BestHub
Sign in
Tagged articles

deep learning

1283 articles · Page 5 of 13
Ele.me Technology
Ele.me Technology
Aug 16, 2023 · Artificial Intelligence

Spatiotemporal-Enhanced Network for Click-Through Rate Prediction in Location‑Based Services

The paper introduces StEN, a spatiotemporal-enhanced network for CTR prediction in location-based services, combining static spatiotemporal feature activation, dynamic preference activation, and target attention, achieving state-of-the-art offline results and a 1.6% CTR lift in online tests.

click-through ratedeep learningrecommendation systems
0 likes · 19 min read
Spatiotemporal-Enhanced Network for Click-Through Rate Prediction in Location‑Based Services
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Aug 16, 2023 · Artificial Intelligence

Deep Dive into OCR – Chapter 2: Development and Classification of OCR Technology

This article provides a comprehensive overview of OCR technology, detailing the evolution from traditional hand‑crafted methods to modern deep‑learning approaches, describing image preprocessing, text detection and recognition pipelines, summarizing classic machine‑learning algorithms, and presenting a practical OpenCV implementation with Python code.

OCROpenCVPython
0 likes · 23 min read
Deep Dive into OCR – Chapter 2: Development and Classification of OCR Technology
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Aug 12, 2023 · Artificial Intelligence

An Introduction to OCR: Concepts, History, Applications, Datasets, and Technical Workflow

This article provides a comprehensive overview of Optical Character Recognition (OCR), covering its definition, historical development, classification, real‑world applications, technical pipeline, common challenges, mitigation strategies, popular datasets, model performance comparisons, and leading open‑source platforms.

OCROptical Character Recognitioncomputer vision
0 likes · 16 min read
An Introduction to OCR: Concepts, History, Applications, Datasets, and Technical Workflow
Kuaishou Tech
Kuaishou Tech
Aug 11, 2023 · Artificial Intelligence

PEPNet: Parameter and Embedding Personalized Network for Multi‑Task Multi‑Domain Recommendation

The paper introduces PEPNet, a plug‑and‑play network that tackles the domain‑seesaw and task‑seesaw problems in multi‑scenario recommendation by using a gated personalization module (GateNU) together with embedding‑level (EPNet) and parameter‑level (PPNet) personalization, and demonstrates its superiority through extensive offline and online experiments on Kuaishou data.

deep learningembeddinggate network
0 likes · 11 min read
PEPNet: Parameter and Embedding Personalized Network for Multi‑Task Multi‑Domain Recommendation
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jul 31, 2023 · Artificial Intelligence

Overview of Deep Neural Network Architectures

This article provides a comprehensive overview of deep neural network families, introducing twelve major architectures—including Feedforward, CNN, RNN, LSTM, DBN, GAN, Autoencoder, Residual, Capsule, Transformer, Attention, and Deep Reinforcement Learning—explaining their principles, structures, training methods, and offering Python/TensorFlow/PyTorch code examples.

CNNGaNPython
0 likes · 29 min read
Overview of Deep Neural Network Architectures
Smart Era Software Development
Smart Era Software Development
Jul 26, 2023 · Artificial Intelligence

Three Core Skills Every Aspiring AI Architect Needs

The article defines the AI architect role and outlines three essential capabilities—mastery of AI technologies and development workflow, deep business understanding with strong abstraction ability, and the design and implementation of efficient, scalable AI solutions—explaining why each is critical for successful AI product delivery.

AI architectureBusiness AnalysisSystem Design
0 likes · 10 min read
Three Core Skills Every Aspiring AI Architect Needs
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jul 26, 2023 · Artificial Intelligence

Building and Training a Fully Connected Neural Network for Fashion-MNIST Classification with PyTorch

This tutorial demonstrates how to download the Fashion‑MNIST dataset, build a four‑layer fully connected neural network with PyTorch, and train it using loss functions, Adam optimizer, learning‑rate strategies, and Dropout to achieve high‑accuracy multi‑class image classification.

AdamDropoutFashion-MNIST
0 likes · 17 min read
Building and Training a Fully Connected Neural Network for Fashion-MNIST Classification with PyTorch
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jul 24, 2023 · Artificial Intelligence

Understanding Slide-Transformer: An Efficient Local Attention Module for Vision Transformers

This article explains the Slide-Transformer paper, describing how the proposed Slide Attention replaces inefficient Im2Col‑based local attention with depthwise convolutions and a deformable shift module, achieving high efficiency, flexibility, and hardware‑agnostic performance for Vision Transformers.

Deformable ShiftDepthwise ConvolutionSlide Attention
0 likes · 13 min read
Understanding Slide-Transformer: An Efficient Local Attention Module for Vision Transformers
Nightwalker Tech
Nightwalker Tech
Jul 19, 2023 · Artificial Intelligence

Step‑by‑Step Implementation of Transformer Blocks, Attention, Normalization, Feed‑Forward, Encoder and Decoder in PyTorch

This article provides a comprehensive tutorial on building the core components of a Transformer model—including multi‑head attention, layer normalization, feed‑forward networks, encoder and decoder layers—and assembles them into a complete PyTorch implementation, supplemented with explanatory diagrams and runnable code.

AttentionEncoderPyTorch
0 likes · 13 min read
Step‑by‑Step Implementation of Transformer Blocks, Attention, Normalization, Feed‑Forward, Encoder and Decoder in PyTorch
Test Development Learning Exchange
Test Development Learning Exchange
Jul 12, 2023 · Fundamentals

Common Python Libraries and Practical Projects: NumPy, Pandas, Matplotlib, Scikit‑learn, Requests, Beautiful Soup, Selenium, Pygame, Flask, PyTorch

This article introduces ten widely used Python libraries—NumPy, Pandas, Matplotlib, Scikit‑learn, Requests, Beautiful Soup, Selenium, Pygame, Flask, and PyTorch—each accompanied by a concise real‑world project and complete code examples to help readers understand and apply them effectively.

Data SciencePythonWeb Scraping
0 likes · 18 min read
Common Python Libraries and Practical Projects: NumPy, Pandas, Matplotlib, Scikit‑learn, Requests, Beautiful Soup, Selenium, Pygame, Flask, PyTorch
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jul 12, 2023 · Artificial Intelligence

Comprehensive Guide to Vision Transformer (ViT): Architecture, Patch Tokenization, Embedding, Fine‑tuning, and Performance

This article provides an in‑depth, English‑language overview of Vision Transformer (ViT), covering its Transformer‑based architecture, patch‑to‑token conversion, token and position embeddings, fine‑tuning strategies such as 2‑D interpolation, experimental results versus CNNs, and the model’s broader significance for multimodal AI research.

