Jun 19, 2025 · Artificial Intelligence

Training Neural Networks with Minimal Labeled Data Using Active Learning

This article explains how active learning can dramatically reduce the amount of labeled data required for training deep neural networks by selecting the most informative and representative samples, and provides a complete Python implementation of a hybrid query strategy (DBAL) with ResNet‑18.

DBALPythonResNet18

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Training Neural Networks with Minimal Labeled Data Using Active Learning

Alibaba Cloud Infrastructure

Aug 29, 2018 · Artificial Intelligence

Alibaba's FPGA-Based Ultra‑Low Latency, High‑Throughput Machine Learning Processor

Alibaba unveiled an FPGA‑designed machine‑learning accelerator that achieves sub‑millisecond inference latency and thousands of frames‑per‑second throughput, demonstrating how integrated hardware‑software optimizations can deliver real‑time AI performance surpassing conventional GPU and ASIC solutions.

AI acceleratorFPGAHigh Throughput

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Alibaba's FPGA-Based Ultra‑Low Latency, High‑Throughput Machine Learning Processor