Artificial intelligence (AI) has made incredible progress, from deciphering the nuances of written language to interpreting the rich complexity of images, videos, and even LiDAR data. This transition has advanced computer vision (CV), enabling machines to “see” and perceive the visual world. Extracting intelligence from visual data is often more intricate than processing text. This is due to factors like the high dimensionality of visual data, occlusion, perspective, and lighting conditions of images, as well as relative complexity in feature extraction. Machine learning (ML) in CV has additional challenges, such as the non-availability of enough relevant images for pre-training, the expensive and time-consuming manual annotating of visual data, and the significantly higher processing power requirements, especially for real-time applications and videos.
AI Foundation Models For Vision Accelerate CV Development
AI foundation models for vision (AI-FMVs) help organizations tackle some of these challenges. They are pre-trained ML models that help ease various downstream visual tasks such as object classification (e.g., ViT), object detection (e.g., DETR), and image segmentation (e.g., SAM). These models have been trained on extensive and varied datasets to capture visual features applicable across various domains. They can accelerate CV-specific application development by:
- Labeling or annotating images for pre-training vision models,
- Adapting AI-FMVs via smart or augmented prompt engineering or fine-tuning AI-FMVs for high precision and task-specific optimizations and
- Using AI-FMVs with zero or few-shot learning for visual tasks.
Additionally, AI-FMVs can empower content creators by generating images and videos at scale (e.g., DALL-E) and enabling more intelligent CV solutions when combined with NLP (e.g., CLIP).
AI-FMVs By Design Power Vertical Solutions
AI-FMVs are used in various vertical use cases. They are often used as “backbones” in the CV model architecture for effective feature extraction, thereby reducing model development time and cost. They also allow transfer learning where the model can adapt to new tasks with minimal additional “head” layer (task-specific) training. Depending on the use cases, foundation models such as CLIP can sometimes be used in a zero-shot manner. The following are a few practical applications:
- In e-commerce, AI-FMVs enable automated product categorization and enhance visual search functionalities. By leveraging such models, businesses can quickly classify products based on images and allow users to search for items using visual inputs rather than text.
- In autonomous driving, AI-FMVs are utilized for image segmentation tasks, which are crucial for identifying and classifying objects on the road, such as pedestrians, vehicles, and traffic signs.
- In healthcare, AI-FMVs are increasingly used to analyze medical images, such as X-rays, MRIs, and CT scans. These models assist in diagnosing diseases by identifying anomalies and patterns in medical images.
- In agriculture, AI-FMVs assist by analyzing aerial images captured by drones or satellites to monitor crop health, identify pests, and optimize resource allocation.
As much as using AI-FMVs has benefits, there are also challenges. These include high memory and computing requirements, real-time application issues, and video-analysis complexities. Academics and tech companies are working to resolve these.
Forrester Can Help You Navigate This Exciting Future
Our newly published report, The Tech Leader’s Primer For AI Foundation Model For Vision, illustrates how organizations can take advantage of this technology and explains how AI-FMVs drive the democratization of CV-related skills within an organization.
Further, our clients can read The State Of Computer Vision Technology, 2024 report to understand how advancements in machine learning, enhanced computing power on devices like smartphones, and increased data availability have accelerated the adoption of CV-powered applications. Clients can also connect with me through an inquiry or guidance session to discuss how to grow their business with CV solutions or other associated topics.
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