Fine‑tuningPatch EmbeddingTransformer
0 likes · 25 min read
Comprehensive Guide to Vision Transformer (ViT): Architecture, Patch Tokenization, Embedding, Fine‑tuning, and Performance
Kuaishou Large Model
Kuaishou Large Model
Jul 7, 2023 · Artificial Intelligence

How HairStep Revolutionizes Single-View 3D Hair Reconstruction

This paper introduces HairStep, a novel intermediate representation combining Strand Maps and Depth Maps, and demonstrates how it reduces domain gap and improves single‑view 3D hair reconstruction accuracy across multiple algorithms, supported by new annotated datasets (HiSa, HiDa) and fair evaluation metrics.

3D hair reconstructionHairStepcomputer vision
0 likes · 11 min read
How HairStep Revolutionizes Single-View 3D Hair Reconstruction
DataFunSummit
DataFunSummit
Jul 1, 2023 · Artificial Intelligence

Alibaba Cloud Native Deep Learning Platform PAI‑DLC: Architecture, Features, and Future Outlook

This article introduces Alibaba Cloud's PAI‑DLC, a cloud‑native deep learning platform that integrates machine‑learning capabilities, containerized services, AI‑aware scheduling, GPU virtualization, elastic training with EasyScale, data access, and observability, and discusses its architecture, key features, and future directions.

AI platformGPU virtualizationKubernetes
0 likes · 16 min read
Alibaba Cloud Native Deep Learning Platform PAI‑DLC: Architecture, Features, and Future Outlook
Architecture & Thinking
Architecture & Thinking
Jun 30, 2023 · Artificial Intelligence

How INT8 Quantization Supercharges Baidu's Search Models: Techniques and Insights

This article explores the rapid evolution of Baidu's semantic search models, the large GPU consumption they entail, and how extensive INT8 quantization, sensitivity analysis, calibration data augmentation, hyper‑parameter auto‑tuning, and advanced methods like Quantization‑Aware Training and SmoothQuant dramatically improve inference performance while preserving business metrics.

ERNIEINT8 quantizationdeep learning
0 likes · 17 min read
How INT8 Quantization Supercharges Baidu's Search Models: Techniques and Insights
OPPO Kernel Craftsman
OPPO Kernel Craftsman
Jun 28, 2023 · Artificial Intelligence

ShaderNN 2.0: A Lightweight Mobile Deep Learning Inference Engine with OpenGL and Vulkan Support

ShaderNN 2.0 is a lightweight mobile deep learning inference engine supporting OpenGL and Vulkan, offering texture‑based zero‑copy I/O, hybrid shader implementation, and achieving significant latency and power reductions versus TensorFlow Lite and MNN, thereby enabling real‑time graphics‑AI tasks such as style transfer, denoising, super‑sampling, and Stable Diffusion on smartphones.

GPU shaderOpenGLShaderNN
0 likes · 16 min read
ShaderNN 2.0: A Lightweight Mobile Deep Learning Inference Engine with OpenGL and Vulkan Support
Bilibili Tech
Bilibili Tech
Jun 27, 2023 · Artificial Intelligence

Design and Implementation of a Real-Time Advertising Feature Platform for CTR Prediction at Bilibili

To eliminate data fragmentation, feature inconsistencies, and multi‑language implementation challenges, Bilibili built a unified real‑time advertising feature platform that aligns offline, hourly, and online pipelines via a shared C++ library and JNI, boosting CTR prediction accuracy, cutting training costs, and increasing ad revenue by over 1 %.

AdvertisingCTR predictionFlink
0 likes · 11 min read
Design and Implementation of a Real-Time Advertising Feature Platform for CTR Prediction at Bilibili
Efficient Ops
Efficient Ops
Jun 26, 2023 · Artificial Intelligence

How Multimodal AI Is Revolutionizing Credit Card Fraud Detection

Amid tightening financial regulations, ICBC's software team proposes a multimodal AI anti‑fraud framework that combines image, video, and structured data to detect deep‑fake, mask, and forged‑document attacks, enriches verification with cross‑modal cues, and outlines future expansion to text and speech modalities.

AICredit CardMultimodal
0 likes · 7 min read
How Multimodal AI Is Revolutionizing Credit Card Fraud Detection
Programmer DD
Programmer DD
Jun 25, 2023 · Artificial Intelligence

How to Build Image Search with Elasticsearch 8.x and CLIP Multilingual Model

This article explains the concept of image‑based search, why it matters, and provides a step‑by‑step guide to implement image search using Elasticsearch 8.x, feature‑extraction libraries, and the multilingual CLIP‑ViT‑B‑32 model, including code snippets and architecture overview.

clip modeldeep learningfeature extraction
0 likes · 10 min read
How to Build Image Search with Elasticsearch 8.x and CLIP Multilingual Model
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Jun 21, 2023 · Artificial Intelligence

How GoldMiner Boosts Deep Learning Training by Up to 12× with Elastic Data Pre‑Processing

GoldMiner, a new system from Alibaba Cloud’s PAI platform, elastically scales deep learning data pre‑processing pipelines, dramatically improving training performance up to 12.1× and GPU cluster utilization by 2.5×, and its underlying research was accepted at SIGMOD 2023.

GPU utilizationSIGMODdata preprocessing
0 likes · 5 min read
How GoldMiner Boosts Deep Learning Training by Up to 12× with Elastic Data Pre‑Processing
Kuaishou Audio & Video Technology
Kuaishou Audio & Video Technology
Jun 20, 2023 · Artificial Intelligence

How a Low‑Latency Hierarchical Fusion Network Beats Echoes in Real‑Time Calls

At ICASSP 2023, Kuaishou’s audio team presented a low‑latency hierarchical fusion network for full‑band acoustic echo cancellation, detailing its multi‑stage design, asymmetric windowing, loss functions, training strategy, and achieving second place in the non‑personalized AEC Challenge, with real‑world deployment results.

Acoustic Echo CancellationHierarchical Fusion NetworkSignal Processing
0 likes · 13 min read
How a Low‑Latency Hierarchical Fusion Network Beats Echoes in Real‑Time Calls
Smart Era Software Development
Smart Era Software Development
Jun 17, 2023 · Artificial Intelligence

Ilya Sutskever Discusses the Future of Large Language Models

In a Stanford eCorner interview, Ilya Sutskever, chief scientist of OpenAI and architect of GPT, reflects on the history of large language models, compares AI to human cognition, debates open‑source versus closed‑source models, discusses regulation, training strategies, and offers guidance for aspiring AI researchers.

AILarge Language Modelsdeep learning
0 likes · 21 min read
Ilya Sutskever Discusses the Future of Large Language Models
21CTO
21CTO
Jun 10, 2023 · Artificial Intelligence

How Huang Xuedong’s Team Achieved Human-Level Speech Recognition at Microsoft

The article chronicles the career of Chinese AI pioneer Huang Xuedong, detailing his education, rise at Microsoft, leadership of Azure AI, groundbreaking human‑level speech recognition breakthroughs, the engineering feats behind them—including a ten‑network model and the CNTK framework—and his recent move to Zoom.

