Greedy vs Beam Search

Greedy vs Beam Search: Optimizing AI Sequence Predictions

What it is

Greedy and Beam Search are algorithms for generating sequences in AI, like text or translations. Greedy Search picks the best option at each step, producing quick but potentially suboptimal results. Beam Search explores multiple options simultaneously, balancing quality and computation.

How it works

Greedy Search selects one token per step, always the highest probability, moving forward without reconsideration. Beam Search keeps a fixed number (beam width) of top sequences at each step, expanding and pruning them to find a better overall sequence than greedy alone.

Why it matters

Choosing between these affects AI product quality and performance. Greedy offers faster responses and lower costs but risks lower accuracy. Beam Search improves output quality and user satisfaction, at higher compute and latency, influencing scalability and feasibility choices in product design.