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1959 articles · Page 4 of 20
Lao Guo's Learning Space
Lao Guo's Learning Space
Feb 14, 2025 · Artificial Intelligence

Key AI Concepts Explained: Definition, Large‑Model Role, and Future Implications

The article defines Artificial Intelligence, explains how large models enable computers to mimic human intelligence for tasks and learning, and presents a personal view that machines may eventually surpass humans and evolve into a silicon‑based intelligent life with autonomous will.

AI FundamentalsArtificial IntelligenceLarge Models
0 likes · 2 min read
Key AI Concepts Explained: Definition, Large‑Model Role, and Future Implications
AI Code to Success
AI Code to Success
Feb 11, 2025 · Artificial Intelligence

Unlocking TensorFlow: From Basics to Building Your First Linear Regression Model

This article introduces TensorFlow's core concepts—tensors, computational graphs, variables, and sessions—covers its wide range of AI applications from traditional machine learning to deep learning in NLP and computer vision, and provides a step‑by‑step Python tutorial for implementing a simple linear regression model.

AI TutorialDeep LearningLinear Regression
0 likes · 6 min read
Unlocking TensorFlow: From Basics to Building Your First Linear Regression Model
DataFunSummit
DataFunSummit
Feb 11, 2025 · Information Security

War‑Like Strategies for URL Anti‑Fraud: Threat Analysis, Detection Techniques, and Operational Intelligence

The article examines the growing threat of black‑market malicious websites, outlines a five‑part war‑themed framework for comprehensive opponent analysis, detection strategies across traffic, channel, content and relationship dimensions, and advanced detection models—including fingerprint, text, image, graph, and multimodal approaches—while highlighting the supporting operational and intelligence systems.

Machine Learningfraud detectioninformation security
0 likes · 14 min read
War‑Like Strategies for URL Anti‑Fraud: Threat Analysis, Detection Techniques, and Operational Intelligence
Python Programming Learning Circle
Python Programming Learning Circle
Feb 10, 2025 · Artificial Intelligence

Why Golang Won’t Replace Python: A Comparative Overview for AI Engineers

The article compares Golang and Python for AI development, highlighting Golang’s superior scalability, performance, and concurrency while acknowledging Python’s extensive libraries, community support, and accessibility, and concludes that both languages have distinct strengths rather than one completely supplanting the other.

AIMachine LearningPerformance
0 likes · 7 min read
Why Golang Won’t Replace Python: A Comparative Overview for AI Engineers
Architect's Alchemy Furnace
Architect's Alchemy Furnace
Feb 6, 2025 · Artificial Intelligence

How Knowledge Distillation Powers Efficient Large‑Model Deployment

This article explains how knowledge distillation enables massive AI models to be compressed and deployed efficiently, covering its principles, classification dimensions, implementation steps, innovative practices at DeepSeek, real‑world applications, and future research directions.

Artificial IntelligenceDeepSeekMachine Learning
0 likes · 11 min read
How Knowledge Distillation Powers Efficient Large‑Model Deployment
JD Tech
JD Tech
Feb 5, 2025 · Artificial Intelligence

Tech Insight: Highlights of Ten JD Retail Technology Papers Published in Top AI Conferences (2024)

Tech Insight presents concise overviews of ten JD retail technology papers accepted at top AI conferences in 2024, covering topics such as open‑vocabulary object detection, multi‑scenario ranking, diversity‑aware re‑ranking, a diversified product search dataset, semi‑supervised query classification, plug‑in CTR models, and methods to mitigate LLM hallucinations.

AIE‑commerceMachine Learning
0 likes · 17 min read
Tech Insight: Highlights of Ten JD Retail Technology Papers Published in Top AI Conferences (2024)
php Courses
php Courses
Feb 5, 2025 · Artificial Intelligence

Anomaly Detection and Outlier Handling in PHP Using Machine Learning

This article explains how to detect and handle outliers in data sets using PHP and machine learning techniques, covering statistical Z‑Score detection, Isolation Forest algorithm, and practical code examples for removing or replacing anomalous values to improve data quality and model accuracy.

Isolation ForestMachine LearningPHP
0 likes · 6 min read
Anomaly Detection and Outlier Handling in PHP Using Machine Learning
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Jan 26, 2025 · Big Data

How a FinTech Scaled Its Data Platform with Alibaba Cloud EMR Serverless Spark

Weifin, a fintech innovator, tackled massive data‑scale challenges by adopting Alibaba Cloud EMR Serverless Spark, building a unified Spark‑based platform that supports data collection, lake ingestion, distributed machine‑learning training, and intelligent risk‑control applications, while achieving performance gains, cost reduction, and scalable automation.

FinTechMachine LearningSpark
0 likes · 10 min read
How a FinTech Scaled Its Data Platform with Alibaba Cloud EMR Serverless Spark
Airbnb Technology Team
Airbnb Technology Team
Jan 24, 2025 · Artificial Intelligence

Chronon — An Open-Source Framework for Production-Level Feature Engineering in Machine Learning

Chronon is an open‑source framework that centralizes feature definitions to guarantee training‑inference consistency, eliminates complex ETL pipelines, and supports real‑time and batch processing across diverse data sources, cutting feature‑development cycles from months to under a week, as demonstrated by Airbnb’s 40,000‑feature deployment.

ChrononHiveMachine Learning
0 likes · 10 min read
Chronon — An Open-Source Framework for Production-Level Feature Engineering in Machine Learning
Test Development Learning Exchange
Test Development Learning Exchange
Jan 22, 2025 · Artificial Intelligence

Comprehensive Guide to Python Data Science Libraries with Code Examples

This article presents a concise tutorial on essential Python data science libraries, covering data cleaning with Pandas, numerical analysis with NumPy and SciPy, visualization with Matplotlib and Seaborn, machine learning with scikit‑learn, NLP with NLTK and spaCy, time‑series modeling, image processing, database access, and parallel computing, each illustrated with ready‑to‑run code examples.

Machine LearningNLPParallel Computing
0 likes · 7 min read
Comprehensive Guide to Python Data Science Libraries with Code Examples
AI Large Model Application Practice
AI Large Model Application Practice
Jan 20, 2025 · Artificial Intelligence

How Embeddings Transform Simple Character Codes into Powerful Vectors for LLMs

This article explains how embeddings convert basic character indices into high‑dimensional vectors, describes their training via gradient descent, introduces the embedding matrix, and shows how these vectors enable modern language models to capture semantic relationships and be reused across tasks.

LLMMachine Learningembeddings
0 likes · 8 min read
How Embeddings Transform Simple Character Codes into Powerful Vectors for LLMs
Test Development Learning Exchange
Test Development Learning Exchange
Jan 17, 2025 · Artificial Intelligence

Essential Python Libraries for Data Processing, Visualization, and Machine Learning

This article introduces ten essential Python libraries—including SciPy, Matplotlib, Plotly, Scikit‑learn, TensorFlow, spaCy, BeautifulSoup, OpenPyXL, Feather/Parquet, and SQLAlchemy—detailing their primary uses for scientific computing, visualization, machine learning, deep learning, NLP, web scraping, Excel handling, efficient data storage, and ORM, with practical code examples.

