I love this direction of research.

Reducing costs of reasoning is a huge ongoing challenge in LLMs. We're spending so much energy and compute resources today on reasoning that today's consumption rates were unexpected (to me) a short 1 yr ago. We're literally burning forests, the atmosphere and making electricity expensive for everyone.

DeepThink v3.1 made a significant leap in this direction recently -- significantly shorter thinking tokens at the same quality. GPT5's router was also one (important) attempt to reduce reasoning costs and make o3-quality available in the free tier without breaking the bank. This is also why Claude 4 is winning the coding wars against its reasoning peers -- it provides great quality without all the added reasoning tokens.

Getting inspiration from Alpha-go and MCMC literature -- applying tree weighting, prioritization and pruning feels extremely appropriate. (To improve the quality of Deep Think -- offered by Gemini & GPT5 Pro today)

So, yes, more of this please. Totally the right direction.