Artificial IntelligenceCNTKMicrosoft
0 likes · 14 min read
How Huang Xuedong’s Team Achieved Human-Level Speech Recognition at Microsoft
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Jun 9, 2023 · Artificial Intelligence

2023 NIRC PhD Graduates Reveal Cutting-Edge AI and Network Intelligence Research

In 2023 the Network Intelligent Research Center celebrated its largest PhD graduating class—seven scholars whose dissertations span deep‑vision hand‑gesture estimation, multi‑scenario network transmission, graph alignment, interactive streaming, knowledge‑defined networking, wireless body‑area networking, and more—showcasing significant AI‑driven advances and high‑impact publications.

Artificial IntelligenceGraph AlignmentWireless Networks
0 likes · 30 min read
2023 NIRC PhD Graduates Reveal Cutting-Edge AI and Network Intelligence Research
Alimama Tech
Alimama Tech
May 31, 2023 · Artificial Intelligence

CF-Font: Content Fusion for Few-shot Font Generation

CF‑Font introduces a content‑fusion module that linearly mixes base‑font content features using a font‑level distance metric, combined with iterative style refinement and a projection character loss, achieving state‑of‑the‑art few‑shot Chinese font generation that outperforms prior methods by over 5% on L1 and FID and is already used to create proprietary Alibaba‑Mama fonts.

content fusiondeep learningfew-shot font generation
0 likes · 10 min read
CF-Font: Content Fusion for Few-shot Font Generation
DataFunSummit
DataFunSummit
May 31, 2023 · Artificial Intelligence

Evolution of Face Detection Techniques: Datasets, Research Directions, and Future Work

This article reviews the evolution of face detection, covering the Widely‑Face dataset, major research directions such as feature fusion, label assignment, auxiliary supervision, anchor‑free methods, NAS‑based designs, summarizes key papers from S3FD to MogFace, introduces ModelScope implementations, and outlines future challenges and opportunities.

AI researchFace Detectioncomputer vision
0 likes · 13 min read
Evolution of Face Detection Techniques: Datasets, Research Directions, and Future Work
JD Retail Technology
JD Retail Technology
May 16, 2023 · Artificial Intelligence

Deploying and Fine‑Tuning the Alpaca‑LoRA Large Language Model on a Multi‑GPU Server

This guide details the end‑to‑end process of installing GPU drivers, setting up a Python environment, deploying the open‑source Alpaca‑LoRA model, fine‑tuning it with Chinese data on a multi‑GPU server, and performing inference, while highlighting practical challenges and performance observations.

Alpaca-LoRAFine-tuningLLM
0 likes · 11 min read
Deploying and Fine‑Tuning the Alpaca‑LoRA Large Language Model on a Multi‑GPU Server
Architects' Tech Alliance
Architects' Tech Alliance
May 15, 2023 · Artificial Intelligence

How Transformer Powers ChatGPT: A Deep Dive into Attention and Architecture

This article provides a comprehensive analysis of the Transformer model behind ChatGPT, covering its origin, core mechanisms such as embedding, positional encoding, self‑attention, multi‑head attention, a step‑by‑step translation example, and the broader implications for AI research and industry.

AI architectureAttention MechanismChatGPT
0 likes · 19 min read
How Transformer Powers ChatGPT: A Deep Dive into Attention and Architecture
Full-Stack Trendsetter
Full-Stack Trendsetter
May 15, 2023 · Artificial Intelligence

Do You Really Understand ChatGPT, the Era‑Defining AI?

This article explains what ChatGPT is, how it builds on natural-language-processing and the Transformer-based GPT series, details its model-size growth, architectural enhancements, multilingual support, and walks through the tokenization-to-generation pipeline that enables coherent AI-driven conversations.

ChatGPTGPT-3NLP
0 likes · 8 min read
Do You Really Understand ChatGPT, the Era‑Defining AI?
DataFunTalk
DataFunTalk
May 13, 2023 · Artificial Intelligence

Multimedia Content Understanding at Weibo: Video Summarization, Quality Assessment, OCR, Embedding, and CV‑CUDA Optimization

This article presents Weibo's comprehensive multimedia content understanding pipeline, covering video summarization techniques, quality assessment models, OCR advancements, video embedding strategies, and the performance benefits of CV‑CUDA acceleration, while highlighting real‑world applications and engineering trade‑offs.

CV-CUDAOCRcomputer vision
0 likes · 32 min read
Multimedia Content Understanding at Weibo: Video Summarization, Quality Assessment, OCR, Embedding, and CV‑CUDA Optimization
Alimama Tech
Alimama Tech
May 10, 2023 · Artificial Intelligence

How AdaSparse Boosts Multi‑Scenario CTR Prediction with Adaptive Sparse Networks

AdaSparse introduces an adaptive sparse network that learns a dedicated sub‑network for each advertising scenario, balancing shared and specific knowledge while keeping computational cost low, and achieves +4.63% CTR and -3.82% CPC improvements in Alibaba’s external ad system, as validated on both public and massive production datasets.

AdvertisingCTR predictionadaptive sparsity
0 likes · 20 min read
How AdaSparse Boosts Multi‑Scenario CTR Prediction with Adaptive Sparse Networks
DaTaobao Tech
DaTaobao Tech
Apr 28, 2023 · Artificial Intelligence

Multi-Scenario Recommendation Model

The paper introduces SASS, a scenario-adaptive self-supervised recommendation model that uses contrastive pre-training and multi-layer gating to expand global samples and transfer scene-aware parameters, enabling a single model to deliver personalized recommendations across diverse Taobao ‘SuoSuo’ scenarios while mitigating data sparsity and cross-domain challenges.

AIData ModelingPersonalized Recommendation
0 likes · 23 min read
Multi-Scenario Recommendation Model
21CTO
21CTO
Apr 27, 2023 · Artificial Intelligence

Demystifying Transformers: A Step‑by‑Step Guide to Self‑Attention and Architecture

This article explains the Transformer model—from its encoder‑decoder structure and self‑attention mechanism to multi‑head attention, positional encoding, residual connections, training loss, and inference strategies—providing a clear, visual walkthrough for readers new to modern NLP architectures.

Transformerdeep learningmachine translation
0 likes · 21 min read
Demystifying Transformers: A Step‑by‑Step Guide to Self‑Attention and Architecture
High Availability Architecture
High Availability Architecture
Apr 27, 2023 · Artificial Intelligence

Design and Optimization of Bilibili's Large‑Scale Video Duplicate Detection System

This article describes the design, algorithmic improvements, and engineering performance optimizations of Bilibili's massive video duplicate detection (collision) system, covering challenges of low‑edit‑degree reposts, two‑stage retrieval, self‑supervised feature extraction, GPU‑accelerated preprocessing, and the resulting gains in accuracy and throughput.

