Offline navigation is a lifeline for travelers, adventurers, and everyday commuters. We demand speed, accuracy, and the flexibility to tailor routes to our specific needs. For years, OsmAnd has championed powerful, feature-rich offline maps that fit in your pocket. But as maps grew more detailed and user demands for complex routing increased, our trusty A* algorithm, despite its flexibility, started hitting a performance wall. How could we deliver a 100x speed boost without bloating map sizes or sacrificing the deep customization our users love?
FirstFT: the day's biggest stories
。WPS官方版本下载对此有专业解读
At some point I realized the scope was too large. I had spent the most time with msdfgen and hadn’t yet learned enough about the other libraries to write a proper guide. They all worked differently. I kept getting stuck. So I reduced the scope. In redesign 2 I decided to only use msdfgen, but show the various tradeoffs involved (atlas size, antialias width, shader derivatives, smoothing function).
�@Zenbook SORA 14�̐V���f���́ASoC�Ƃ���Snapdragon X2 Elite�𓋍ڂ����B����SoC��NPU�̃s�[�N���\��80TOPS�ŁACopilot+ PC�������B��������32GB�iLPDDR5X�K�i�j�ŁA�X�g���[�W��1TB SSD�iPCI Express 4.0�ڑ��j���B�f�B�X�v���C��1920�~1200�s�N�Z���𑜓x�̗L�@EL�i�ő�60Hz�쓮�j�ƂȂ��B
。关于这个话题,搜狗输入法下载提供了深入分析
正如前面提到,一个强大的 AI agent,强大之处从来不在于知道或者训练过正确答案,而是「在面对没见过的情况时能自主探索出解决路径」,可以理解为一种 0-shot 或 few-shot 实现 SOTA 效果的能力。,更多细节参见safew官方版本下载
Continue reading...