Tagged articles

deep learning

1283 articles · Page 11 of 13

Jun 20, 2019 · Artificial Intelligence

Unlock Cutting-Edge Voice AI: Highlights from Alibaba’s Speech & Signal Processing eBook

This article introduces Alibaba's new e‑book collection of five ICASSP‑accepted papers that showcase advances in speech recognition, synthesis, and emotion detection, detailing novel models like DFSMN, A‑LSTM, and speaker‑adaptation techniques that dramatically improve speed, size, and accuracy.

AI voiceEmotion RecognitionICASSP

0 likes · 6 min read

Unlock Cutting-Edge Voice AI: Highlights from Alibaba’s Speech & Signal Processing eBook

Alibaba Cloud Developer

Jun 12, 2019 · Artificial Intelligence

How YOLOv3 Boosts Video Content Advertising on Youku: A Real‑World Case Study

By integrating YOLOv3 video object detection into Youku’s ad platform, the team replaced traditional subtitle‑based and scene‑based placements with precise object‑level targeting, achieving higher relevance, expanded inventory, and a 20% click‑through increase despite 3.5× higher exposure.

Object DetectionYOLOv3computer vision

0 likes · 14 min read

How YOLOv3 Boosts Video Content Advertising on Youku: A Real‑World Case Study

Alibaba Cloud Developer

Jun 12, 2019 · Artificial Intelligence

How Alibaba’s PAISoar Accelerates Deep Learning: 101× Speedup on 128 GPUs

Alibaba engineers detail the PAISoar distributed training framework, showing how RDMA‑optimized hardware, Ring AllReduce algorithms, and user‑friendly APIs boost deep‑learning models—like the GreenNet CNN—to 101‑fold speedups on 128 GPUs, dramatically reducing training time from days to under a day.

AI InfrastructureDistributed TrainingGPU acceleration

0 likes · 17 min read

How Alibaba’s PAISoar Accelerates Deep Learning: 101× Speedup on 128 GPUs

Tencent Cloud Developer

Jun 5, 2019 · Artificial Intelligence

Tencent Cloud OCR Technology: Principles, Challenges, and Industry Applications

Tencent Cloud OCR leverages deep‑learning‑based text detection and recognition, including Compact Inception and multi‑layer RNN refinements, to overcome challenges such as complex backgrounds, low resolution, and multilingual layouts, delivering over 90% accuracy for ID cards, bank cards, business licenses, handwritten text, and powering fast, cost‑saving applications in logistics, QQ, and WeChat Work.

OCROptical Character RecognitionTencent Cloud

0 likes · 7 min read

Tencent Cloud OCR Technology: Principles, Challenges, and Industry Applications

Alibaba Cloud Developer

Jun 5, 2019 · Artificial Intelligence

Tracing the Evolution of Language Models: From N‑grams to GPT‑2

This article reviews the historical development of natural language processing language models, covering expert rule‑based systems, statistical n‑grams, smoothing techniques, neural network models such as NNLM, RNN, word2vec, GloVe, ELMo, and the transformer‑based breakthroughs of GPT, BERT and GPT‑2, and summarizes their impact on modern NLP tasks.

BERTGPTNLP

0 likes · 25 min read

Tracing the Evolution of Language Models: From N‑grams to GPT‑2

Youku Technology

May 29, 2019 · Artificial Intelligence

Youku Video Enhancement and Super-Resolution Competition Announcement

The Youku Video Enhancement and Super‑Resolution Challenge invites teams to develop models that restore low‑resolution, noisy video to high‑definition quality using a 10,000‑pair industry dataset, offering up to RMB 100,000 in prizes and a recruitment pathway, with registration open through June 16 and competition phases spanning May to September.

AI competitionYoukucomputer vision

0 likes · 10 min read

Youku Video Enhancement and Super-Resolution Competition Announcement

Alibaba Cloud Developer

May 27, 2019 · Artificial Intelligence

From Neurons to BERT: Tracing the Evolution of Deep Learning in NLP

This article walks through the development of deep learning for natural language processing, starting with basic neural cells and shallow networks, then exploring CNNs, RNNs, LSTMs, TextCNN, ESIM, ELMo, and culminating with the Transformer‑based BERT model, its training objectives, fine‑tuning strategies, and performance comparisons.

BERTCNNNLP

0 likes · 19 min read

From Neurons to BERT: Tracing the Evolution of Deep Learning in NLP

Liulishuo Tech Team

May 24, 2019 · Artificial Intelligence

Grammatical Error Correction (GEC): Definition, Challenges, Evaluation, and Solutions

This article introduces Grammatical Error Correction (GEC), explains its main error categories, outlines four key challenges, reviews evaluation metrics and the evolution of NLP approaches, and showcases practical solutions and product applications developed by Liulishuo.

Grammatical Error CorrectionNLPdeep learning

0 likes · 11 min read

Grammatical Error Correction (GEC): Definition, Challenges, Evaluation, and Solutions

Beike Product & Technology

May 23, 2019 · Artificial Intelligence

Practical Applications and Challenges of Machine Learning and AI at QCon Beijing 2019

At QCon Beijing 2019, four Beike technology experts presented the practical use and challenges of machine learning for user profiling, deep‑learning‑based house‑quality scoring, intelligent customer‑service systems, and AI‑driven floor‑plan generation, summarizing the architecture, data pipelines, model evolution, and future improvement directions.

AIGaNNLP

0 likes · 16 min read

Practical Applications and Challenges of Machine Learning and AI at QCon Beijing 2019

Architects Research Society

May 21, 2019 · Artificial Intelligence

Differences Between Machine Learning, Data Science, AI, Deep Learning, and Statistics

This article explains the various roles of data scientists, compares data science with machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics, and clarifies the distinctions and overlaps among these fields.

