning?
AI agents leverage transfer learning by utilizing knowledge gained from one task to improve performance on a different b
What are observability challenges in distributed databases?
Observability in distributed databases refers to the ability to monitor, understand, and troubleshoot system performance