Beam Search is a smart search algorithm used in AI to generate sequences, like translations or text summaries. Instead of exploring every possible outcome, it focuses only on the most promising options (called beams) at each step, striking a balance between speed and quality.
How It Works:
- Scoring Options: The algorithm evaluates all possible next steps and assigns each a score based on how likely it is to fit the overall sequence.
- Selecting the Best: It keeps only the top-scoring options (e.g., the top 3 or 5 beams), ignoring less likely ones.
- Building a Sequence: This process repeats until a complete and coherent output is generated.
Why It Matters:
Beam Search is widely used in tasks like machine translation, text generation, and speech recognition, where it’s important to find results that are both accurate and meaningful. The number of options retained (beam width) affects how thorough or efficient the process is, with larger beams improving quality but requiring more computation.