Artificial IntelligenceData Sciencedeep learning

0 likes · 13 min read

Differences Between Machine Learning, Data Science, AI, Deep Learning, and Statistics

Youku Technology

May 20, 2019 · Artificial Intelligence

Youku Video Enhancement and Super‑Resolution Competition Overview

The Youku Video Enhancement and Super‑Resolution Competition challenges teams of up to five to develop 4× upscaling models that also remove noise and compression artifacts, using a 10,000‑pair dataset, with prizes up to ¥100,000 and recruitment opportunities, running from May to September 2019.

AI competitionYoukucomputer vision

0 likes · 9 min read

Youku Video Enhancement and Super‑Resolution Competition Overview

Architects Research Society

May 19, 2019 · Artificial Intelligence

Artificial Intelligence vs. Machine Learning: Definitions, History, and Key Concepts

This article explains the historical development, definitions, and relationship between artificial intelligence and machine learning, highlighting key milestones, foundational concepts such as deep learning and neural networks, and their modern applications across industries.

Artificial Intelligencedeep learninghistory

0 likes · 11 min read

Artificial Intelligence vs. Machine Learning: Definitions, History, and Key Concepts

HomeTech

May 15, 2019 · Artificial Intelligence

How to Build a Deep Learning Model to Predict Workdays from Attendance Data

This article walks beginners through the fundamentals of artificial intelligence, machine learning, and deep learning, using a real‑world attendance dataset to illustrate how to label data, construct a simple linear model, and expand it into a neural network for workday prediction.

Artificial Intelligenceattendance predictiondeep learning

0 likes · 9 min read

How to Build a Deep Learning Model to Predict Workdays from Attendance Data

360 Tech Engineering

May 10, 2019 · Artificial Intelligence

Distributed Training with MXNet: Data Parallel on Single and Multi‑Node GPUs and Integration with Kubeflow

This article explains how MXNet supports data‑parallel training on single‑machine multi‑GPU and multi‑machine multi‑GPU setups, describes KVStore modes, outlines the worker‑server‑scheduler architecture, and shows how to launch large‑scale distributed training using Kubeflow and the mxnet‑operator.

Data ParallelDistributed TrainingKubeflow

0 likes · 11 min read

Distributed Training with MXNet: Data Parallel on Single and Multi‑Node GPUs and Integration with Kubeflow

Alibaba Cloud Developer

May 7, 2019 · Artificial Intelligence

What Makes Alibaba’s MNN Engine a Game-Changer for Mobile AI Inference?

Alibaba’s open‑source MNN is a lightweight, high‑performance deep‑learning inference engine optimized for edge devices, supporting multiple model formats and backends, offering portability across iOS, Android, and IoT, with detailed architecture, performance benchmarks, roadmap, and real‑world application examples.

Edge AIMNNPerformance Optimization

0 likes · 12 min read

What Makes Alibaba’s MNN Engine a Game-Changer for Mobile AI Inference?

Architecture Digest

May 6, 2019 · Artificial Intelligence

Deep Learning Practices in Meituan O2O Service Search

The article details Meituan's large‑scale O2O search platform, describing its current coverage, challenges such as heterogeneous POI data and user intent diversity, and the deep‑learning‑driven solutions—including intelligent matching, business recognition, component analysis, semantic models, real‑time features, and future personalization directions.

AIMeituandeep learning

0 likes · 14 min read

Deep Learning Practices in Meituan O2O Service Search

Hulu Beijing

Apr 30, 2019 · Artificial Intelligence

How Can Deep Neural Networks Be Accelerated and Compressed? Key Techniques Explained

This article reviews why deep neural networks are over‑parameterized, outlines the challenges of deploying them on mobile and embedded devices, and presents six major strategies—pruning, low‑rank approximation, filter selection, quantization, knowledge distillation, and novel architecture design—to accelerate and compress models while preserving performance.

deep learningknowledge distillationmodel acceleration

0 likes · 11 min read

How Can Deep Neural Networks Be Accelerated and Compressed? Key Techniques Explained

Youku Technology

Apr 29, 2019 · Artificial Intelligence

Precise and Fast Object Segmentation Algorithms – Talk by Ren Haibing (Youku Cognitive Lab)

Ren Haibing’s Youku Cognitive Lab talk reviews object segmentation’s motivation, explains semantic and instance concepts, presents UNet‑based and category‑agnostic methods—including fast video segmentation with motion cues—and reports high IoU results while outlining future edge‑aware, label‑free, and non‑online video segmentation research directions.

AIcategory-agnosticcomputer vision

0 likes · 19 min read

Precise and Fast Object Segmentation Algorithms – Talk by Ren Haibing (Youku Cognitive Lab)

Architects' Tech Alliance

Apr 27, 2019 · Fundamentals

Why GPUs Outperform CPUs: Core Parameters and Architecture Explained

This article explains the fundamental differences between CPUs and GPUs, outlines key GPU specifications such as CUDA cores, memory capacity, bandwidth, and floating‑point precision, and reviews NVIDIA's major GPU series and architectural evolution for high‑performance and AI workloads.

CPUNVIDIAdeep learning

0 likes · 11 min read

Why GPUs Outperform CPUs: Core Parameters and Architecture Explained

Hulu Beijing

Apr 25, 2019 · Artificial Intelligence

How to Build End-to-End Deep Learning Models for Self-Driving Cars

This article reviews the evolution of autonomous‑driving research, explains how to design end‑to‑end deep‑neural‑network models such as PilotNet, and outlines a reinforcement‑learning based decision system, highlighting key architectures, performance metrics, and future challenges.

Autonomous DrivingEnd-to-EndPilotNet

0 likes · 9 min read

How to Build End-to-End Deep Learning Models for Self-Driving Cars

HomeTech

Apr 25, 2019 · Artificial Intelligence

An Introduction to Artificial Intelligence: Basics, Applications, and How to Get Started

This article provides a beginner-friendly overview of artificial intelligence, explaining its core concepts, the relationship between AI, machine learning and deep learning, common real-world applications such as search and recommendation, and practical steps and resources for newcomers to start learning AI with Python and basic statistics.