BilibiliLarge-Scale RetrievalVector Search
0 likes · 17 min read
Design and Optimization of Bilibili's Large‑Scale Video Duplicate Detection System
DevOps
DevOps
Apr 25, 2023 · Artificial Intelligence

The Bitter Lesson: Why Brute‑Force Computation Outperforms Hand‑Crafted Knowledge in AI

Richard Sutton’s “The Bitter Lesson” argues that over the past seven decades the most powerful driver of AI progress has been general‑purpose compute and large‑scale search, which consistently surpasses methods that rely on human‑engineered knowledge across domains such as chess, Go, speech recognition, and computer vision.

AIbrute-forcecomputational scaling
0 likes · 7 min read
The Bitter Lesson: Why Brute‑Force Computation Outperforms Hand‑Crafted Knowledge in AI
Bilibili Tech
Bilibili Tech
Apr 21, 2023 · Artificial Intelligence

Design and Optimization of Bilibili's Large-Scale Video Duplicate Detection System

Bilibili built a massive video‑duplicate detection platform that trains a self‑supervised ResNet‑50 feature extractor, removes black borders, and uses a two‑stage ANN‑plus‑segment‑level matching pipeline accelerated by custom GPU decoding and inference, boosting duplicate rejection 7.5×, recall 3.75×, and cutting manual misses from 65 to 5 per day.

GPU accelerationLarge-Scale Retrievaldeep learning
0 likes · 19 min read
Design and Optimization of Bilibili's Large-Scale Video Duplicate Detection System
DataFunSummit
DataFunSummit
Apr 11, 2023 · Artificial Intelligence

OneFlow Coop: Joint Optimization of Dynamic‑Graph Recomputation and Memory Allocation

This article introduces OneFlow Coop, a memory‑optimization technique that jointly optimizes dynamic‑graph recomputation strategies and GPU memory allocation by analyzing existing DTR limitations, proposing recomputable in‑place, op‑guided tensor allocation, and layout‑aware eviction modules, and demonstrating superior experimental results.

Dynamic GraphGPU memoryMemory Optimization
0 likes · 18 min read
OneFlow Coop: Joint Optimization of Dynamic‑Graph Recomputation and Memory Allocation
Programmer DD
Programmer DD
Apr 10, 2023 · Artificial Intelligence

Why ChatGPT Sparks Panic and What Its Real Technical Foundations Are

In this talk, AI expert Wu Jun explains why ChatGPT has caused widespread fear, traces the historical development of language models from the 1970s to today, clarifies the massive computational and data requirements, and discusses the real impact and opportunities of large‑scale AI systems.

AI hypeChatGPTcomputational resources
0 likes · 20 min read
Why ChatGPT Sparks Panic and What Its Real Technical Foundations Are
DataFunTalk
DataFunTalk
Apr 3, 2023 · Artificial Intelligence

Implementing RNN, LSTM, and GRU with PyTorch

This article introduces the basic architectures of recurrent neural networks (RNN), LSTM, and GRU, explains PyTorch APIs such as nn.RNN, nn.LSTM, nn.GRU, details their parameters, demonstrates code examples for building and testing these models, and provides practical insights for deep learning practitioners.

GRULSTMPyTorch
0 likes · 9 min read
Implementing RNN, LSTM, and GRU with PyTorch
DataFunTalk
DataFunTalk
Apr 1, 2023 · Artificial Intelligence

Nvidia Meets OpenAI: Highlights from the GTC Fireside Chat on GPT‑4, Deep Learning History, and the Future of AI

In a GTC fireside chat, Nvidia CEO Jensen Huang and OpenAI co‑founder Ilya Sutskever discuss GPT‑4's multimodal advances, the evolution of deep learning from early neural networks to large‑scale models, the pivotal role of GPUs and datasets like ImageNet, and their vision for more reliable, scalable artificial intelligence.

Artificial IntelligenceGPT-4Multimodal
0 likes · 10 min read
Nvidia Meets OpenAI: Highlights from the GTC Fireside Chat on GPT‑4, Deep Learning History, and the Future of AI
21CTO
21CTO
Mar 31, 2023 · Artificial Intelligence

From Student to AI Pioneer: Ilya Sutskever’s Journey Behind ChatGPT

This article chronicles Ilya Sutskever’s two‑decade rise from a young researcher to a leading figure in artificial intelligence, highlighting his early mentorship, breakthroughs in image recognition, language translation, the founding of OpenAI, and the development of GPT and DALL‑E models.

AI researchGPTIlya Sutskever
0 likes · 13 min read
From Student to AI Pioneer: Ilya Sutskever’s Journey Behind ChatGPT
DataFunTalk
DataFunTalk
Mar 24, 2023 · Artificial Intelligence

Deep UPLIFT Modeling: Techniques, Challenges, and FinTech Applications

This article provides a comprehensive overview of deep UPLIFT models, covering their fundamentals, key technical challenges such as confounding bias and inductive bias, the evolution of meta‑learner and deep architectures, and practical case studies in financial technology marketing.

Marketing OptimizationUplift Modelingdeep learning
0 likes · 14 min read
Deep UPLIFT Modeling: Techniques, Challenges, and FinTech Applications
Python Programming Learning Circle
Python Programming Learning Circle
Mar 22, 2023 · Artificial Intelligence

Overview of PyTorch 2.0 Features and New APIs

The article provides a detailed overview of PyTorch 2.0, highlighting its stable and beta features such as torch.compile, accelerated transformers, MPS backend, new quantization support, and prototype parallelism tools, while emphasizing performance improvements for dynamic shapes, distributed training, and CPU/GPU inference.

AIAccelerated TransformersMPS
0 likes · 6 min read
Overview of PyTorch 2.0 Features and New APIs
Alibaba Cloud Infrastructure
Alibaba Cloud Infrastructure
Mar 22, 2023 · Artificial Intelligence

CUTLASS Extreme Performance Optimization and Its Application in Alibaba's Recommendation System

At the GTC conference, the talk presents Alibaba Cloud’s heterogeneous computing platform and introduces the Open Deep Learning API (ODLA), then details how CUTLASS‑based operator fusion dramatically accelerates attention and MLP layers in large‑scale recommendation models, achieving multi‑fold performance gains in production.

CutlassGPU computingPerformance Optimization
0 likes · 5 min read
CUTLASS Extreme Performance Optimization and Its Application in Alibaba's Recommendation System
Baidu Geek Talk
Baidu Geek Talk
Mar 16, 2023 · Artificial Intelligence

PaddleDetection v2.6 Release: PP-YOLOE Family Expansion and Advanced Detection Algorithms

PaddleDetection v2.6 expands the PP‑YOLOE family with rotating, small‑object, dense‑object, and ultra‑lightweight edge‑GPU models, upgrades PP‑Human and PP‑Vehicle toolboxes, releases semi‑supervised, few‑shot and distillation learning methods, adds numerous state‑of‑the‑art algorithms, and improves infrastructure with Python 3.10, EMA filtering and AdamW support.