Data ProcessingLibrariesMachine Learning
0 likes · 8 min read
Essential Python Libraries for Data Processing, Visualization, and Machine Learning
Kuaishou Tech
Kuaishou Tech
Jan 17, 2025 · Artificial Intelligence

Kuaishou Achieves 7 Papers Accepted at AAAI 2025

Kuaishou has achieved a significant milestone with 7 papers accepted at AAAI 2025, covering diverse AI research areas including video processing, recommendation systems, and image restoration, demonstrating the company's strong research capabilities in artificial intelligence.

AAAI 2025Artificial IntelligenceKuaishou
0 likes · 10 min read
Kuaishou Achieves 7 Papers Accepted at AAAI 2025
Architects' Tech Alliance
Architects' Tech Alliance
Jan 12, 2025 · Artificial Intelligence

Explore the Full AI Expert Roadmap: From Data Science to Big Data Engineering

The AI Expert Roadmap on GitHub offers a comprehensive, interactive guide covering data‑science fundamentals, machine‑learning algorithms, deep‑learning techniques, data‑engineering pipelines, and big‑data architectures, with linked resources, up‑to‑date references, and practical tool recommendations for aspiring AI professionals.

AIBig DataDeep Learning
0 likes · 6 min read
Explore the Full AI Expert Roadmap: From Data Science to Big Data Engineering
Test Development Learning Exchange
Test Development Learning Exchange
Jan 12, 2025 · Fundamentals

Popular Python Libraries Across Various Domains

This article provides an overview of widely used Python libraries spanning web development, GUI programming, web scraping, game development, multimedia processing, security, cloud computing, data visualization, version control, parallel computing, natural language processing, and IoT, highlighting each library's primary purpose and typical use cases.

Cloud ComputingLibrariesMachine Learning
0 likes · 6 min read
Popular Python Libraries Across Various Domains
Java Tech Enthusiast
Java Tech Enthusiast
Jan 12, 2025 · Artificial Intelligence

AgiBot World: Large-Scale Multi‑Robot Embodied AI Dataset Release

AgiBot World, the first globally‑scale robot dataset captured in fully realistic environments, provides ten‑fold longer trajectories and hundred‑fold greater scene coverage than prior collections, featuring over 80 daily‑life skills recorded by a 32‑DOF robot with advanced sensing, and includes rigorous multi‑stage quality control with future releases slated to reach a million runs and millions of simulated trajectories.

Embodied AILarge DatasetMachine Learning
0 likes · 9 min read
AgiBot World: Large-Scale Multi‑Robot Embodied AI Dataset Release
Test Development Learning Exchange
Test Development Learning Exchange
Jan 9, 2025 · Artificial Intelligence

Numerical Computing, Data Analysis, Machine Learning, and Data Visualization with Python Libraries

This article presents practical examples and code snippets for using Python libraries such as NumPy, Pandas, SciPy, Statsmodels, Dask, Vaex, Modin, CuPy, Scikit‑learn, TensorFlow, PyTorch, XGBoost, LightGBM, and various visualization tools to perform efficient numerical computation, data processing, machine‑learning modeling, and interactive visual analytics.

Machine LearningNumPyPython
0 likes · 22 min read
Numerical Computing, Data Analysis, Machine Learning, and Data Visualization with Python Libraries
Meituan Technology Team
Meituan Technology Team
Jan 9, 2025 · Artificial Intelligence

Roundtable Discussion on Embodied Intelligence at Meituan Robot Research Institute 2024 Academic Annual Meeting

At Meituan Robot Research Institute’s 2024 academic meeting, a diverse panel of scholars and entrepreneurs debated the relative importance of hardware and algorithms for embodied intelligence, identified near‑term market niches such as hazardous‑environment and household assistance, projected rapid scaling to thousands of autonomous humanoids, and highlighted safety, mass‑market adoption, and ethical considerations as key challenges.

Artificial IntelligenceEmbodied AIIndustry Applications
0 likes · 27 min read
Roundtable Discussion on Embodied Intelligence at Meituan Robot Research Institute 2024 Academic Annual Meeting
AI Large Model Application Practice
AI Large Model Application Practice
Jan 9, 2025 · Artificial Intelligence

How Does Gradient Descent Train a Neural Network? A Step‑by‑Step Guide

This article walks through the complete training cycle of a simple neural network—from random weight initialization and forward propagation with labeled data, through loss calculation and gradient‑based weight updates, to iterative epochs, average loss, and practical issues like gradient explosion and vanishing.

AIMachine Learninggradient descent
0 likes · 11 min read
How Does Gradient Descent Train a Neural Network? A Step‑by‑Step Guide
Baidu Geek Talk
Baidu Geek Talk
Jan 6, 2025 · Information Security

MarkupLM-based Detection of Malicious Content Scraping

The article presents a MarkupLM‑based approach that enriches BERT with XPath embeddings to jointly model webpage text and structure, enabling site‑level detection of malicious content‑scraping pages that bypass traditional rule‑based filters and demonstrating the critical role of structural cues in improving spam classification accuracy.

Machine LearningMarkupLMXPath embedding
0 likes · 16 min read
MarkupLM-based Detection of Malicious Content Scraping
DataFunSummit
DataFunSummit
Jan 2, 2025 · Operations

Data‑Driven Inventory Selection and Allocation Algorithms for JD Retail Supply Chain

This article presents JD Retail's award‑winning, data‑driven inventory selection and allocation framework that combines machine‑learning‑based demand forecasting, heuristic selection algorithms, and an end‑to‑end multi‑task learning model to improve fulfillment rates, reduce stock‑out loss, and lower inventory transfer costs in a large‑scale e‑commerce supply chain.

Machine LearningSupply Chaine‑commerce
0 likes · 21 min read
Data‑Driven Inventory Selection and Allocation Algorithms for JD Retail Supply Chain
Python Programming Learning Circle
Python Programming Learning Circle
Dec 31, 2024 · Fundamentals

Top 10 Essential Python Libraries and How to Use Them

An overview of ten indispensable Python libraries—including Requests, NumPy, Pandas, Matplotlib, Flask, Django, PyTorch, OpenCV, Scikit‑learn, and BeautifulSoup—detailing their core features, typical use cases, common pitfalls, and example code snippets to help developers quickly adopt them in projects.

LibrariesMachine Learningrequests
0 likes · 8 min read
Top 10 Essential Python Libraries and How to Use Them
IT Services Circle
IT Services Circle
Dec 31, 2024 · Artificial Intelligence

Understanding Linear Regression, Loss Functions, and Gradient Descent: A Conversational Guide

This article uses a dialogue format to introduce the fundamentals of linear regression, explain how loss functions such as mean squared error quantify prediction errors, and describe gradient descent as an iterative optimization technique for finding the best model parameters, illustrated with simple numeric examples and visual aids.

