Example mobile template:
blacksky-algorithms/rsky。关于这个话题，新收录的资料提供了深入分析
。新收录的资料对此有专业解读
第二类是按账号（seats）付费的定价，这感觉很公平，但账号（seats）并没有绑定到某个结果上。比如Workday有这样一个很棒的定价模型，由于你有34万名员工，我就按每人每月向你收费。为什么收费？我不知道，只是觉得这样公平。但是GE的那些员工并不是在使用Workday来产出成果。我觉得Workday挺好的，这其实涉及到你可以用AI工具做什么。比如在GE招聘员工时，HR必须去查看Workday中的文件并致电那三家前司来进行背景调查，确保候选人的履历真实。但AI工具完全可以做到致电公司这一点，前提是你必须是核心业务系统。目前IT领域下跌了45%，但没有人会弃用QuickBooks。这两个支柱就是按账号（seats）计费且与某种工作量挂钩，账号（seats）只是一种聪明的定价策略。
Let’s examine the math heatmap first. Starting at any layer, and stopping before about layer 60 seem to improves the math guesstimate scores, as shown by the large region with a healthy red blush. Duplicating just the very first layers (the tiny triangle in the top left), messes things up, as does repeating pretty much any of the last 20 layers (the vertical wall of blue on the right). This is more clearly visualised in a skyline plot (averaged rows or columns), and we can see for the maths guesstimates, the starting position of the duplication matters much less. So, the hypothesis that ‘starting layers’ encode tokens, to a smooth ‘thinking space’, and then finally a dedicated ‘re-encoding’ system seem to be somewhat validated.，这一点在新收录的资料中也有详细论述