BaiduFew-Shot LearningObject Detection
0 likes · 14 min read
PaddleDetection v2.6 Release: PP-YOLOE Family Expansion and Advanced Detection Algorithms
政采云技术
政采云技术
Mar 9, 2023 · Artificial Intelligence

Comprehensive Overview of Object Detection: From Traditional Methods to Modern Deep Learning Models

This article provides a comprehensive overview of object detection, describing traditional sliding‑window approaches, deep‑learning based two‑stage and one‑stage models such as R‑CNN, Faster R‑CNN, YOLO series, and discusses current challenges, improvement directions, and future research trends in the field.

Object DetectionR-CNNYOLO
0 likes · 29 min read
Comprehensive Overview of Object Detection: From Traditional Methods to Modern Deep Learning Models
Tencent Cloud Developer
Tencent Cloud Developer
Mar 8, 2023 · Artificial Intelligence

Building a Scalable Recommendation System for WeChat Games: Architecture and Implementation

The article describes WeChat Games’ scalable recommendation system, detailing its four‑component architecture—offline ML platform, unified management, online DAG‑based engine, and peripheral services—along with a hybrid algorithm library, feature engineering, real‑time monitoring, and solutions that boost engagement across diverse game recommendation scenarios.

architecture-designdata managementdeep learning
0 likes · 28 min read
Building a Scalable Recommendation System for WeChat Games: Architecture and Implementation
DataFunTalk
DataFunTalk
Feb 25, 2023 · Artificial Intelligence

The Evolution of Modern AI: From Deep Learning Foundations to ChatGPT and Future Directions

This article traces the development of artificial intelligence from its early conceptual roots and the 2012 deep‑learning breakthrough through the rise of self‑supervised large language models like BERT and GPT, explains ChatGPT’s architecture and RLHF training, and discusses its commercial impact and future prospects for fields such as life sciences.

AI applicationsChatGPTRLHF
0 likes · 19 min read
The Evolution of Modern AI: From Deep Learning Foundations to ChatGPT and Future Directions
DataFunTalk
DataFunTalk
Feb 22, 2023 · Artificial Intelligence

Fundamentals, Frontiers, and Applications of Graph Neural Networks

An in‑depth overview of graph neural networks (GNNs) covering their basic concepts, historical development, core models, recent research frontiers, and diverse applications such as recommendation systems, computer vision, NLP, program analysis, and smart cities, based on the book “Fundamentals, Frontiers and Applications of GNNs.”

AI applicationsGNN Modelsdeep learning
0 likes · 12 min read
Fundamentals, Frontiers, and Applications of Graph Neural Networks
Architects Research Society
Architects Research Society
Feb 18, 2023 · Artificial Intelligence

Comparison of Deep Learning Software Frameworks

This article provides an overview of deep learning as a branch of machine learning and presents detailed comparative tables of popular deep‑learning software frameworks, covering creators, initial releases, licenses, platforms, programming languages, supported features such as CUDA, OpenMP, and model‑training capabilities.

Artificial Intelligencedeep learningsoftware frameworks
0 likes · 9 min read
Comparison of Deep Learning Software Frameworks
Baidu Geek Talk
Baidu Geek Talk
Feb 15, 2023 · Artificial Intelligence

PaddlePaddle 2.4 Release: New Sparse, Graph, and Audio APIs

PaddlePaddle 2.4 introduces 167 new APIs—including sparse computing (paddle.sparse), graph learning (paddle.geometric), and audio processing (paddle.audio) modules—enabling efficient sparse model training and inference, graph message‑passing, advanced audio feature extraction, plus fresh loss functions, tensor utilities, and expanded vision transforms.

API ReleasePaddlePaddleaudio processing
0 likes · 16 min read
PaddlePaddle 2.4 Release: New Sparse, Graph, and Audio APIs
DataFunSummit
DataFunSummit
Feb 14, 2023 · Artificial Intelligence

Deep Learning Hyperparameter Tuning and Training Tips: Insights from Zhihu Experts

This article compiles practical deep learning training and hyperparameter tuning advice from Zhihu contributors, covering model debugging, learning‑rate strategies, optimizer choices, data preprocessing, regularization techniques, initialization methods, common pitfalls, recommended research papers, and ensemble approaches.

Gradient ClippingOptimizerRegularization
0 likes · 13 min read
Deep Learning Hyperparameter Tuning and Training Tips: Insights from Zhihu Experts
Volcano Engine Developer Services
Volcano Engine Developer Services
Feb 14, 2023 · Artificial Intelligence

How Make-An-Audio Turns Text Into Realistic Sound Effects

Make-An-Audio, a collaborative text‑to‑audio model from Zhejiang University, Peking University and Volcano Speech, uses a Distill‑then‑Reprogram strategy to generate high‑quality, controllable sound effects from any modality, showcasing impressive demos and promising future AIGC applications.

AIGCSpeech SynthesisText-to-Audio
0 likes · 7 min read
How Make-An-Audio Turns Text Into Realistic Sound Effects
DataFunTalk
DataFunTalk
Feb 11, 2023 · Artificial Intelligence

Accelerating Computer Vision Pipelines with CV-CUDA: Reducing Complexity and Performance Bottlenecks

This article explains how moving image preprocessing and post‑processing to GPU with the open‑source CV‑CUDA library dramatically reduces system complexity, eliminates CPU‑GPU bottlenecks, and delivers up to thirty‑fold performance gains for computer‑vision workloads across training and inference stages.

CV-CUDAGPU accelerationPerformance Optimization
0 likes · 16 min read
Accelerating Computer Vision Pipelines with CV-CUDA: Reducing Complexity and Performance Bottlenecks
JD Cloud Developers
JD Cloud Developers
Feb 8, 2023 · Operations

Boosting Log Anomaly Detection with NLP and Deep Learning

This article presents a log anomaly detection approach that leverages NLP techniques such as Part‑of‑Speech tagging and Named Entity Recognition combined with deep neural networks, detailing a six‑step model, experimental validation on three datasets, and superior performance compared with existing DeepLog and LogClass methods.

DNNNERNLP
0 likes · 13 min read
Boosting Log Anomaly Detection with NLP and Deep Learning
DataFunSummit
DataFunSummit
Feb 6, 2023 · Artificial Intelligence

A Minimalist White‑Box Unsupervised Learning Method Using Sparse Manifold Transform

A recent paper by Prof. Ma Yi and Turing‑Award winner Yann LeCun introduces a simple, interpretable unsupervised learning approach that combines sparse coding, manifold learning, and slow feature analysis, achieving near‑state‑of‑the‑art performance on MNIST, CIFAR‑10, and CIFAR‑100 without data augmentation or extensive hyper‑parameter tuning.