AI basicsLinear RegressionMachine Learning
0 likes · 13 min read
Understanding Linear Regression, Loss Functions, and Gradient Descent: A Conversational Guide
JD Tech Talk
JD Tech Talk
Dec 30, 2024 · Operations

Data‑Driven Inventory Selection and Allocation Algorithms for JD Retail Supply Chain

JD Retail’s supply‑chain team won the Daniel H. Wagner Prize by developing data‑driven inventory selection and allocation algorithms that optimize two‑tier RDC/FDC networks, improve order fulfillment rates, reduce stock‑out losses and costs, and have been deployed at scale across millions of orders.

Machine Learninginventory optimizationoperations research
0 likes · 21 min read
Data‑Driven Inventory Selection and Allocation Algorithms for JD Retail Supply Chain
Tencent Advertising Technology
Tencent Advertising Technology
Dec 27, 2024 · Artificial Intelligence

Tencent's AutoML Research for Advertising Recommendation Systems

This article outlines Tencent's AutoML research, presenting several recent papers that introduce novel neural architecture search, feature selection, pooling, embedding size, and hyper‑parameter optimization techniques to improve the efficiency, accuracy, and scalability of large‑scale advertising recommendation systems.

AutoMLEmbedding Size SearchMachine Learning
0 likes · 10 min read
Tencent's AutoML Research for Advertising Recommendation Systems
JD Retail Technology
JD Retail Technology
Dec 27, 2024 · Industry Insights

How JD’s Data‑Driven Inventory Selection Boosted Fulfillment Efficiency

This article details JD Retail's award‑winning, data‑driven inventory selection and allocation algorithms, explains their mathematical models, heuristic and end‑to‑end learning solutions, presents experimental results on real‑world data, and quantifies the operational gains achieved after deployment.

Machine LearningSupply Chaine‑commerce
0 likes · 21 min read
How JD’s Data‑Driven Inventory Selection Boosted Fulfillment Efficiency
Alimama Tech
Alimama Tech
Dec 25, 2024 · Artificial Intelligence

Contextual Generative Auction with Permutation-level Externalities for Online Advertising

The paper introduces Contextual Generative Auction (CGA), a generative framework that directly optimizes ad placements while modeling permutation‑level externalities, decouples allocation from payment learning, and achieves near‑optimal Myerson‑style outcomes, delivering up to 3.2% higher RPM, 1.4% more CTR, 6.4% GMV growth, and 3.5% increased advertiser ROI in large‑scale Taobao experiments.

ExternalitiesGenerative ModelsMachine Learning
0 likes · 18 min read
Contextual Generative Auction with Permutation-level Externalities for Online Advertising
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Dec 18, 2024 · Artificial Intelligence

Personalized Video Streaming and Playback Technology: Methods, Architecture, and Optimization

This article presents a comprehensive study of personalized short‑video streaming and playback, detailing the limitations of traditional audio‑video pipelines, introducing a decision‑theoretic framework that models user, item, and context features, and describing system components such as personalized streaming, quality scheduling, on‑demand delivery, user‑item aware encoding, and resource allocation, all validated through extensive online experiments that demonstrate significant business and performance gains.

CDN optimizationContent DeliveryMachine Learning
0 likes · 52 min read
Personalized Video Streaming and Playback Technology: Methods, Architecture, and Optimization
dbaplus Community
dbaplus Community
Dec 16, 2024 · Operations

How Qunar Built a 5‑Million‑Metric Radar System to Cut Ticket Failures by 87%

This article details the design, implementation, and results of Qunar's intelligent ticket‑monitoring Radar system, covering the business need, architecture, anomaly‑detection algorithms, test‑set construction, parameter tuning, and the achieved 87% detection accuracy with future plans for large‑model integration.

Machine LearningReliabilityanomaly detection
0 likes · 17 min read
How Qunar Built a 5‑Million‑Metric Radar System to Cut Ticket Failures by 87%
Python Programming Learning Circle
Python Programming Learning Circle
Dec 13, 2024 · Artificial Intelligence

Batch Image Translation Demo Using Youdao OCR API with Python

This article demonstrates how to build a Python desktop application that batch‑processes cosmetic product images, sends them to Youdao's OCR translation service, and displays the translated text, covering API preparation, request parameters, signature generation, and full source code.

Batch ProcessingMachine LearningOCR
0 likes · 12 min read
Batch Image Translation Demo Using Youdao OCR API with Python
php Courses
php Courses
Dec 13, 2024 · Artificial Intelligence

OpenAI Day 2: Launch of Reinforcement Learning from Human Feedback (RLHF) Model for Enhanced AI Capabilities

OpenAI announced on the second day of its twelve‑day event that it has integrated Reinforcement Learning from Human Feedback (RLHF) into its 001 series models, demonstrating significant reasoning improvements, showcasing legal and medical use cases, and promising a public release early next year.

AI Model Fine-tuningMachine LearningOpenAI
0 likes · 5 min read
OpenAI Day 2: Launch of Reinforcement Learning from Human Feedback (RLHF) Model for Enhanced AI Capabilities
iKang Technology Team
iKang Technology Team
Dec 12, 2024 · Mobile Development

How to Build AI-Powered iOS Apps with Core ML, Create ML, and Vision

This article explains how to integrate artificial‑intelligence capabilities such as image classification, speech‑to‑text, and facial‑expression analysis into iOS applications using Apple’s Core ML, Create ML, and Vision frameworks, providing step‑by‑step guidance, code samples, and future‑direction insights.

Core MLCreate MLMachine Learning
0 likes · 16 min read
How to Build AI-Powered iOS Apps with Core ML, Create ML, and Vision
DevOps
DevOps
Dec 11, 2024 · Artificial Intelligence

Five Levels of AI Development and the AGILE Five‑Step Methodology for Enterprise AIGC Adoption

The article outlines OpenAI's five AI maturity levels—from chatbots to organizational AI—examines the challenges Chinese enterprises face when adopting large‑model technologies, and presents the AGILE five‑step framework (Awareness, Gauge, Inception, Ladder, Expansion) together with current best practices and job‑market impacts.

AIAIGCArtificial Intelligence
0 likes · 12 min read
Five Levels of AI Development and the AGILE Five‑Step Methodology for Enterprise AIGC Adoption
Python Programming Learning Circle
Python Programming Learning Circle
Dec 11, 2024 · Artificial Intelligence

Key Python 3.13 Features Boosting AI and Machine Learning Performance

Python 3.13 introduces experimental free‑threading, a JIT compiler, enhanced type system, asyncio improvements, new standard‑library modules, security updates, and expanded platform support, all of which aim to increase performance, productivity, and reliability for machine‑learning and artificial‑intelligence developers.

