达美航空取消了数百个航班,努力从微软的停机中恢复过来

币界网Pubblicato 2024-07-22Pubblicato ultima volta 2024-07-22

币界网报道:
达美航空公司首席执行官Ed Bastian为数百次航班取消向旅客道歉并提供飞行常客里程,因为该航空公司努力从周五全球范围内的IT中断中恢复过来,这些中断引发了运输部长Pete Buttigieg的批评。根据航空数据公司OAG的数据,这家总部位于亚特兰大的航空公司从周五到周日取消了4600多个航班,比其他任何航空公司都多。截至周一早些时候,达美航空已经取消了另外550个航班,占其主线运营的15%。航班延误和取消使达美航空成为这家航空公司罕见的焦点,该公司的领导者以可靠性和准时性为荣。Buttigieg在周日晚些时候的一份电子邮件声明中表示:“我们继续收到达美航空公司不可接受的中断和客户服务状况的报告,包括向我们部门提交的数百起投诉。”。“我已经向达美明确表示,我们希望该航空公司为因航班中断而选择取消行程的客户提供及时退款”,并“为受延误和取消影响的消费者及时报销食品和过夜酒店住宿费用,并为所有乘客提供足够的客户服务协助”。达美航空的航班中断持续存在,而大多数其他航空公司已经恢复。美国航空公司表示,到周六,情况几乎恢复正常。巴斯蒂安在给客户的一条信息中说:“我想向所有受到这些事件影响的人道歉。”。周日的一份员工备忘录称:“达美航空从事连接世界的业务,我们理解当你的旅行中断时会有多么困难。”该航空公司为空乘人员提供额外工资以轮班。据知情人士透露,运营商用他们的个人手机叫他们进来巴斯蒂安在他的报告中说,在夏季最繁忙的时期之一,高需求促使该航空公司为受影响的旅客寻找替代航班。根据FlightAware的数据,联合航空公司周日的航班中断也有所增加,取消了9%的航班,即260个航班,但仍低于达美航空。达美航空公司有许多微软工具在中断中受到影响,“特别是我们的一个机组人员跟踪相关工具受到影响,无法有效处理系统关闭引发的前所未有的变化,”巴斯蒂安在他的报告中说。这将使这一事件类似于西南航空公司在2022年底遭遇的一个更大规模的问题,当时它连续几天未能从恶劣的冬季天气中恢复过来。网络安全公司Crowdstrike的一次拙劣的软件更新使一些基于Windows的程序瘫痪,也打击了银行和医疗保健行业

Letture associate

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

DeepSeek has updated its DeepSeek V4 model with the DSpark speculative decoding framework, achieving a significant 60-85% speedup in generation for Flash models and 57-78% for Pro models while maintaining the same overall throughput. This engineering-focused update, rather than a core architectural change, introduces DSpark to address latency and throughput bottlenecks in high-concurrency production environments. DSpark combines high-throughput parallel generation with adaptive load-aware verification. Its key innovations include a semi-autoregressive generation architecture to model dependencies within token blocks and a hardware-aware confidence-scheduled verification system. This system uses a confidence head to predict token acceptance probabilities, allowing it to dynamically optimize verification length per request and allocate compute only to tokens with the highest expected payoff. The asynchronous scheduler is designed for real-world deployment, ensuring zero-overhead scheduling and continuous CUDA graph replay while preserving the target model's output distribution. In tests across mathematical reasoning, code generation, and daily dialogue, DSpark outperformed state-of-the-art models like Eagle3 and DFlash, increasing average acceptance length by 26.7%-30.9% and 16.3%-18.4% respectively on Qwen3 target models. DeepSeek also open-sourced DeepSpec, a full-stack codebase for training and evaluating speculative decoding draft models, providing a standardized toolkit that includes data preparation tools, model implementations, training code, and evaluation scripts.

marsbit7 h fa

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

marsbit7 h fa

Trading

Spot
活动图片