AIUnsupervised Learningdeep learning
0 likes · 8 min read
A Minimalist White‑Box Unsupervised Learning Method Using Sparse Manifold Transform
DataFunSummit
DataFunSummit
Feb 5, 2023 · Artificial Intelligence

Key Takeaways from the Causal Inference Summit: Motivation, Applications, Challenges, and Links to A/B Testing, Machine Learning, and Deep Learning

After attending the DataFun causal inference summit, this article outlines why causal analysis matters, its typical use cases, practical challenges, its relationship with A/B testing, and how it integrates with machine learning and deep learning to improve decision‑making and model robustness.

A/B testingCausal InferenceUplift Modeling
0 likes · 10 min read
Key Takeaways from the Causal Inference Summit: Motivation, Applications, Challenges, and Links to A/B Testing, Machine Learning, and Deep Learning
Alimama Tech
Alimama Tech
Feb 1, 2023 · Artificial Intelligence

CapOnImage: Context-driven Dense Captioning on Images

The paper presents CapOnImage, a novel image‑on‑image captioning task that generates location‑specific decorative text for product images, introduces the 2.1‑million‑image CapOnImage2M dataset, and proposes a mixed‑modality transformer with position‑aware pre‑training and progressive training, achieving superior accuracy and diversity and already deployed in Alibaba’s advertising platforms for measurable business impact.

Context-AwareImage CaptioningMultimodal
0 likes · 9 min read
CapOnImage: Context-driven Dense Captioning on Images
DataFunTalk
DataFunTalk
Jan 12, 2023 · Artificial Intelligence

The Evolution of AIGC in 2022 and Baidu’s Role in AI Talent and Large‑Model Innovation

The article reviews the rapid rise of AI‑generated content (AIGC) in 2022, outlines its historical development stages, highlights Baidu’s breakthrough video‑generation and search technologies, and discusses the severe AI talent shortage in China along with Baidu’s extensive training initiatives.

AI talentAIGCArtificial Intelligence
0 likes · 14 min read
The Evolution of AIGC in 2022 and Baidu’s Role in AI Talent and Large‑Model Innovation
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Jan 10, 2023 · Artificial Intelligence

AI‑Driven Video Coding: Expert Q&A on Intelligent Compression, Standards, and Future Directions

Experts Wang Shenshe and Chen Jing discuss how deep‑learning‑based video coding is reshaping traditional compression by offering modest quality gains but facing theoretical, hardware, and standardization hurdles, while debating hybrid versus end‑to‑end designs, rate control, 3‑D support, and the balance between human‑centric perception and machine‑oriented efficiency.

AIRate ControlVideo Coding
0 likes · 16 min read
AI‑Driven Video Coding: Expert Q&A on Intelligent Compression, Standards, and Future Directions
Tencent Cloud Developer
Tencent Cloud Developer
Jan 9, 2023 · Artificial Intelligence

Search Relevance Architecture and Practices in QQ Browser

The QQ Browser search relevance team describes a unified, billion‑scale architecture that combines a main and vertical subsystem, a pyramid‑shaped ranking pipeline (recall, coarse, fine), a dedicated GPU‑accelerated relevance service, and hybrid semantic‑matching models (dual‑tower, BERT, matrix fusion) evaluated with offline and online metrics to deliver accurate, fresh, and authoritative results for diverse content and long‑tail queries.

Information Retrievaldeep learningevaluation metrics
0 likes · 28 min read
Search Relevance Architecture and Practices in QQ Browser
DataFunTalk
DataFunTalk
Jan 9, 2023 · Artificial Intelligence

Key Techniques for Digital Human Modeling: Facial Portrait Editing, Eyelash Segmentation, and Real‑Time Loose Clothing Animation

This article reviews recent research on digital human creation, covering graph‑based facial portrait editing (fat‑slim adjustment, double‑chin removal, hair removal), a high‑quality eyelash segmentation dataset with the EyelashNet pipeline, and a deep‑learning framework for real‑time animation of loose clothing using virtual skeletons and RBF networks.

deep learningdigital humanseyelash segmentation
0 likes · 15 min read
Key Techniques for Digital Human Modeling: Facial Portrait Editing, Eyelash Segmentation, and Real‑Time Loose Clothing Animation
DataFunTalk
DataFunTalk
Jan 8, 2023 · Artificial Intelligence

Adaptive Blend Pyramid Network for Real-Time Local Retouching of Ultra High-Resolution Images

The paper introduces ABPN, an Adaptive Blend Pyramid Network that achieves precise, high‑quality skin retouching and garment wrinkle removal on 4K‑8K photos in real time by combining a context‑aware local retouching layer with a novel adaptive blend pyramid layer, addressing challenges of artifact‑free detail preservation and efficient high‑resolution processing.

adaptive blend pyramidcomputer visiondeep learning
0 likes · 16 min read
Adaptive Blend Pyramid Network for Real-Time Local Retouching of Ultra High-Resolution Images
Bilibili Tech
Bilibili Tech
Jan 3, 2023 · Artificial Intelligence

Two‑Pass Deep Learning Bitrate Factor Prediction for Constant‑Quality Segment Encoding in Bilibili Narrow‑Band HD Transcoding

Bilibili’s IEEE‑VCIP‑2022‑accepted two‑pass deep‑learning bitrate‑factor predictor achieves 98.8% accuracy with only 1.55 encoding passes, enabling constant‑quality segment encoding that reduces bitrate consumption by over 15% while maintaining visual quality in its narrow‑band HD transcoding pipeline.

AIBitrate Optimizationconstant quality
0 likes · 6 min read
Two‑Pass Deep Learning Bitrate Factor Prediction for Constant‑Quality Segment Encoding in Bilibili Narrow‑Band HD Transcoding
DataFunTalk
DataFunTalk
Dec 28, 2022 · Artificial Intelligence

A Comprehensive Survey of Graph Neural Networks: Development, Complex Graph Models, Applications, Scalability, and Future Directions

This article provides an extensive overview of graph neural networks, tracing their evolution from early RNN‑based models to modern message‑passing frameworks, discussing complex graph types, diverse real‑world applications, scalability challenges, design spaces, training platforms, and promising research directions.

GNNGraph Neural Networksdeep learning
0 likes · 49 min read
A Comprehensive Survey of Graph Neural Networks: Development, Complex Graph Models, Applications, Scalability, and Future Directions
DataFunTalk
DataFunTalk
Dec 27, 2022 · Artificial Intelligence

Efficient Training for Very Large‑Scale Face Recognition and the FFC Framework

This article reviews the challenges of ultra‑large‑scale face recognition, presents existing solutions such as metric learning, PFC and VFC, and details the proposed FFC framework with dual loaders, ID groups, probe and gallery networks, plus experimental results showing its cost‑effective performance.