AIMachine LearningPerformance
0 likes · 22 min read
Key Python 3.13 Features Boosting AI and Machine Learning Performance
DevOps
DevOps
Dec 8, 2024 · Artificial Intelligence

Understanding Fine-Tuning in Machine Learning: Concepts, Importance, Steps, and Applications

This article explains fine‑tuning in machine learning, covering its definition, why it matters, the role of pre‑trained models, detailed step‑by‑step procedures, advantages, and diverse applications such as NLP, computer vision, speech and finance, with practical examples like face recognition and object detection.

AI ApplicationsMachine LearningModel Optimization
0 likes · 16 min read
Understanding Fine-Tuning in Machine Learning: Concepts, Importance, Steps, and Applications
Baobao Algorithm Notes
Baobao Algorithm Notes
Dec 7, 2024 · Artificial Intelligence

What Is Reinforcement Fine-Tuning (RFT) and How Does It Supercharge LLMs?

Reinforcement Fine-Tuning (RFT) combines supervised fine‑tuning with reinforcement learning to teach large language models to reason more effectively, using separate training and validation datasets, graders, and PPO optimization, and has shown superior performance on tasks like gene prediction and math reasoning compared to standard SFT.

AILarge Language ModelsMachine Learning
0 likes · 8 min read
What Is Reinforcement Fine-Tuning (RFT) and How Does It Supercharge LLMs?
AI Product Manager Community
AI Product Manager Community
Dec 7, 2024 · Artificial Intelligence

How Reinforcement Fine-Tuning (RFT) Is Redefining AI Customization

Reinforcement Fine-Tuning (RFT), unveiled at OpenAI’s 12‑day launch, introduces a feedback‑loop approach that transforms generic models into specialized experts using reinforcement learning, small data, and domain‑specific scorers, offering product managers a powerful tool for rapid, cost‑effective AI customization across industries.

AI CustomizationMachine LearningReinforcement Learning
0 likes · 7 min read
How Reinforcement Fine-Tuning (RFT) Is Redefining AI Customization
Test Development Learning Exchange
Test Development Learning Exchange
Dec 6, 2024 · Artificial Intelligence

Using pytesseract and Pillow for OCR: Installation, Configuration, and Accuracy Improvement Techniques

This guide explains how to install Tesseract OCR and the Python libraries pytesseract and Pillow, configure the engine path, perform image-to-text extraction with example code, and apply various preprocessing, detection, and post‑processing methods to significantly improve OCR accuracy.

Machine LearningOCRPython
0 likes · 8 min read
Using pytesseract and Pillow for OCR: Installation, Configuration, and Accuracy Improvement Techniques
AntTech
AntTech
Dec 6, 2024 · Artificial Intelligence

Nimbus: Secure and Efficient Two‑Party Inference for Transformers

The paper introduces Nimbus, a two‑party privacy‑preserving inference framework for Transformer models that leverages a client‑side outer‑product linear‑layer protocol and distribution‑aware polynomial approximations for non‑linear layers, achieving up to five‑fold speedups with negligible accuracy loss.

Homomorphic EncryptionMachine LearningTransformer
0 likes · 15 min read
Nimbus: Secure and Efficient Two‑Party Inference for Transformers
DevOps
DevOps
Dec 5, 2024 · Artificial Intelligence

A Brief History of Artificial Intelligence: From McCulloch‑Pitts Neurons to GPT‑4

This article traces the evolution of artificial intelligence from the 1943 McCulloch‑Pitts neuron model through key milestones such as Turing's test, the Dartmouth conference, the rise of neural networks, deep learning breakthroughs, and recent large language models like GPT‑4, illustrating the field's rapid progress.

Artificial IntelligenceGPTMachine Learning
0 likes · 7 min read
A Brief History of Artificial Intelligence: From McCulloch‑Pitts Neurons to GPT‑4
Test Development Learning Exchange
Test Development Learning Exchange
Dec 5, 2024 · Artificial Intelligence

End-to-End House Prices Prediction Project: Data Collection, Preprocessing, Modeling, Evaluation, and Deployment with Python

This tutorial walks through a complete house price prediction project, covering data collection from Kaggle, preprocessing with pandas and scikit‑learn, model training using RandomForestRegressor, evaluation, and deployment of a Flask API for real‑time predictions, providing full code examples.

FlaskMachine LearningModel deployment
0 likes · 9 min read
End-to-End House Prices Prediction Project: Data Collection, Preprocessing, Modeling, Evaluation, and Deployment with Python
AntTech
AntTech
Dec 5, 2024 · Artificial Intelligence

Simplifying Deep Learning: Research Overview by Prof. Yao Quanming

Prof. Yao Quanming presents a comprehensive overview of his research on simplifying deep learning, discussing scaling laws, data, compute and trust bottlenecks, and proposing minimalist approaches in model design, training, and interpretability, with a focus on drug interaction prediction using graph neural networks.

Deep LearningMachine Learningdrug interaction prediction
0 likes · 17 min read
Simplifying Deep Learning: Research Overview by Prof. Yao Quanming
php Courses
php Courses
Dec 5, 2024 · Artificial Intelligence

Integrating Artificial Intelligence with PHP for Modern Web Development

This article explores how artificial intelligence is reshaping modern web development and details how PHP can integrate AI through libraries, APIs, and data processing, highlighting use cases such as recommendation engines, chatbots, and content generation, while also discussing benefits and challenges of such integration.

API IntegrationMachine LearningPHP
0 likes · 7 min read
Integrating Artificial Intelligence with PHP for Modern Web Development
Model Perspective
Model Perspective
Dec 5, 2024 · Artificial Intelligence

Choosing the Right Activation Function: Pros, Cons, and Best Practices

Activation functions are crucial for neural networks, providing non‑linearity, normalization, and gradient flow; this article reviews common functions such as Sigmoid, Tanh, ReLU, Leaky ReLU, ELU, Noisy ReLU, Softmax, and Swish, comparing their characteristics, advantages, drawbacks, and guidance for selecting the appropriate one.

Machine LearningModel Optimizationactivation functions
0 likes · 10 min read
Choosing the Right Activation Function: Pros, Cons, and Best Practices
php Courses
php Courses
Dec 2, 2024 · Artificial Intelligence

Anomaly Detection and Outlier Handling in PHP Using Z-Score and Isolation Forest

This article explains how to detect and handle outliers in data using PHP, covering statistical Z-Score and Isolation Forest methods, and provides sample code for both detection and subsequent removal or replacement of anomalous values to improve data quality and model accuracy.

Isolation ForestMachine LearningPHP
0 likes · 7 min read
Anomaly Detection and Outlier Handling in PHP Using Z-Score and Isolation Forest
Model Perspective
Model Perspective
Dec 2, 2024 · Fundamentals

What Is the Beta Distribution and Why It Matters in A/B Testing?

The Beta distribution is a flexible probability model defined on the interval [0,1] with two shape parameters that control its form, offering useful properties such as mean and variance, and is widely applied in A/B testing, risk assessment, and machine‑learning tasks to model proportions and uncertainties.