AIData SciencePython

0 likes · 8 min read

An Introduction to Artificial Intelligence: Basics, Applications, and How to Get Started

Tencent Cloud Developer

Apr 24, 2019 · Artificial Intelligence

Chinese Text Sentiment Classification Using Multi‑layer LSTM: Data Preparation, Model Architecture, and Business Applications

The article details a practical workflow for Chinese sentiment classification in Tencent’s Goose Man product, covering data preparation, word‑segmentation challenges, a six‑layer multi‑LSTM architecture with word embeddings, training results achieving roughly 96 % accuracy, and its deployment for automatic detection of misleading and high‑impact user reviews.

Chinese NLPKerasLSTM

0 likes · 23 min read

Chinese Text Sentiment Classification Using Multi‑layer LSTM: Data Preparation, Model Architecture, and Business Applications

Hulu Beijing

Apr 22, 2019 · Artificial Intelligence

How Has Speech Recognition Evolved from Traditional Methods to Modern Deep Learning?

This article reviews the fundamentals of automatic speech recognition, compares traditional MFCC‑GMM‑HMM pipelines with modern deep neural network approaches such as DNN‑HMM, LSTM‑CTC, and attention‑based models, and illustrates each evolution step with flowchart diagrams and key references.

ASRCTCDNN

0 likes · 11 min read

How Has Speech Recognition Evolved from Traditional Methods to Modern Deep Learning?

JD Tech Talk

Apr 19, 2019 · Artificial Intelligence

Fundamentals and Practical Applications of Text Mining: Workflow, Methods, and a Sentiment Analysis Case Study

This article outlines the end‑to‑end text‑mining workflow—from data acquisition and preprocessing to feature extraction, algorithm selection, and model evaluation—while demonstrating a sentiment‑analysis case study that combines LDA topic modeling with deep‑learning classifiers.

LDANatural Language ProcessingSentiment Analysis

0 likes · 11 min read

Fundamentals and Practical Applications of Text Mining: Workflow, Methods, and a Sentiment Analysis Case Study

Sohu Tech Products

Apr 17, 2019 · Artificial Intelligence

CTR Estimation in Recommendation Systems: From Logistic Regression to Deep & Cross Networks

This article reviews the evolution of click‑through‑rate (CTR) estimation models for recommendation ranking, covering logistic regression, feature‑engineering tricks, factorization machines, deep neural networks, wide‑and‑deep architectures, and the Deep & Cross Network, while discussing their strengths, limitations, and future research directions.

CTRcross networkdeep learning

0 likes · 14 min read

CTR Estimation in Recommendation Systems: From Logistic Regression to Deep & Cross Networks

Tencent Cloud Developer

Apr 16, 2019 · Artificial Intelligence

Building Image Recognition Systems: From Basics to Advanced AI Techniques

This article summarizes a computer‑vision salon where Dr. Ji Yongnan explains imaging pipelines, traditional feature‑based methods, deep‑learning breakthroughs, Tencent Cloud AI services, real‑world case studies, and answers audience questions about machine‑vision versus computer‑vision and data‑scarcity challenges.

AI applicationsObject Detectioncomputer vision

0 likes · 18 min read

Building Image Recognition Systems: From Basics to Advanced AI Techniques

Hulu Beijing

Apr 16, 2019 · Artificial Intelligence

How Deep Learning Transforms Network Bandwidth Prediction: From RNN to CNN‑RNN Hybrids

This article explores how deep learning techniques such as RNN, LSTM, 3D‑CNN, and CNN‑RNN hybrids can be applied to predict network bandwidth and traffic, comparing traditional time‑series methods with modern AI approaches and highlighting the potential of graph neural networks for future improvements.

CNNNetwork TrafficRNN

0 likes · 9 min read

How Deep Learning Transforms Network Bandwidth Prediction: From RNN to CNN‑RNN Hybrids

MaGe Linux Operations

Apr 15, 2019 · Artificial Intelligence

How to Build a Breast Cancer Prediction Neural Network from Scratch in Python

This article walks through creating a Python‑based neural network to predict breast cancer using the Wisconsin dataset, covering network architecture, weight and bias initialization, back‑propagation, gradient descent, and the role of activation functions such as sigmoid, tanh, ReLU and Leaky ReLU.

Neural NetworkPythonactivation functions

0 likes · 13 min read

How to Build a Breast Cancer Prediction Neural Network from Scratch in Python

Alibaba Cloud Developer

Apr 15, 2019 · Artificial Intelligence

Why Deep Learning Finally Succeeded and What Challenges Lie Ahead

This article reviews Jia Yangqing’s insights on why deep learning finally succeeded—highlighting the roles of big data and high‑performance computing—while examining its current limitations, emerging challenges, and future opportunities across AI engineering, AutoML, and hardware‑software co‑design.

AI ChallengesAI EngineeringAutoML

0 likes · 9 min read

Why Deep Learning Finally Succeeded and What Challenges Lie Ahead

Sohu Tech Products

Apr 11, 2019 · Artificial Intelligence

Media Domain Named Entity Recognition: Techniques, Evolution, and Sohu’s Practical Implementation

This article reviews the challenges of media‑domain named entity recognition, outlines the evolution from rule‑based methods through traditional machine‑learning and deep‑learning models to attention‑based Transformers, and details Sohu’s practical Bi‑LSTM‑CRF system with data‑annotation strategies and performance results.

Bi-LSTMCRFNER

0 likes · 12 min read

Media Domain Named Entity Recognition: Techniques, Evolution, and Sohu’s Practical Implementation

Hulu Beijing

Apr 11, 2019 · Artificial Intelligence

Optimizing Real-Time Ad Bidding with Reinforcement Learning: A Deep Dive

This article explains how real‑time bidding works in computational advertising, defines the budget‑constrained bidding problem, models it with reinforcement learning, and presents a deep‑network implementation together with visual analysis and key references.