AIcomputer visiondeep learning
0 likes · 7 min read
Efficient Training for Very Large‑Scale Face Recognition and the FFC Framework
58 Tech
58 Tech
Dec 22, 2022 · Artificial Intelligence

Implementing a Cloud-Native Istio Gateway for 58.com Deep Learning Inference Platform

This article details the evolution of 58.com’s deep learning inference platform, describing the transition from the original SCF‑based architecture to a cloud‑native Istio gateway (architecture 2.0), and explains design choices, traffic‑management, adaptive rate‑limiting, observability, model pre‑warming, and performance improvements.

AIInference PlatformIstio
0 likes · 22 min read
Implementing a Cloud-Native Istio Gateway for 58.com Deep Learning Inference Platform
Alimama Tech
Alimama Tech
Dec 21, 2022 · Artificial Intelligence

Adaptive Parameter Generation Network for Click-Through Rate Prediction

Adaptive Parameter Generation Network (APG) dynamically creates sample‑specific model parameters for click‑through‑rate prediction using low‑rank factorization, parameter sharing, and over‑parameterization, achieving up to 0.2% AUC improvement, 3% CTR lift, and up to 96.6% storage reduction with faster inference.

CTR predictionadaptive parameter generationdeep learning
0 likes · 14 min read
Adaptive Parameter Generation Network for Click-Through Rate Prediction
DataFunTalk
DataFunTalk
Dec 21, 2022 · Artificial Intelligence

A Comprehensive Overview of Computational Advertising: Architecture, Deep‑Learning Evolution, and Future Directions

This article provides a thorough examination of computational advertising, covering the oCPM pricing model as a superset, classic system architecture, the evolution of core modules such as ad ranking, pacing, bidding, federated learning, calibration, and conversion‑delay handling, and concludes with career advice for algorithm engineers.

ad rankingbudget optimizationcalibration
0 likes · 29 min read
A Comprehensive Overview of Computational Advertising: Architecture, Deep‑Learning Evolution, and Future Directions
DataFunTalk
DataFunTalk
Dec 17, 2022 · Artificial Intelligence

Multimodal Pre‑training Techniques and Applications – Overview, OPPOVL Dataset, Architecture, and Performance

This article presents a comprehensive overview of multimodal pre‑training, describing its motivation, architecture choices, large‑scale Chinese image‑text dataset construction, training optimizations, performance benchmarks, downstream applications, and a Q&A session that highlights practical deployment considerations.

MultimodalNatural Language ProcessingPretraining
0 likes · 16 min read
Multimodal Pre‑training Techniques and Applications – Overview, OPPOVL Dataset, Architecture, and Performance
Alimama Tech
Alimama Tech
Dec 14, 2022 · Artificial Intelligence

Contrastive Image Representation Learning with Debiasing for CTR Prediction

The article proposes a three-stage contrastive learning framework—pre‑training, fine‑tuning, and debiasing—to generate unbiased, fine‑grained image embeddings for mobile Taobao CTR prediction, achieving higher accuracy, fairness, and a 4‑5% CTR lift in large‑scale offline and online evaluations.

Bias MitigationCTR predictionContrastive Learning
0 likes · 14 min read
Contrastive Image Representation Learning with Debiasing for CTR Prediction
vivo Internet Technology
vivo Internet Technology
Dec 7, 2022 · Artificial Intelligence

Mixing Heterogeneous Queues in Vivo's Information Flow and App Store: Challenges, Practices, and RL/Deep Learning Solutions

Vivo tackles the complex problem of mixing heterogeneous content queues—ads, games, and organic items—in its information‑flow and app‑store by evolving from rule‑based weighting to Q‑learning and deep‑learning position models that respect product constraints, preserve ordering, and balance short‑term revenue with long‑term user experience, while planning deeper personalization and on‑device solutions.

AdvertisingApp StoreInformation Flow
0 likes · 14 min read
Mixing Heterogeneous Queues in Vivo's Information Flow and App Store: Challenges, Practices, and RL/Deep Learning Solutions
Alimama Tech
Alimama Tech
Dec 7, 2022 · Artificial Intelligence

Adaptive Domain Interest Network for Multi-domain Recommendation

The Adaptive Domain Interest Network (ADIN) introduces a shared backbone with scenario‑specific subnetworks, domain‑specific batch normalization and SE‑Block attention to capture both commonalities and divergences across recommendation scenarios, and, combined with self‑supervised training, consistently outperforms baselines, delivering a 1.8% revenue lift in Alibaba’s display‑ad platform and now runs in production.

Domain AdaptationSelf-Supervised Learningdeep learning
0 likes · 12 min read
Adaptive Domain Interest Network for Multi-domain Recommendation
DataFunTalk
DataFunTalk
Dec 4, 2022 · Artificial Intelligence

Key Insights on Causal Inference: Motivation, Applications, Challenges, and Links to A/B Testing, ML, and Deep Learning

This article summarizes the motivations behind causal inference, its typical business applications such as intelligent decision‑making and prediction, the practical challenges of validation and data, and its relationship with A/B testing, machine learning, and deep learning, providing a concise overview for newcomers.

AB TestingBusiness AnalyticsCausal Inference
0 likes · 10 min read
Key Insights on Causal Inference: Motivation, Applications, Challenges, and Links to A/B Testing, ML, and Deep Learning
Hulu Beijing
Hulu Beijing
Dec 2, 2022 · Artificial Intelligence

How Disney+ Designs a Multi‑Task Video Search Ranking Model

This article explains the architecture of a video search ranking system that combines a deep encoding network, multi‑task expert networks, and a bias‑correction module to jointly optimize relevance, click‑through rate, and watch time for streaming platforms.

Bias Correctiondeep learningfeature engineering
0 likes · 15 min read
How Disney+ Designs a Multi‑Task Video Search Ranking Model
DataFunSummit
DataFunSummit
Nov 30, 2022 · Artificial Intelligence

Combining Knowledge Graphs with Personalized News Recommendation Systems

This article presents a comprehensive overview of a personalized news recommendation system that leverages knowledge graphs to improve accuracy, explainability, and user satisfaction, detailing background motivations, graph construction methods, model architecture, experimental results, and practical insights from a Meituan research perspective.

Graph Neural Networksdeep learningexplainability
0 likes · 23 min read
Combining Knowledge Graphs with Personalized News Recommendation Systems
Architects Research Society
Architects Research Society
Nov 30, 2022 · Artificial Intelligence

A Comprehensive Overview of Machine Learning Tools and Libraries

An extensive survey ranks and compares a wide range of machine learning libraries and frameworks—both deep and shallow learning—detailing their languages, types, GPU acceleration, distributed computing capabilities, and typical academic and industrial applications, based on Google search popularity as of May.

Distributed ComputingGPU accelerationLibraries
0 likes · 20 min read
A Comprehensive Overview of Machine Learning Tools and Libraries
Dada Group Technology
Dada Group Technology
Nov 18, 2022 · Artificial Intelligence

JD Daojia Machine Learning Platform: Architecture and Implementation

This article introduces JD Daojia's machine learning platform, detailing its architecture, implementation principles, and practical applications in various business scenarios, achieving significant improvements in recommendation and search systems.