A/B testingMachine Learningbeta distribution
0 likes · 5 min read
What Is the Beta Distribution and Why It Matters in A/B Testing?
JavaEdge
JavaEdge
Dec 1, 2024 · Artificial Intelligence

Exploring the Limits and Benchmarks of Qwen’s QwQ‑32B‑Preview AI Model

QwQ‑32B‑Preview, an experimental AI model from the Qwen team, showcases strong reasoning in math and programming while facing challenges like language switching, inference loops, safety concerns, and variable capabilities across domains, with benchmark scores ranging from 50% to over 90% on tests such as GPQA, AIME, MATH‑500, and LiveCodeBench.

AI BenchmarkLLMMachine Learning
0 likes · 7 min read
Exploring the Limits and Benchmarks of Qwen’s QwQ‑32B‑Preview AI Model
Test Development Learning Exchange
Test Development Learning Exchange
Nov 30, 2024 · Artificial Intelligence

Popular Python Libraries for Image Processing with Installation Commands and Code Samples

This article introduces ten widely used Python image‑processing libraries—including Pillow, OpenCV, scikit‑image, imageio, mahotas, SimpleITK, imgaug, face_recognition, Pyradiomics, and tqdm—provides brief descriptions, pip installation commands, and runnable code examples to help developers choose the right tool for their computer‑vision tasks.

Machine LearningOpenCVPython
0 likes · 10 min read
Popular Python Libraries for Image Processing with Installation Commands and Code Samples
HyperAI Super Neural
HyperAI Super Neural
Nov 28, 2024 · Artificial Intelligence

Why Implementing AI for Science Feels More Rewarding – Insights from Prof. Hong Liang

In an in‑depth interview, Prof. Hong Liang of Shanghai Jiao Tong University discusses the evolution of AI for Science, the challenges of turning research breakthroughs into real‑world protein‑engineering solutions, the importance of industry‑academia collaboration, and how luck, timing, and focused problem definition drive successful AI adoption.

AI for ScienceAlphaFoldBiotech
0 likes · 13 min read
Why Implementing AI for Science Feels More Rewarding – Insights from Prof. Hong Liang
Python Programming Learning Circle
Python Programming Learning Circle
Nov 27, 2024 · Artificial Intelligence

Open‑Source Bird Species Detection with TensorFlow, MobileNet V2 and OpenCV

A hobbyist builds a Python‑based bird‑recognition system using TensorFlow's SSD OpenImages model, a MobileNet V2 classifier from TensorFlow Hub, and OpenCV, shares the open‑source code on GitHub, discusses early results, challenges like accuracy and non‑maximum suppression, and outlines future improvements.

Bird DetectionMachine LearningOpenCV
0 likes · 8 min read
Open‑Source Bird Species Detection with TensorFlow, MobileNet V2 and OpenCV
Test Development Learning Exchange
Test Development Learning Exchange
Nov 26, 2024 · Artificial Intelligence

Comprehensive Python Tutorial for Data Preprocessing, Feature Engineering, Model Training, Evaluation, and Deployment

This tutorial walks through consolidating the first ten days of learning by covering data preprocessing, feature engineering, model training with linear regression, decision tree, and random forest, model evaluation using cross‑validation, and finally saving and loading the best model, all illustrated with complete Python code examples.

Machine LearningPythondata preprocessing
0 likes · 9 min read
Comprehensive Python Tutorial for Data Preprocessing, Feature Engineering, Model Training, Evaluation, and Deployment
DataFunTalk
DataFunTalk
Nov 25, 2024 · Artificial Intelligence

2024 AI Development Report Summary by Fei‑Fei Li’s Team

The 2024 AI Development Report by Fei‑Fei Li’s team highlights rapid progress in model capabilities, rising training costs, dominant contributions from the US, China and Europe, emerging reliability challenges, and the broad economic, medical, and educational impacts of artificial intelligence.

2024AIEconomic Impact
0 likes · 12 min read
2024 AI Development Report Summary by Fei‑Fei Li’s Team
Test Development Learning Exchange
Test Development Learning Exchange
Nov 22, 2024 · Artificial Intelligence

Introduction to Data Modeling with Scikit-Learn

This article provides a comprehensive guide to using Scikit-Learn for data modeling, covering linear regression and decision tree algorithms, including data preparation, model training, evaluation metrics, and visualization techniques for predictive analysis.

Decision TreesMachine LearningPython
0 likes · 4 min read
Introduction to Data Modeling with Scikit-Learn
Python Programming Learning Circle
Python Programming Learning Circle
Nov 22, 2024 · Artificial Intelligence

Introducing the Python "communities" Library for Graph Clustering and Visualization

This article introduces the Python "communities" library, explains its support for multiple graph clustering algorithms such as Louvain and Girvan‑Newman, demonstrates how to import algorithms, build adjacency matrices, visualize communities, create animation of the clustering process, and provides author and resource information.

Louvain AlgorithmMachine Learningcommunity-detection
0 likes · 7 min read
Introducing the Python "communities" Library for Graph Clustering and Visualization
Cognitive Technology Team
Cognitive Technology Team
Nov 20, 2024 · Artificial Intelligence

Fundamentals and Implementation of Neural Networks and Transformers with PyTorch Examples

This article provides a comprehensive overview of neural network fundamentals, loss functions, activation functions, embedding techniques, attention mechanisms, multi‑head attention, residual networks, and the full Transformer encoder‑decoder architecture, illustrated with detailed PyTorch code and a practical MiniRBT fine‑tuning case for Chinese text classification.

AIMachine LearningPyTorch
0 likes · 49 min read
Fundamentals and Implementation of Neural Networks and Transformers with PyTorch Examples
58UXD
58UXD
Nov 20, 2024 · Artificial Intelligence

How AI Is Transforming UI Design: Benefits, Challenges, and Real‑World Tools

This article examines how artificial intelligence reshapes UI design by boosting efficiency, enabling personalized experiences, and supporting data‑driven decisions, while also confronting limits such as understanding complex business logic, lacking creative nuance, and adapting to industry‑specific standards, illustrated through the Uizard tool.

AIMachine LearningPrototype
0 likes · 6 min read
How AI Is Transforming UI Design: Benefits, Challenges, and Real‑World Tools
Alimama Tech
Alimama Tech
Nov 13, 2024 · Artificial Intelligence

DeepString: Alibaba's Anti‑Fraud Platform Using Large Models for Real‑Time Traffic Detection

Alibaba's anti-fraud platform DeepString uses large unsupervised models to detect abnormal traffic in real time across multiple advertising products, combining a foundation model for event mining, anomaly measurement, and an alignment model for online filtering, reducing reliance on manual labeling and domain expertise.

