Convolutional Neural Network (CNN)
A type of neural network designed for processing grid-like data such as images, using convolutional filters to automatically detect patterns like edges, textures, and shapes.
CNNs dominated computer vision from 2012 to 2020, beginning with AlexNet's ImageNet victory. Architectures like ResNet (152 layers) and EfficientNet pushed accuracy to superhuman levels on image classification. CNNs use shared weights and local connectivity to efficiently process high-dimensional visual data. While vision transformers have overtaken CNNs on many benchmarks, CNNs remain widely deployed in edge devices and mobile applications due to their computational efficiency and smaller model sizes.
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Related Terms
Artificial General Intelligence (AGI)
A hypothetical form of AI that can understand, learn, and apply knowledge across any intellectual task at or above human level, rather than being specialized for specific tasks.
AI Alignment
The research field focused on ensuring AI systems behave in accordance with human values and intentions, particularly as systems become more capable.
ChatGPT
OpenAI's conversational AI assistant, launched in November 2022, which catalyzed the current generative AI boom by demonstrating the capabilities of large language models to a mainstream audience.
Fine-Tuning
The process of further training a pre-trained AI model on a specific, smaller dataset to specialize it for a particular task or domain, requiring far less compute than training from scratch.
Foundation Model
A large AI model trained on broad data that can be adapted to a wide range of downstream tasks — examples include GPT-4, Claude, Gemini, and Llama.
Frontier Model
The most capable and advanced AI models at any given time, typically trained with the largest compute budgets and achieving state-of-the-art performance on benchmarks.
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