Distributed TrainingGraph Neural NetworksKubernetes
0 likes · 28 min read
JD Daojia Machine Learning Platform: Architecture and Implementation
SQB Blog
SQB Blog
Nov 18, 2022 · Artificial Intelligence

Boosting AI Model Development with Alibaba's EasyModeling Framework

This article introduces the EasyModeling framework built on Alibaba Cloud's PAI platform, detailing its modular design, high reusability, integration with deep‑learning libraries, automated hyper‑parameter tuning, deployment scenarios, and a real‑world case study using RoBERTa for dish‑name standardization, demonstrating significant performance gains.

AI modelingAlibaba CloudAutoML
0 likes · 13 min read
Boosting AI Model Development with Alibaba's EasyModeling Framework
Zuoyebang Tech Team
Zuoyebang Tech Team
Nov 17, 2022 · Artificial Intelligence

Scaling Deep Learning Model Serving: High‑Concurrency, Low‑Latency Solutions

This article examines the challenges of deploying dozens of deep‑learning models at Zuoyebang and compares three serving architectures—Gunicorn + Flask + Transformers, Tornado + PyTorch, and Tornado + Triton—highlighting performance trade‑offs and presenting a final high‑concurrency, low‑latency solution in production.

Inference ServingTritondeep learning
0 likes · 11 min read
Scaling Deep Learning Model Serving: High‑Concurrency, Low‑Latency Solutions
Tencent Advertising Technology
Tencent Advertising Technology
Nov 17, 2022 · Artificial Intelligence

Scaling Huge Embedding Model Training with Cache-Enabled Distributed Framework (HET): VLDB 2022 Best Paper and Its Industrial Deployment

The award‑winning VLDB 2022 paper introduces HET, a cache‑enabled distributed framework that dramatically reduces communication overhead for sparse trillion‑parameter embedding models, and Tencent Ads has industrialized this technology to train 10 TB‑scale models with up to 7×24‑hour online deep learning.

cachedeep learningembedding
0 likes · 9 min read
Scaling Huge Embedding Model Training with Cache-Enabled Distributed Framework (HET): VLDB 2022 Best Paper and Its Industrial Deployment
Alimama Tech
Alimama Tech
Nov 16, 2022 · Artificial Intelligence

STARDOM: Semantic-Aware Deep Hierarchical Forecasting Model for Search Traffic Prediction

STARDOM is an end‑to‑end deep hierarchical forecasting model that jointly learns hierarchical constraints, query semantics via pretrained BERT, and a calibration matrix within an encoder‑decoder architecture, using a distilled reconciliation loss and hierarchical sampling to accurately predict large‑scale search traffic and outperform state‑of‑the‑art baselines.

deep learninghierarchical modelingsearch advertising
0 likes · 22 min read
STARDOM: Semantic-Aware Deep Hierarchical Forecasting Model for Search Traffic Prediction
DataFunSummit
DataFunSummit
Nov 10, 2022 · Artificial Intelligence

Voice‑Driven Facial Animation for Digital Humans: Techniques and OPPO XiaoBu Assistant Practice

This article introduces digital‑human voice‑driven facial animation technologies, compares motion‑capture, audio‑driven and key‑point methods, details OPPO XiaoBu Assistant's end‑side and cloud‑side Audio2Lip pipelines, explores BlendShape versus Mesh approaches, and discusses current challenges and future research directions.

OPPOReal-time Renderingaudio-to-facial
0 likes · 15 min read
Voice‑Driven Facial Animation for Digital Humans: Techniques and OPPO XiaoBu Assistant Practice
Shopee Tech Team
Shopee Tech Team
Nov 10, 2022 · Artificial Intelligence

ShopeeVideo OCR: Multi-language Text Recognition System for E-commerce Video

ShopeeVideo OCR is a multi‑language text‑recognition system for Southeast Asian e‑commerce videos that unifies detection, Transformer‑based recognition, layout analysis, and large‑scale synthetic data generation to handle Indonesian, Filipino, English, Vietnamese, Thai and Chinese scripts, delivering industry‑leading accuracy and winning thirteen ICDAR first‑place awards.

Data SynthesisMulti-language OCROCR
0 likes · 15 min read
ShopeeVideo OCR: Multi-language Text Recognition System for E-commerce Video
Ctrip Technology
Ctrip Technology
Nov 10, 2022 · Artificial Intelligence

Improving Search Intent Recognition and Term Weighting with Deep Learning and Model Distillation at Ctrip

This article describes how Ctrip's R&D team applied deep‑learning models, BERT‑based embeddings, knowledge distillation, and term‑weighting techniques to enhance e‑commerce search intent recognition and term importance estimation, achieving high accuracy while meeting sub‑10 ms latency requirements.

BERTdeep learninge-commerce
0 likes · 12 min read
Improving Search Intent Recognition and Term Weighting with Deep Learning and Model Distillation at Ctrip
Bilibili Tech
Bilibili Tech
Nov 8, 2022 · Artificial Intelligence

Real-Time Super-Resolution Algorithm for League of Legends S12 Live Streaming

A lightweight real‑time super‑resolution network was created for the 2022 League of Legends S12 World Championship, using pixel‑unshuffle/shuffle, structural re‑parameterization, and a multi‑loss (L1, perceptual, Sobel‑based texture, GAN) training pipeline that upscales 1080p streams to 4K at 75 fps on a V100 GPU, delivering clearer textures and reduced noise while remaining computationally efficient.

Loss Functionsdeep learninggame streaming
0 likes · 10 min read
Real-Time Super-Resolution Algorithm for League of Legends S12 Live Streaming
JD Cloud Developers
JD Cloud Developers
Nov 7, 2022 · Artificial Intelligence

Detecting Time‑Series Anomalies Without Thresholds Using LSTM and Unsupervised Fusion

This article presents a threshold‑free anomaly detection framework for streaming time series that combines an LSTM‑based baseline module with an unsupervised detection module, detailing the architecture, training process, data preprocessing, and experimental results that demonstrate superior accuracy and F1 scores.

LSTMTime SeriesUnsupervised Learning
0 likes · 15 min read
Detecting Time‑Series Anomalies Without Thresholds Using LSTM and Unsupervised Fusion
Model Perspective
Model Perspective
Nov 5, 2022 · Artificial Intelligence

Explore the Most Popular Machine Learning Algorithms and How They Work

This comprehensive guide walks you through the most popular machine learning algorithms, explaining how they are classified by learning style and problem type, and highlighting key examples from supervised, unsupervised, deep learning, ensemble, and many other algorithm families.

Unsupervised Learningdeep learningsupervised learning
0 likes · 11 min read
Explore the Most Popular Machine Learning Algorithms and How They Work