Large ModelsMachine LearningRisk Management
0 likes · 19 min read
DeepString: Alibaba's Anti‑Fraud Platform Using Large Models for Real‑Time Traffic Detection
Tencent Advertising Technology
Tencent Advertising Technology
Nov 8, 2024 · Artificial Intelligence

Optimizing Real-Time Bidding: Machine Learning Approaches for Bid Shading and Winning Price Prediction

This article explores advanced machine learning techniques for optimizing bid shading in real-time advertising auctions, introducing a mixed censorship multi-task learning framework and a cost-effective active learning strategy to accurately predict winning price distributions and overcome sample selection bias.

Active LearningAuction MechanismsBid Shading
0 likes · 16 min read
Optimizing Real-Time Bidding: Machine Learning Approaches for Bid Shading and Winning Price Prediction
JD Cloud Developers
JD Cloud Developers
Nov 6, 2024 · Artificial Intelligence

How Data Science Powers JD’s Logistics, Finance, and Healthcare Innovations

This article explains the fundamentals of data science, its key components, and showcases how JD applies it across e‑commerce, finance, healthcare, and logistics, while also reviewing past innovations, common project pitfalls, and future directions such as quantum computing and supply‑chain digital twins.

Artificial IntelligenceHealthcareMachine Learning
0 likes · 21 min read
How Data Science Powers JD’s Logistics, Finance, and Healthcare Innovations
Architects' Tech Alliance
Architects' Tech Alliance
Nov 1, 2024 · Artificial Intelligence

Master Machine Learning: Core Concepts, Algorithms, and Evaluation Explained

This comprehensive guide walks through the fundamentals of artificial intelligence, machine learning and deep learning, explains the three essential elements of ML, outlines its historical milestones, details core techniques, workflow, key terminology, algorithm families, model evaluation metrics, bias‑variance trade‑offs, validation strategies, and practical model‑selection guidelines.

AlgorithmsArtificial IntelligenceMachine Learning
0 likes · 19 min read
Master Machine Learning: Core Concepts, Algorithms, and Evaluation Explained
php Courses
php Courses
Oct 23, 2024 · Artificial Intelligence

Data Dimensionality Reduction and Feature Extraction with PHP

This article explains the concepts of data dimensionality reduction and feature extraction in machine learning and demonstrates how to implement them in PHP using the PHP‑ML library, including installation, data preprocessing, PCA-based reduction, and feature extraction with token vectorization and TF‑IDF.

Machine LearningPCAPHP-ML
0 likes · 5 min read
Data Dimensionality Reduction and Feature Extraction with PHP
AntTech
AntTech
Oct 16, 2024 · Artificial Intelligence

Subgraph Retrieval Enhanced by Graph-Text Alignment for Commonsense Question Answering (SEPTA Framework)

The paper introduces the SEPTA framework, which converts knowledge graphs into a subgraph vector database and employs graph‑text alignment via bidirectional contrastive learning to improve subgraph retrieval and knowledge fusion for commonsense question answering, demonstrating strong performance across five benchmark datasets.

Machine LearningSEPTAcommonsense QA
0 likes · 4 min read
Subgraph Retrieval Enhanced by Graph-Text Alignment for Commonsense Question Answering (SEPTA Framework)
Baobao Algorithm Notes
Baobao Algorithm Notes
Oct 15, 2024 · Artificial Intelligence

How DPO Simplifies RLHF: A Deep Dive into Direct Preference Optimization

This article breaks down how Direct Preference Optimization (DPO) mathematically reduces the two‑stage RLHF pipeline into a single‑stage SFT process, explains the underlying loss transformations, and discusses DPO's practical limitations and trade‑offs for large language model alignment.

DPODirect Preference OptimizationMachine Learning
0 likes · 9 min read
How DPO Simplifies RLHF: A Deep Dive into Direct Preference Optimization
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Oct 11, 2024 · Artificial Intelligence

Harmonized Speculative Sampling (HASS): Aligning Training and Decoding for Efficient Large Language Model Inference

HASS aligns training and decoding contexts and objectives for speculative sampling, using harmonized objective distillation and multi-step context alignment, achieving 2.81–4.05× speedup and 8%–20% improvement over EAGLE‑2 while preserving generation quality in real-world deployments at Xiaohongshu.

AIHASSInference Acceleration
0 likes · 11 min read
Harmonized Speculative Sampling (HASS): Aligning Training and Decoding for Efficient Large Language Model Inference
Architecture Development Notes
Architecture Development Notes
Oct 11, 2024 · Artificial Intelligence

Can Rust Replace Python for Data Science? Exploring Performance and Safety

While Python dominates data analysis and machine learning with its ease of use, Rust offers memory safety and near‑C performance; this article examines their respective strengths, the challenges of rewriting the Python interpreter in Rust, and how combining both can boost library speed and reliability.

Machine LearningPerformancePython
0 likes · 6 min read
Can Rust Replace Python for Data Science? Exploring Performance and Safety
DevOps
DevOps
Oct 8, 2024 · Artificial Intelligence

Top 20+ Retrieval‑Augmented Generation (RAG) Interview Questions and Answers

This article presents over twenty essential Retrieval‑Augmented Generation (RAG) interview questions with detailed answers, covering fundamentals, applications, architecture, training, limitations, ethical considerations, and integration, offering AI enthusiasts and job candidates a comprehensive guide to mastering RAG concepts.

AI InterviewMachine LearningNLP
0 likes · 15 min read
Top 20+ Retrieval‑Augmented Generation (RAG) Interview Questions and Answers
Python Programming Learning Circle
Python Programming Learning Circle
Oct 7, 2024 · Fundamentals

50 Classic Python Libraries You Can Master Quickly

This article presents a curated list of fifty essential Python libraries spanning data analysis, scientific computing, visualization, machine learning, web development, database access, testing, and utilities, providing brief descriptions to help developers quickly identify and master the most useful tools in the Python ecosystem.

LibrariesMachine LearningWeb Development
0 likes · 7 min read
50 Classic Python Libraries You Can Master Quickly
YiSu Grain
YiSu Grain
Sep 29, 2024 · Artificial Intelligence

Finding the ‘Heavenly Path’ of Data Points: A Linear Regression Walkthrough

This article walks through linear regression by visualizing scattered data points, defining the line y = ax + b, deriving the mean‑squared‑error cost function, computing its gradients with the chain rule, and implementing gradient descent in Python to find the optimal parameters.

Linear RegressionMachine LearningPython
0 likes · 11 min read
Finding the ‘Heavenly Path’ of Data Points: A Linear Regression Walkthrough
Zhuanzhuan Tech
Zhuanzhuan Tech
Sep 26, 2024 · Artificial Intelligence

Pricing Strategy and Model Evolution for Second‑Hand Phone Auctions in ZhaiZhai TOB Marketplace

This article examines the characteristics of ZhaiZhai's B2B auction scenario, defines core pricing metrics, presents a step‑by‑step methodology for determining optimal starting prices, reviews early practices and their shortcomings, and details the current modular machine‑learning model architecture that improves transaction rates and reduces price premiums for second‑hand smartphones.