Advertisingbudget optimizationdeep learning

0 likes · 6 min read

Optimizing Real-Time Ad Bidding with Reinforcement Learning: A Deep Dive

Hulu Beijing

Apr 10, 2019 · Artificial Intelligence

Designing Deep Learning Models for Item Similarity in Recommendation Systems

This article explains how to build both unsupervised and supervised deep‑learning models that compute item similarity from user behavior, covering prod2vec embeddings, skip‑gram architectures, loss function design, and practical training steps for modern recommender systems.

This article introduces Alibaba’s intelligent matting editor and its Semantic Human Matting (SHM) algorithm, detailing the integration of semantic segmentation and deep matting networks, the fusion module, training strategy, experimental results, and the deployment of an online fully‑automatic cutout tool for designers.

AlibabaSemantic Segmentationautomatic cutout

0 likes · 16 min read

How Alibaba’s Semantic Human Matting Achieves Fully Automatic High‑Precision Image Cutouts

Xianyu Technology

Feb 27, 2019 · Artificial Intelligence

UI2CODE: Layout Analysis and Background/Foreground Extraction for UI Images

The UI2CODE system tackles UI layout analysis by first extracting backgrounds with Sobel, Laplacian and Canny edge detection plus a flood‑fill algorithm, then isolating foreground components through connected‑component analysis and a Faster R‑CNN classifier, and finally fusing both pipelines to achieve superior precision, recall and IoU on Xianyu app screenshots.

Faster R-CNNUI2Codecomputer vision

0 likes · 16 min read

UI2CODE: Layout Analysis and Background/Foreground Extraction for UI Images

58 Tech

Feb 22, 2019 · Artificial Intelligence

Algorithm Evolution and Implementation of 58.com Intelligent QABot for Business Consultation

The article details the design and iterative improvement of 58.com’s intelligent QABot, covering knowledge‑base construction, feature engineering, three generations of classification models—including FastText, Bi‑LSTM, and deep semantic matching—and evaluation metrics that achieve high accuracy and automation rates.

AIIntelligent Customer ServiceNatural Language Processing

0 likes · 12 min read

Algorithm Evolution and Implementation of 58.com Intelligent QABot for Business Consultation

Alibaba Cloud Developer

Feb 21, 2019 · Artificial Intelligence

How Alibaba Uses AI to Automatically Find High‑Quality Buyer Photos on Taobao

This article explains how Alibaba’s algorithm team tackles the massive challenge of extracting high‑quality buyer‑generated images from Taobao by combining statistical features, GBDT classification, deep CNN visual assessment, aesthetic scoring, and dirty‑data filters to improve content moderation efficiency.

AIUGCcontent moderation

0 likes · 12 min read

How Alibaba Uses AI to Automatically Find High‑Quality Buyer Photos on Taobao

Architects Research Society

Feb 9, 2019 · Artificial Intelligence

Introduction to TensorFlow and Building a Simple Neural Network for Image Classification

This article introduces TensorFlow, explains when neural networks are appropriate, outlines the general workflow for solving image‑based problems, and provides a step‑by‑step Python implementation of a multilayer perceptron that classifies handwritten digits, while also discussing TensorFlow's strengths, limitations, and alternatives.

PythonTensorFlowdeep learning

0 likes · 14 min read

Introduction to TensorFlow and Building a Simple Neural Network for Image Classification

Architects' Tech Alliance

Feb 3, 2019 · Fundamentals

Understanding GPUDirect RDMA: Principles, Implementation, and Performance

This article explains the background of GPU communication, introduces DMA and RDMA fundamentals, describes how GPUDirect RDMA enables direct GPU-to-GPU memory access across machines, and presents performance results showing reduced latency and increased bandwidth for distributed deep‑learning training.

GPU communicationGPUDirectInfiniBand

0 likes · 7 min read

Understanding GPUDirect RDMA: Principles, Implementation, and Performance

JD Tech

Feb 2, 2019 · Artificial Intelligence

Improved Selective Refinement Network (ISRN): JD AI’s State‑of‑the‑Art Face Detection Achieves Top Rankings on WIDER FACE

JD AI Research Institute introduced the Improved Selective Refinement Network (ISRN), a face‑detection model that outperforms all competitors on the WIDER FACE benchmark across Easy, Medium, and Hard subsets with AP scores of 96.3%, 95.4% and 90.3%, thanks to novel training strategies, COCO pre‑training, redesigned input modules, and multi‑stage classification‑regression enhancements.

Face DetectionISRNJD AI

0 likes · 8 min read

Improved Selective Refinement Network (ISRN): JD AI’s State‑of‑the‑Art Face Detection Achieves Top Rankings on WIDER FACE

Architects' Tech Alliance

Feb 1, 2019 · Industry Insights

How GPUDirect P2P Boosts Multi‑GPU Performance and What Limits It in Virtualized Environments

This article explains the background of GPU communication, details NVIDIA's GPUDirect and its Peer‑to‑Peer features, discusses virtualization challenges, and presents performance measurements on an Alibaba Cloud GN5 instance showing latency reduction and near‑linear scaling for deep‑learning workloads.

GPU communicationGPUDirectNVLink

0 likes · 6 min read

How GPUDirect P2P Boosts Multi‑GPU Performance and What Limits It in Virtualized Environments

Alibaba Cloud Developer

Feb 1, 2019 · Artificial Intelligence

How an Automatic Pipeline Framework Supercharges AI Inference in Retail Surveillance

This article explains how Alibaba's automatic task‑pipeline system transforms deep‑learning inference for retail video streams by decoupling model execution from scheduling, using Python‑based pipelines, high‑performance shared memory, and robust fault‑tolerance, achieving up to 13% faster processing and double the camera capacity.

AI PipelinePerformance OptimizationPython

0 likes · 22 min read

How an Automatic Pipeline Framework Supercharges AI Inference in Retail Surveillance

21CTO

Jan 28, 2019 · Artificial Intelligence

Why Deep Learning Is the Paradigm Shift Shaping the AI Era

The article traces AI’s origins from the 1956 Dartmouth conference, explains how deep learning has become the driving force behind modern AI applications, discusses the need for a mindset shift, lifelong learning, and strategic adaptation to stay relevant in the rapidly evolving intelligent era.

