她以前在苏州做瑜伽教练，待了七八年。经济发达的城市房租贵，竞争也大，一条街上能有三四家馆，互相压价。那时候她每天坐一个小时地铁去上课，晚上十点才能到家。赚是赚了一些，但存不下钱，人也累。
摆在车企面前的只有两条路：要么在智驾上完成从“能用”到“好用”的跨越，为用户提供不可替代的价值锚点；要么在愈演愈烈的“价格战”中失去护城河，在销量上继续痛苦承压。
，这一点在WhatsApp Web 網頁版登入中也有详细论述
This approach shares a lot in common with the idea of multivariate interpolation over scattered data. Multivariate interpolation attempts to estimate values at unknown points within an existing data set and is often used in fields such as geostatistics or for geophysical analysis like elevation modelling. We can think of our colour palette as the set of variables we want to interpolate from, and our input colour as the unknown we’re trying to estimate. We can borrow some ideas from multivariate interpolation to develop more effective dithering algorithms.
ArchitectureBoth models share a common architectural principle: high-capacity reasoning with efficient training and deployment. At the core is a Mixture-of-Experts (MoE) Transformer backbone that uses sparse expert routing to scale parameter count without increasing the compute required per token, while keeping inference costs practical. The architecture supports long-context inputs through rotary positional embeddings, RMSNorm-based stabilization, and attention designs optimized for efficient KV-cache usage during inference.