AlgorithmE‑commerceMachine Learning
0 likes · 29 min read
Pricing Strategy and Model Evolution for Second‑Hand Phone Auctions in ZhaiZhai TOB Marketplace
Ctrip Technology
Ctrip Technology
Sep 23, 2024 · Frontend Development

Intelligent Alert Attribution System for Ctrip Hotel Frontend: Design, Implementation, and Outcomes

This article details the design and deployment of an intelligent alert attribution system for Ctrip Hotel's front‑end, describing the background challenges, the unified data pool, weighted alert rules, three attribution algorithms, achieved improvements in accuracy and troubleshooting speed, and future enhancement plans.

AlertAttributionData Pipeline
0 likes · 18 min read
Intelligent Alert Attribution System for Ctrip Hotel Frontend: Design, Implementation, and Outcomes
Data Thinking Notes
Data Thinking Notes
Sep 19, 2024 · Artificial Intelligence

Why AI Has Only a Seven-Year History—and What AI+ Means for the Future

In this speech, Wang Jian reflects on the evolution of artificial intelligence, arguing that modern AI is fundamentally different from its early concepts, emphasizing the pivotal roles of data, models, and infrastructure, and exploring the transformative impact of AI+, transformers, and cloud platforms on future innovation.

AI infrastructureAI+Artificial Intelligence
0 likes · 18 min read
Why AI Has Only a Seven-Year History—and What AI+ Means for the Future
DataFunSummit
DataFunSummit
Sep 18, 2024 · Artificial Intelligence

Multi‑Scenario Modeling for NetEase Cloud Music Recommendation: Architecture, Challenges, and Results

This article presents NetEase Cloud Music's multi‑scenario recommendation modeling work, covering background, overall system architecture, key modules such as unified and private domain networks, modeling objectives and difficulties, experimental results, future outlook, and a detailed Q&A session.

AIMachine LearningNetEase Cloud Music
0 likes · 13 min read
Multi‑Scenario Modeling for NetEase Cloud Music Recommendation: Architecture, Challenges, and Results
21CTO
21CTO
Sep 13, 2024 · Artificial Intelligence

Boost Your Development Workflow: 7 AI Tools Every Developer Should Try

Discover seven AI-powered tools—including GitHub Copilot, Tabnine, ChatGPT, Figma plugins, DALL·E, AI testing suites, and Code Snippets AI—that can streamline coding, design, and testing, helping developers work faster, reduce repetitive tasks, and focus on creative problem‑solving.

AI toolsMachine LearningTesting automation
0 likes · 8 min read
Boost Your Development Workflow: 7 AI Tools Every Developer Should Try
DataFunSummit
DataFunSummit
Sep 12, 2024 · Cloud Native

Design and Implementation of a Next‑Generation Multi‑Protocol Unstructured Storage System for Machine Learning

This article presents the challenges of storing massive machine‑learning datasets, evaluates existing storage solutions, and details the design of OrangeFS—a cloud‑native, multi‑protocol, multi‑tenant unstructured storage system that integrates object and file interfaces, optimizes metadata services, supports hot upgrades, and provides robust scalability and reliability for AI workloads.

Machine LearningMulti-Protocolcloud-native
0 likes · 24 min read
Design and Implementation of a Next‑Generation Multi‑Protocol Unstructured Storage System for Machine Learning
iQIYI Technical Product Team
iQIYI Technical Product Team
Sep 12, 2024 · Artificial Intelligence

Intelligent Compute Allocation in Advertising: Value Quantification, Elastic Elimination, and Dynamic Optimization

iQIYI’s ad engine team introduced an intelligent compute allocation system that quantifies traffic value and unified compute cost, uses elastic elimination and a dynamic allocation framework to maximize revenue under fixed compute limits, delivering over 30% inventory growth, modest consumption rise, and near‑perfect availability.

Machine LearningOptimizationPID control
0 likes · 11 min read
Intelligent Compute Allocation in Advertising: Value Quantification, Elastic Elimination, and Dynamic Optimization
Alimama Tech
Alimama Tech
Sep 11, 2024 · Artificial Intelligence

A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective

The paper introduces a coupled generative adversarial framework that merges biased observational with unbiased experimental data to create a bias‑free dataset for causal inference, enabling robust treatment‑effect estimation under collider bias from an out‑of‑distribution perspective, and demonstrates superior bias reduction on three public advertising datasets.

Generative Adversarial NetworksMachine LearningOut-of-Distribution
0 likes · 10 min read
A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective
DataFunSummit
DataFunSummit
Sep 11, 2024 · Artificial Intelligence

Weak Supervision Machine Learning in Ant Group Business Scenarios

This article presents an overview of weak supervision machine learning techniques applied to Ant Group’s business scenarios, covering an introduction to weak supervision, challenges of modeling with scarce or noisy labels, detailed methodologies for cross‑domain causal effect estimation, multi‑source noisy label denoising, and real‑world application examples.

Machine LearningWeak Supervisioncausal inference
0 likes · 18 min read
Weak Supervision Machine Learning in Ant Group Business Scenarios
Model Perspective
Model Perspective
Sep 10, 2024 · Artificial Intelligence

Why Cross-Entropy Is the Key Loss Function for Classification Models

This article explains how loss functions evaluate model performance, contrasts regression’s mean squared error with classification’s cross‑entropy, describes one‑hot encoding and softmax outputs, and shows why higher predicted probabilities for the correct class yield lower loss, highlighting applications in image, language, and speech tasks.

Machine LearningOne-hot encodingclassification
0 likes · 5 min read
Why Cross-Entropy Is the Key Loss Function for Classification Models
Python Programming Learning Circle
Python Programming Learning Circle
Sep 4, 2024 · Artificial Intelligence

Building an Automatic Math Grading System with Python: Data Generation, CNN Training, Image Segmentation, and Result Feedback

This tutorial explains how to create an automatic math‑grading tool in Python by generating synthetic digit images, training a small CNN on the data, segmenting handwritten equations with projection techniques, recognizing characters, evaluating the expressions, and overlaying the results back onto the original image.

CNNMachine LearningOCR
0 likes · 30 min read
Building an Automatic Math Grading System with Python: Data Generation, CNN Training, Image Segmentation, and Result Feedback
php Courses
php Courses
Sep 4, 2024 · Artificial Intelligence

Anomaly Detection and Outlier Handling Using PHP and Machine Learning

This article explains how to detect and handle outliers in data using PHP, covering statistical Z-Score detection and the Isolation Forest algorithm, and provides sample code for both detection and subsequent removal or replacement of anomalous values to improve data quality.

Isolation ForestMachine Learninganomaly detection
0 likes · 6 min read
Anomaly Detection and Outlier Handling Using PHP and Machine Learning
DataFunSummit
DataFunSummit
Sep 3, 2024 · Artificial Intelligence

Metric Attribution on Internet Platforms: Concepts, Methods, and Tool Applications

This article explains metric attribution for internet platforms, covering its definition, a three‑step analytical framework, deterministic and probabilistic methods such as metric decomposition, machine‑learning models with SHAP values, case studies, and a practical tool that guides users through attribution analysis.