This article provides a comprehensive, step‑by‑step explanation of the Transformer architecture, covering its encoder‑decoder structure, self‑attention, multi‑head attention, positional encoding, residual connections, and training processes, illustrated with diagrams and code snippets to aid readers new to neural machine translation.

Multi-Head AttentionNeural Machine TranslationPositional Encoding

0 likes · 16 min read

Understanding the Transformer Model: Attention, Self‑Attention, and Multi‑Head Mechanisms

Alibaba Cloud Developer

Jan 9, 2019 · Artificial Intelligence

Master Deep Learning Foundations and 14 Cutting-Edge Recommendation Models

This article introduces core deep‑learning architectures—including MLP, RNN, CNN, auto‑encoders, and RBM—explains common activation and loss functions, and then surveys fourteen influential deep‑learning‑based recommendation algorithms such as FM, wide&deep, deepFM, NCF, GBDT+LR, seq2seq and YouTube DNN, complete with model diagrams and reference links.

AIdeep learningmachine learning

0 likes · 18 min read

Master Deep Learning Foundations and 14 Cutting-Edge Recommendation Models

iQIYI Technical Product Team

Jan 4, 2019 · Artificial Intelligence

Building a Deep Learning Training Platform on Cloud: Challenges, Runonce Service, and Storage Optimization

iQIYI built a cloud‑based deep‑learning training platform called Jarvis, replacing the initial Runonce service, by containerizing GPU tasks, adopting Ceph S3 storage with FUSE, optimizing data pipelines, and addressing compute, storage, and networking challenges to improve scalability and reduce GPU idle time.

GPU computingai-trainingcloud platform

0 likes · 9 min read

Building a Deep Learning Training Platform on Cloud: Challenges, Runonce Service, and Storage Optimization

iQIYI Technical Product Team

Jan 4, 2019 · Artificial Intelligence

NLP-based Text Opinion Extraction and Sentiment Analysis for iQIYI Video Comments

iQIYI’s NLP pipeline—combining CRF‑based segmentation, bidirectional LSTM/GRU models with attention and a CNN classifier—automatically extracts opinion targets, sentiment words and polarity from unstructured video comments, aggregates them across users to reveal collective attitudes toward actors, plot, and visual effects, and guides future work on implicit opinions and broader sentiment domains.

NLPOpinion Miningdeep learning

0 likes · 12 min read

NLP-based Text Opinion Extraction and Sentiment Analysis for iQIYI Video Comments

Alibaba Cloud Developer

Dec 21, 2018 · Artificial Intelligence

X-DeepLearning: Alibaba’s Open‑Source Framework for Large‑Scale Sparse Deep Learning

Alibaba's X‑DeepLearning (XDL) is an open‑source deep‑learning framework optimized for high‑dimensional sparse data, offering industrial‑grade distributed training, built‑in CTR/recommendation algorithms, structured compression, and online learning capabilities, with benchmark results demonstrating superior scalability and performance.

CTR predictionDistributed TrainingSparse Data

0 likes · 18 min read

X-DeepLearning: Alibaba’s Open‑Source Framework for Large‑Scale Sparse Deep Learning

Ctrip Technology

Dec 19, 2018 · Artificial Intelligence

Anomaly Detection in Operations: From Statistical Rules to Deep Learning with LSTM and Real‑Time Streaming

This article describes how a large‑scale operations monitoring system at Ctrip evolved from rule‑based alerts to a deep‑learning‑driven anomaly detection pipeline using LSTM models and Flink streaming, achieving a ten‑fold reduction in alert volume while improving fault detection.

FlinkLSTManomaly detection

0 likes · 14 min read

Anomaly Detection in Operations: From Statistical Rules to Deep Learning with LSTM and Real‑Time Streaming

Alibaba Cloud Developer

Dec 19, 2018 · Artificial Intelligence

How Cross‑Domain Embedding Boosts New User Recommendations in Alibaba’s Ecosystem

This article explains the design of a Cross‑Domain Embedding (CSDE) method that transfers Alipay user features to Taobao representations, details its learning and adaptive prediction stages, and shows experimental and online results demonstrating significant conversion‑rate improvements for new and inactive users.

GaNUser Representationconversion rate prediction

0 likes · 15 min read

How Cross‑Domain Embedding Boosts New User Recommendations in Alibaba’s Ecosystem

iQIYI Technical Product Team

Dec 14, 2018 · Industry Insights

How AI Is Transforming Video Entertainment: iQIYI’s Strategic Innovations

The article analyzes how iQIYI leverages deep learning, dynamic frame interpolation, personalized content features, and AI-driven heat metrics to reshape video streaming, improve traffic prediction, and gain a competitive edge in the rapidly evolving entertainment industry.

AIVideo Streamingcontent personalization

0 likes · 8 min read

How AI Is Transforming Video Entertainment: iQIYI’s Strategic Innovations

Architects' Tech Alliance

Dec 13, 2018 · Fundamentals

Intel Unveils Sunny Cove 10 nm CPU Architecture and Foveros 3D Stacking Technology at Architecture Day 2018

At Intel Architecture Day 2018 the company announced its next‑generation Sunny Cove micro‑architecture built on 10 nm, detailed its roadmap through 2021, introduced the 3D‑stacking Foveros technology, previewed new integrated and discrete GPUs, and launched a deep‑learning reference stack for AI developers.

10nm3D stackingFoveros

0 likes · 12 min read

Intel Unveils Sunny Cove 10 nm CPU Architecture and Foveros 3D Stacking Technology at Architecture Day 2018

37 Interactive Technology Team

Dec 13, 2018 · Artificial Intelligence

A 2‑Channel CNN Method for Automatic Game Asset Tag Generation and Similarity Recommendation

The paper introduces an improved two‑channel CNN, built on a shared VGG16 backbone and a hinge‑loss metric, to automatically generate numeric tags for game advertising assets by learning content and style similarity, achieving over 97% test accuracy and enabling efficient ad placement and asset management.

