> Most people will both lose time with false-start approaches that are scrapped To a discerning eye this pattern looks like stronger minds implementing higher

> Most people will both lose time with false-start approaches that are scrapped To a discerning eye this pattern looks like stronger minds implementing higher quality tree search[1], either through implementing higher quality neural search heuristics for tree pruning or via greater search depth. Given relative NP-hardness of the problems[2] we are usually dealing with at our line of work and what we know about planning in machines and animals[3], it doesn't look immediately implausible. With planning capability strong enough, one doesn't need trial and error in the real world for moderately complex problems: the plan devised through internal search is good enough to work on the first try. Weaker planners have to compensate by executing more rollouts and using the real world as a ground truth model. 1. https://arxiv.org/abs/1911.08265 https://arxiv.org/abs/1911.08265 2. https://www.microsoft.com/en-us/research/wp-content/uploads/2017/10/program_synthesis_now.pdf https://www.microsoft.com/en-us/research/wp-content/uploads/... 3. https://onlinelibrary.wiley.com/doi/abs/10.1111/ejn.13851 https://onlinelibrary.wiley.com/doi/abs/10.1111/ejn.13851