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This article examines the current state and future prospects of large AI models and inference acceleration, covering technology trends, diverse application scenarios from research to industry, and the challenges and opportunities that lie ahead for intelligent data governance, multimodal agents, and AGI.
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Tencent Cloud’s OCR team cut average response time from 1.8 seconds to under one second and boosted throughput by over 50 % by redesigning the model with self‑attention, accelerating inference with a Tensor‑Network accelerator, shrinking RPC payloads, enabling asynchronous logging, and optimizing multi‑region GPU memory utilization.
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This article describes the design, automated workflow, functional modules, and performance results of a comprehensive AI model optimization platform built for Ctrip's travel business, covering operator libraries, graph optimization, model compression techniques such as distillation, quantization, pruning, and deployment integration.
This article explains how to use NVIDIA TensorRT to accelerate TensorFlow model inference by describing TensorRT architecture, optimization techniques such as layer fusion and precision calibration, detailing the conversion of frozen_graph and saved_model formats, presenting experimental setup and performance comparisons, and summarizing the achieved speed‑up.