2-channel networkCNNGame Advertising

0 likes · 14 min read

A 2‑Channel CNN Method for Automatic Game Asset Tag Generation and Similarity Recommendation

Tencent Cloud Developer

Dec 13, 2018 · Artificial Intelligence

Everything you need to know about AutoML and Neural Architecture Search

AutoML and Neural Architecture Search automate deep‑learning model design by using controller networks to explore and evaluate candidate architectures, with efficient variants like PNAS and ENAS reducing cost, while platforms such as Google Cloud AutoML and open‑source AutoKeras make these techniques accessible, promising broader, democratized AI breakthroughs.

AutoMLENASGoogle Cloud

0 likes · 7 min read

Everything you need to know about AutoML and Neural Architecture Search

Tencent Cloud Developer

Dec 11, 2018 · Artificial Intelligence

Everything You Need to Know About AutoML and Neural Architecture Search

AutoML and Neural Architecture Search automate deep‑learning model design by sampling and training network blocks, using reinforcement‑learning or efficient weight‑sharing strategies such as PNAS and ENAS, enabling high‑accuracy architectures in days on a single GPU, with services like Google Cloud AutoML and open‑source tools like AutoKeras, while future research aims to expand search spaces beyond hand‑crafted blocks.

AutoMLENASNAS

0 likes · 9 min read

DataFunTalk

Dec 11, 2018 · Artificial Intelligence

Multi-Task Learning in Natural Language Processing

An in‑depth overview of multi‑task learning for natural language processing is presented, covering deep learning foundations, challenges, various multi‑task learning paradigms (hard, soft, shared‑private, function‑level, hierarchical, and search‑based sharing), benchmark platforms, and future research directions, illustrated with numerous diagrams.

NLPdeep learning

0 likes · 15 min read

Multi-Task Learning in Natural Language Processing

DataFunTalk

Dec 8, 2018 · Artificial Intelligence

Analysis of YouTube’s Deep Neural Network–Based Recommendation System

The article examines YouTube’s large‑scale recommendation system, detailing its deep‑learning architecture, the challenges of scale, freshness and noise, and the design choices in candidate generation, ranking, data collection, and evaluation that together deliver over 70% of user watch time.

YouTubedeep learning

0 likes · 10 min read

Analysis of YouTube’s Deep Neural Network–Based Recommendation System

Tencent Cloud Developer

Dec 5, 2018 · Artificial Intelligence

19 AI Technologies That Are Currently Dominating

The article surveys the nineteen leading AI technologies—from natural language generation and speech recognition to digital twins and marketing automation—detailing their core functions, common use cases such as customer service, security, content creation, and the key vendors delivering each solution.

AI TechnologiesArtificial IntelligenceNatural Language Processing

0 likes · 17 min read

19 AI Technologies That Are Currently Dominating

Alibaba Cloud Developer

Nov 30, 2018 · Artificial Intelligence

How Multi‑Source Pointer Networks Transform E‑Commerce Product Title Generation

This article presents a multi‑source pointer network approach for generating concise, brand‑preserving product short titles in e‑commerce, detailing problem formalization, model architecture, extensive offline and online experiments, and demonstrating significant improvements over traditional truncation and seq2seq baselines.

Text Summarizationdeep learninge-commerce

0 likes · 16 min read

How Multi‑Source Pointer Networks Transform E‑Commerce Product Title Generation

DataFunTalk

Nov 29, 2018 · Artificial Intelligence

TensorFlow Technology Development and Practical Applications: Deep Learning Overview, TensorFlow Introduction, and Fashion Design Use Cases

The article summarizes Zheng Zeyu's presentation on deep learning fundamentals, the evolution and features of TensorFlow, and how AI techniques such as neural networks and Faster R-CNN are applied to address data challenges and enable intelligent fashion design and recommendation.

Faster R-CNNTensorFlowdeep learning

0 likes · 10 min read

TensorFlow Technology Development and Practical Applications: Deep Learning Overview, TensorFlow Introduction, and Fashion Design Use Cases

Alibaba Cloud Developer

Nov 28, 2018 · Artificial Intelligence

How Alibaba’s X-Deep Learning Framework Revolutionizes High‑Dimensional Sparse Data Processing

Alibaba's X-Deep Learning (XDL) framework, the first open‑source deep learning system designed for high‑dimensional sparse data, powers advertising, recommendation, and search workloads, delivering industrial‑scale performance and boosting revenue while offering an open, easy‑to‑use solution for the broader AI community.

AdvertisingXDLdeep learning

0 likes · 6 min read

How Alibaba’s X-Deep Learning Framework Revolutionizes High‑Dimensional Sparse Data Processing

MaGe Linux Operations

Nov 26, 2018 · Artificial Intelligence

Master Python Machine Learning in 14 Steps: From Zero to Expert

This comprehensive guide walks beginners through fourteen practical steps to learn Python machine learning, covering essential Python skills, core scientific libraries, fundamental algorithms, advanced techniques like SVM and ensemble methods, dimensionality reduction, and deep learning with TensorFlow, all using free online resources.

Data SciencePythondeep learning

0 likes · 22 min read

Master Python Machine Learning in 14 Steps: From Zero to Expert

MaGe Linux Operations

Nov 22, 2018 · Artificial Intelligence

Accelerating TensorFlow Deep Learning: GPU & Distributed Training Techniques

This article explains how to speed up TensorFlow deep‑learning model training using single‑GPU acceleration, multi‑GPU parallelism, and distributed TensorFlow on Kubernetes, covering device placement, session parameters, synchronous vs asynchronous training modes, and practical code examples to improve performance and scalability.

Distributed TrainingGPU accelerationTensorFlow

0 likes · 10 min read

Accelerating TensorFlow Deep Learning: GPU & Distributed Training Techniques

JD Retail Technology

Nov 22, 2018 · Artificial Intelligence

Challenges and Innovations in Category Classification Systems

This article discusses the limitations of algorithm-based classification models, including the need for large labeled datasets, limited sample coverage, frequent category changes requiring retraining, and complex optimization issues, while exploring knowledge graph-based approaches and generative adversarial networks for more flexible and accurate classification.

