AI engineering

Every Future Product Will Be a Living System: Ronak Malde on Continual Learning

Ronak Malde, CEO of Trajectory.ai, argues that static AI models are insufficient for enterprise use cases like legal or finance—every future product must be a living system that learns continuously. He details how they achieve this with concurrent training jobs, Self-Distillation Policy Optimization, and open-sourced infrastructure.

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PP-OCRv6: Lightweight, Multilingual OCR from 1.5M to 34.5M Parameters

PP-OCRv6 is a practical, tiered OCR model family from 1.5M to 34.5M parameters that improves detection and recognition accuracy over its predecessor while supporting 50 languages in a single architecture. It's worth reading if you need a lightweight, deployable OCR pipeline that integrates with Paddle Inference, Transformers, or ONNX Runtime backends.

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Improving Ray Serve LLM on GKE: 5x Throughput, 8x Latency

If you've ever struggled with the performance tax of using Ray Serve for LLM inference on Kubernetes, this article details three concrete architectural fixes—HAProxy integration, direct token streaming, and a v2 vLLM executor—that deliver up to 5x higher throughput and 8x lower latency on GKE, closing the gap with native vLLM without sacrificing developer experience.

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Google Cloud Network Insights: Active monitoring for cross-cloud visibility

Google Cloud has launched Cloud Network Insights in partnership with Broadcom AppNeta, a native observability tool that uses active synthetic probing to monitor network performance and digital experience across multi-cloud and hybrid environments. It integrates directly with Cloud Monitoring and Gemini Cloud Assist, helping teams pinpoint bottlenecks rapidly.

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