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让需求简单一点，心灵就会更轻松一点；让外表简单一点，本色就会更接近一点；让沟通简单一点，情感就会更融洽一点，让过程简单一点，内涵就会更丰富一点；让效率更高一点，成果就会更丰硕一点。
文库
- 1 淘特端侧模型从微调到应用的全链路实践
- 2 从 vmcore 到上游 commit：一次 systemd 事件循环缺陷的完整猎杀
- 3 基于AST与LLM的遗留代码重构：绞杀者模式自动化实践
- 4 3个月用Harness重写90万行旧代码：踩过的坑都在这
- 5 Inside Minerva: building scalable observability for eBay’s monetization platform
- 6 Meta’s Generative Ads Model (GEM): Scaling the Central Model and Compute Engine for Frontier Ads AI
- 7 大表治理之分表实践：带你手搓一个简单的数据库分表组件
- 8 CASTLE: training natural language search before the first real query
- 9 Reliable GPU compute for large training & inference jobs
- 10 Netflix Stratum Media Processing: Automated Container Right-Sizing
- 11 The Lifecycle of LLM-as-a-Judge: Building, Aligning, and Monitoring at scale
- 12 Running Apache Spark experiments in my sleep (and on a plane)
- 13 Netflix Conductor : The Next Chapter
- 14 Behind the Scenes: Evolving Netflix’s Ads Event Pipeline for Live — Part II
- 15 TimeSeries Tiered Storage Journey: Kafka/Flink Streams to Native Cassandra Cold Reads
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