Internet PlatformsMachine LearningSHAP
0 likes · 15 min read
Metric Attribution on Internet Platforms: Concepts, Methods, and Tool Applications
DataFunTalk
DataFunTalk
Sep 2, 2024 · Artificial Intelligence

Exploring Graph Foundation Models: Concepts, Techniques, and Future Directions

This article introduces graph foundation models, explains their relationship with large language models, reviews recent advances in graph neural networks and representation learning, presents the authors' own research on PT‑HGNN, Specformer and GraphTranslator, and discusses challenges, future research directions, and a Q&A session.

Large Language ModelsMachine Learningfoundation models
0 likes · 23 min read
Exploring Graph Foundation Models: Concepts, Techniques, and Future Directions
JD Retail Technology
JD Retail Technology
Aug 28, 2024 · Industry Insights

How JD Retail Secures E‑Commerce with AI‑Driven Content Compliance

This article examines JD Retail's content compliance platform, detailing user‑facing problems, business‑level audit responsibilities, key performance metrics, operational workflows, and a technical case study on detecting price over‑pricing using comparable‑price models and large‑scale price prediction.

E‑commerceMachine LearningPrice Anomaly Detection
0 likes · 10 min read
How JD Retail Secures E‑Commerce with AI‑Driven Content Compliance
Model Perspective
Model Perspective
Aug 27, 2024 · Fundamentals

How Mathematics Solves Murder Mysteries: From Galois to Network Theory

This article explores how mathematical concepts—from Galois theory and radian angles to distance‑decay functions and network theory—have been creatively applied to criminal investigations, illustrating real‑world cases of murder, serial killings, and terrorism, and highlighting the growing role of machine‑learning models in crime prediction.

Machine Learningcrime predictioncriminology
0 likes · 8 min read
How Mathematics Solves Murder Mysteries: From Galois to Network Theory
JD Retail Technology
JD Retail Technology
Aug 26, 2024 · Artificial Intelligence

Preference-oriented Diversity Model Based on Mutual Information for E-commerce Search Re-ranking (SIGIR 2024)

This article introduces PODM‑MI, a preference‑oriented diversity model that uses mutual information and variational Gaussian representations to jointly optimize accuracy and diversity in e‑commerce search re‑ranking, and reports significant online A/B test improvements on JD.com.

DiversityE‑commerceMachine Learning
0 likes · 10 min read
Preference-oriented Diversity Model Based on Mutual Information for E-commerce Search Re-ranking (SIGIR 2024)
DataFunTalk
DataFunTalk
Aug 25, 2024 · Artificial Intelligence

Learning at Serving Time (LAST): An Online Learning Approach for Real‑Time Re‑ranking in Recommendation Systems

This article introduces LAST, a novel online learning method that updates ranking models instantly at serving time without waiting for user feedback, addressing the latency and stability challenges of real‑time re‑ranking in industrial recommendation pipelines and demonstrating its superiority through offline and online experiments.

Machine Learningonline learningreal-time
0 likes · 11 min read
Learning at Serving Time (LAST): An Online Learning Approach for Real‑Time Re‑ranking in Recommendation Systems
Model Perspective
Model Perspective
Aug 24, 2024 · Fundamentals

Why Vectors Are the Secret Sauce Behind Modern AI and Everyday Tech

Vectors, mathematical objects capturing magnitude and direction, serve as a versatile tool for representing multidimensional data, enabling everything from economic indicators and navigation cues to deep-learning feature extraction, similarity measures, and applications like music recognition, smart chatbots, and image search.

Machine LearningSimilaritydata representation
0 likes · 9 min read
Why Vectors Are the Secret Sauce Behind Modern AI and Everyday Tech
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Aug 23, 2024 · Artificial Intelligence

Xiaohongshu REDtech Live: Presentation of Recent Top‑Conference Papers (Recruitment Session)

On August 24, 2024, Xiaohongshu’s technical team will livestream a four‑hour REDtech session across WeChat Channels, its recruitment account, and Bilibili, showcasing recent top‑conference papers—from ACL and CVPR to ICLR and AAAI—covering innovations such as KV‑cache compression, zero‑shot image generation, early‑stopping self‑consistency, negative‑sample‑aware distillation, and real‑time nearest‑neighbor search, while allowing live interaction and offering surprise merchandise.

AIConference PapersMachine Learning
0 likes · 18 min read
Xiaohongshu REDtech Live: Presentation of Recent Top‑Conference Papers (Recruitment Session)
Open Source Tech Hub
Open Source Tech Hub
Aug 22, 2024 · Artificial Intelligence

Unlock AI Power in PHP: A Hands‑On Guide to TransformersPHP

TransformersPHP brings Hugging Face’s Transformer models to PHP, enabling developers to run thousands of pre‑trained NLP models locally for tasks like text generation, summarisation, and translation, with simple installation, ONNX‑based execution, and a Python‑like pipeline API.

AIMachine LearningNLP
0 likes · 8 min read
Unlock AI Power in PHP: A Hands‑On Guide to TransformersPHP
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Aug 22, 2024 · Artificial Intelligence

How RECom Accelerates Recommendation Model Inference on GPUs

The RECom compiler introduces a subgraph‑parallel fusion technique and symbolic shape handling to dramatically speed up GPU inference of deep recommendation models with massive embedding columns, achieving up to 6.61× lower latency and 1.91× higher throughput than TensorFlow baselines, while eliminating redundant computations.

GPU OptimizationMachine LearningRecommendation Systems
0 likes · 10 min read
How RECom Accelerates Recommendation Model Inference on GPUs
DataFunSummit
DataFunSummit
Aug 21, 2024 · Artificial Intelligence

Causal Debiasing in Ant Group Marketing Recommendation: Data Fusion and Backdoor Adjustment

This article introduces causal debiasing techniques for Ant Group's marketing recommendation systems, detailing background biases, causal graph analysis, a meta‑learning data‑fusion model (MDI), backdoor‑adjustment methods, extensive experiments on public and internal datasets, and real‑world deployment results.

Ant GroupMachine Learningbackdoor adjustment
0 likes · 16 min read
Causal Debiasing in Ant Group Marketing Recommendation: Data Fusion and Backdoor Adjustment
Baidu Geek Talk
Baidu Geek Talk
Aug 21, 2024 · Artificial Intelligence

Step-by-Step PCA Face Recognition with PaddlePaddle

This article walks through using PaddlePaddle's linear algebra API to vectorize face images, load the ORL dataset, implement PCA for dimensionality reduction, and evaluate a simple face‑recognition classifier, providing full code, installation steps, and experimental results.

Machine LearningPCAPaddlePaddle
0 likes · 11 min read
Step-by-Step PCA Face Recognition with PaddlePaddle