Generative Adversarial Networksbad case optimizationcategory optimization

0 likes · 6 min read

Challenges and Innovations in Category Classification Systems

21CTO

Nov 21, 2018 · Artificial Intelligence

What’s Driving the Rapid Evolution of Face Recognition Technology?

This comprehensive overview examines the fundamentals, historical milestones, key algorithms, major datasets, policy support, industry applications, and future trends of face recognition technology, highlighting its rapid growth within computer vision and artificial intelligence.

AIBiometricscomputer vision

0 likes · 45 min read

What’s Driving the Rapid Evolution of Face Recognition Technology?

Tencent Cloud Developer

Nov 20, 2018 · Artificial Intelligence

Top 18 Machine Learning Platforms Every Developer Should Know

This guide lists and briefly describes 18 open‑source and cloud‑based machine learning platforms—from H2O and TensorFlow to Azure ML and AWS services—highlighting their key features, supported languages, and typical use cases for developers at any skill level.

AI toolsclouddeep learning

0 likes · 12 min read

Top 18 Machine Learning Platforms Every Developer Should Know

Xianyu Technology

Nov 20, 2018 · Artificial Intelligence

How to Separate Complex Image Foreground from Background Using AI and Classic CV Techniques

This article presents a step‑by‑step solution that combines computer‑vision preprocessing, OCR, CNN classification, shape matching, and inpainting to isolate meaningful foreground elements from images with intricate backgrounds, discussing practical results, limitations, and code implementations.

OpenCVTensorFlowcomputer vision

0 likes · 15 min read

How to Separate Complex Image Foreground from Background Using AI and Classic CV Techniques

Alibaba Cloud Developer

Nov 20, 2018 · Artificial Intelligence

How Reinforcement Learning Powers Interactive Search in E‑Commerce

This article explains how reinforcement learning can be modeled and deployed to enable intelligent, interactive product search on e‑commerce platforms, detailing problem definition, system architecture, training methodology, online results, and future research directions.

deep learningdialogue systeme-commerce

0 likes · 17 min read

How Reinforcement Learning Powers Interactive Search in E‑Commerce

Tencent Cloud Developer

Nov 19, 2018 · Artificial Intelligence

10 Open-Source Tools and Frameworks for Artificial Intelligence

The article surveys ten leading open-source AI tools and frameworks—including TensorFlow, SystemML, Caffe, Apache Mahout, OpenNN, Torch, Neuroph, Deeplearning4j, Mycroft, and OpenCog—detailing their primary features, supported languages, hardware compatibility, and typical use cases for research and development.

Artificial IntelligenceFrameworksdeep learning

0 likes · 12 min read

10 Open-Source Tools and Frameworks for Artificial Intelligence

vivo Internet Technology

Nov 16, 2018 · Artificial Intelligence

Efficient Vector Search with Deep Learning Embeddings in Elasticsearch

The article explains how to replace keyword matching with deep‑learning document embeddings in Elasticsearch by applying PCA dimensionality reduction, indexing vectors using Lucene’s KD‑tree structures via a custom plugin, and leveraging FAISS‑style nearest‑neighbour techniques to achieve fast, semantically aware similarity search.

ElasticsearchFAISSKD-Tree

0 likes · 7 min read

Efficient Vector Search with Deep Learning Embeddings in Elasticsearch

DataFunTalk

Nov 1, 2018 · Artificial Intelligence

Intelligent Customer Service at Meituan: NLP Techniques, System Architecture, and Real‑World Deployment

The article presents a comprehensive overview of Meituan's intelligent customer service system, detailing its evolution, the roles of QABot, TaskBot and ChatBot, the underlying NLP and knowledge‑graph technologies, model implementations such as DSSM and Seq2seq, and the impressive operational results achieved in food‑delivery and ride‑hailing services.

MeituanNLPdeep learning

0 likes · 14 min read

Intelligent Customer Service at Meituan: NLP Techniques, System Architecture, and Real‑World Deployment

Alibaba Cloud Developer

Nov 1, 2018 · Artificial Intelligence

How DFSMN Cuts Speech Synthesis Model Size by 75% and Quadruples Speed

Researchers propose a Deep Feedforward Sequential Memory Network (DFSMN) for speech synthesis that matches BLSTM quality while using only a quarter of the model size and achieving four times faster inference, making it ideal for memory‑constrained, real‑time edge devices.

DFSMNSpeech Synthesisdeep learning

0 likes · 10 min read

How DFSMN Cuts Speech Synthesis Model Size by 75% and Quadruples Speed

Alibaba Cloud Developer

Oct 30, 2018 · Artificial Intelligence

How Advanced LSTM (A‑LSTM) Boosts Speech Emotion Recognition by 5.5%

This article introduces Advanced LSTM (A‑LSTM), which linearly combines multiple past hidden states to overcome traditional LSTM's one‑step dependency, and demonstrates its application in utterance‑level speech emotion recognition, achieving a 5.5% accuracy improvement through attention‑based weighted‑pooling RNNs and auxiliary speaker and gender tasks.

A-LSTMAttentionLSTM

0 likes · 8 min read

How Advanced LSTM (A‑LSTM) Boosts Speech Emotion Recognition by 5.5%

Youku Technology

Oct 25, 2018 · Artificial Intelligence

High‑Frame‑Rate Video Interpolation: FRUC Algorithm for 25→50 FPS Conversion

During the World Cup, Youku used a frame‑rate‑up‑conversion algorithm that synthesizes intermediate frames by combining block‑based motion estimation, optical‑flow refinement, and a rule‑based plus deep‑learning fusion, enabling smooth 25→50 fps video and preserving fast‑moving objects such as a football.

