Beam Search
A search algorithm used in sequence generation that keeps track of multiple candidate outputs at each step, selecting the most probable complete sequences rather than greedily choosing one token at a time.
Beam search is widely used in machine translation, text generation, and speech recognition to improve output quality. A beam width of 5 means the algorithm tracks the top 5 candidate sequences at each step. While greedy decoding picks only the single best token at each position, beam search explores multiple paths to find globally better sequences. Larger beam widths improve quality but increase computation linearly, creating a practical trade-off between output quality and inference speed.
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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.
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.
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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.
Generative AI
AI systems that can create new content — text, images, code, audio, video — rather than simply analyzing or classifying existing data. Large language models and diffusion models are the primary architectures.
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