Neural Network
A computing system inspired by biological neural networks, consisting of interconnected layers of nodes (neurons) that process information by adjusting the strength of connections during training.
Neural networks are the fundamental architecture behind modern AI breakthroughs. Transformer-based neural networks, introduced in 2017, power virtually all large language models. The largest neural networks now exceed 1 trillion parameters. Deep neural networks — those with many layers — enable the complex pattern recognition that drives image generation, language understanding, and scientific discovery applications.
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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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