FRUCdeep learningframe-rate conversion

0 likes · 10 min read

High‑Frame‑Rate Video Interpolation: FRUC Algorithm for 25→50 FPS Conversion

Tencent Cloud Developer

Oct 23, 2018 · Artificial Intelligence

Demystifying AI, Machine Learning, and Deep Learning

The article clarifies that artificial intelligence encompasses machine learning, which in turn includes deep learning, and uses real‑world examples—from fraud detection and customer clustering to image recognition and language translation—to illustrate how these data‑driven models learn patterns, make predictions, and transform many industries.

Artificial IntelligenceData ScienceUnsupervised Learning

0 likes · 12 min read

Demystifying AI, Machine Learning, and Deep Learning

Alibaba Cloud Developer

Oct 23, 2018 · Artificial Intelligence

How DFSMN Cuts Speech Synthesis Model Size by 75% While Quadrupling Speed

This paper introduces a Deep Feedforward Sequential Memory Network (DFSMN) for statistical parametric speech synthesis that matches BLSTM quality with only a quarter of the model size and four times faster inference, making it ideal for memory‑constrained, real‑time IoT devices.

DFSMNIoT devicesSpeech Synthesis

0 likes · 10 min read

How DFSMN Cuts Speech Synthesis Model Size by 75% While Quadrupling Speed

Manbang Technology Team

Oct 21, 2018 · Artificial Intelligence

AI and Deep Learning for Highway Freight Matching – Insights from QCon 2018

The article summarizes a QCon 2018 presentation by Luo Jingjia of Manbang Group, detailing how AI and deep‑learning techniques are applied to model, optimize, and recommend vehicle‑cargo matching in China’s massive highway logistics network, including data handling, neural‑network design, and practical challenges.

AIdeep learningrecommendation system

0 likes · 18 min read

AI and Deep Learning for Highway Freight Matching – Insights from QCon 2018

Tencent Cloud Developer

Oct 12, 2018 · Artificial Intelligence

Understanding Convolutional Neural Networks (CNN) with Keras

The article introduces convolutional neural networks, explains core concepts such as convolution, padding, stride, and pooling, demonstrates how to calculate output dimensions, and provides a step‑by‑step Keras example that builds, compiles, and trains a multi‑layer CNN for image classification.

CNNKerasPython

0 likes · 8 min read

Understanding Convolutional Neural Networks (CNN) with Keras

Ctrip Technology

Oct 10, 2018 · Artificial Intelligence

Intelligent Image Aesthetic Scoring for OTA Ticket Listings Using Deep Learning

This article describes how deep learning techniques, including convolutional neural networks and CAM visualizations, are applied to automatically evaluate and select high‑quality images for online travel agency ticket listings, improving user experience while reducing manual effort.

CNNOTAdeep learning

0 likes · 11 min read

Intelligent Image Aesthetic Scoring for OTA Ticket Listings Using Deep Learning

MaGe Linux Operations

Oct 10, 2018 · Artificial Intelligence

How to Build Real-Time Object Detection with OpenCV and Deep Learning in Python

This tutorial explains how to extend a deep‑learning object detection project with OpenCV and Python to process live video streams, covering setup, command‑line arguments, model loading, frame‑by‑frame detection, drawing bounding boxes, FPS measurement, and performance tips for achieving real‑time results.

VideoStreamdeep learningfps

0 likes · 8 min read

How to Build Real-Time Object Detection with OpenCV and Deep Learning in Python

Alibaba Cloud Developer

Sep 30, 2018 · Artificial Intelligence

How Alibaba’s Search & Recommendation Evolved: From Rules to Cognitive AI

This article reviews the evolution of Alibaba’s e‑commerce search and recommendation technologies, detailing Taobao’s unique challenges, the shift from rule‑based retrieval to large‑scale machine learning, real‑time online learning, deep learning and intelligent decision‑making, and outlines future directions toward cognitive intelligence.

cognitive AIdeep learninge-commerce

0 likes · 16 min read

How Alibaba’s Search & Recommendation Evolved: From Rules to Cognitive AI

Alibaba Cloud Developer

Sep 27, 2018 · Artificial Intelligence

How DeepInsight Transforms Deep Learning Model Debugging with Real-Time Visualization

DeepInsight is a distributed, micro‑service‑based platform that provides end‑to‑end data exposure, multi‑dimensional visual analysis, and interactive debugging for TensorFlow models, turning opaque neural networks into transparent, controllable systems through real‑time visualizations, dynamic data sets, and integrated lifecycle management.

AI platformTensorFlowdeep learning

0 likes · 17 min read

How DeepInsight Transforms Deep Learning Model Debugging with Real-Time Visualization

Alibaba Cloud Developer

Sep 25, 2018 · Artificial Intelligence

How Deep Learning Unwarps Curved Document Images for Better OCR

This article explores the challenges of OCR on warped document images, reviews traditional and deep‑learning‑based correction methods, describes a synthetic dataset generation pipeline, proposes enhanced U‑Net architectures including stacked and dilated variants, evaluates them with MS‑SSIM, and outlines future research directions.

OCRU-Netdeep learning

0 likes · 18 min read

JD Retail Technology

Sep 21, 2018 · Artificial Intelligence

JD.com's AI-Powered UGC Content Management System for E-Commerce Reviews

JD.com's technical architecture team partnered with product teams to leverage the Euler knowledge computing platform and product knowledge graph to enhance the e-commerce review ecosystem, improving user experience in UGC communities through intelligent content management.

AI content moderationOpinion MiningUGC management

0 likes · 6 min read

JD.com's AI-Powered UGC Content Management System for E-Commerce Reviews

DataFunTalk

Sep 16, 2018 · Artificial Intelligence

Interview with Dr. Lv Zhengdong, Founder & CTO of DeepCuriosity on AI and Natural Language Processing

In an interview at the 2018 AI Pioneer Conference, Dr. Lv Zhengdong discusses his background, the development of neural‑symbolic AI at DeepCuriosity, its applications in law, public security and finance, challenges in NLP, and his perspective on the future trajectory of artificial intelligence.

AINatural Language Processingdeep learning

0 likes · 7 min read

Interview with Dr. Lv Zhengdong, Founder & CTO of DeepCuriosity on AI and Natural Language Processing