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When we approach a challenging problem, we brainstorm together about the possible approaches to tackle it, weigh them against evidence, and converge on the strongest solution. We designed Parallel Thinking to bring this same spirit of exploration into AI reasoning. Rather than following a single line of thought, the model generates several trajectories in parallel. A separate system, trained on verifiable problems, then resolves among these possibilities, outputting the final answer. We have integrated Parallel Thinking into Reka Research —our research agent that can browse the web and private documents to answer complex questions—and found that it brings substantial improvements on benchmarks like SimpleQA and Research–Eval . How Parallel Thinking Works At a high level, Parallel Thinking works in two stages: Parallel generation . Given an input prompt, we use the standard version of Reka Research to independently generate N candidate responses in parallel...."},"evidence_pages":[],"related_signals":[{"id":"fb063843-18fc-4913-83b1-fa3ee04c7f69","url":"https://onlylabs.fyi/signals/fb063843-18fc-4913-83b1-fa3ee04c7f69","source_url":"https://reka.ai/news/your-archive-is-a-revenue-engine.-most-broadcasters-are-still-treating-it-like-a-hard-drive","title":"Your Archive Is A Revenue Engine. 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