本文讨论了使用Kafka 3.x（KRaft）和Flink 1.20+进行流处理实验的复现步骤，包括环境设置、事件时间与处理时间窗口、Kafka日志解读、事务处理和检查点间隔等内容。实验结果将记录在output/目录中，以确保实验的准确性。

Hardwood, the project Gunnar Morling kick-started to improve the handling of Parquet files in Java, reached version 1. Its multi-threaded approach and zero mandatory external dependencies promise...

Netflix has detailed a cloud-based system for scaling camera file processing across global film and TV workflows. The pipeline handles ingest, validation, metadata extraction, and media...

Uber introduced a high-throughput financial ledger processing system designed to handle hot account write contention at scale. Using 250ms batching, Redis coordination, and optimistic atomic...

Joseph Stein discusses engineering an enterprise AI-as-a-Service platform within a private cloud data center. He explains how to maximize underutilized GPU pools via multi-namespace scheduling,...

The Local-First AI Inference pattern routes 70–80% of documents to deterministic local extraction at zero API cost, reserving Azure OpenAI calls for edge cases and flagging low-confidence results...

Jimmy Morzaria discusses the evolution of Stripe’s database tier to support 5 million QPS with 5.5 nines of reliability. He explains the architecture of DocDB and shares how Stripe leverages a...

Discord open-sourced Osprey, a safety rules engine processing 400 million daily actions and 2.3 million rules per second. Osprey uses a polyglot architecture: a Rust coordinator manages traffic,...

Intelligent document processing (IDP) is an AI-powered technology that extracts,...

How and Why Netflix Built a Real-Time Distributed Graph: Part 1 — Ingesting and Processing Data Streams at Internet ScaleAuthors: Adrian Taruc and James DaltonThis is the first entry of a...

MISP 2025挑战聚焦于复杂声学条件下的会议转录，提出音视频说话者分离与识别任务。参与者通过结合音频和视频模态，显著提升了系统准确率，展示了多模态信息在语音处理中的潜力。

本研究探讨了生成大型语言模型与传统自然语言处理在医疗任务中的差异。分析19123项研究发现，生成模型在开放性任务中表现优越，而传统方法在信息提取和分析中占主导地位。确保技术在医学中的伦理使用至关重要。

本研究利用自然语言处理技术自动提取肺癌和乳腺癌的临床报告信息，解决了手动提取的时间和准确性问题。通过NLP工具uQuery，能够高效识别和分类临床实体，但在处理低频实体时仍面临挑战。

本研究提出了$ ext{B}_2 ext{S}_6$模型，以解决Mamba在长序列任务中的不足。该模型结合块选择动态和通道特定偏差，显著提升了性能，超越了S4和S4D，同时保持了语言建模效果。

Kinesh SatiyaIntroductionIn a digital advertising platform, a robust feedback system is essential for the lifecycle and success of an ad campaign. This system comprises of diverse sub-systems...

本研究针对临床对话数据集稀缺问题，提出了一种新的合成数据集类型学，以分类和评估不同的数据合成方式，从而推动医疗领域对话处理的研究进展。

本研究针对中库尔德语在自然语言处理中的资源不足问题，提出了一种全面的词性标注集，以提升相关任务的表现。该标注集通过整合研究和专家贡献，支持大规模语料库的标注，显著提高了库尔德语处理任务的准确性。