Tagged articles

large language models

1355 articles · Page 8 of 14

Sep 24, 2025 · Artificial Intelligence

Interview Guide: Core Differences Between PPO and GRPO Algorithms for Large Model Fine‑Tuning

The article explains the fundamental principles of PPO and GRPO reinforcement‑learning algorithms, compares their architectures and training workflows, highlights why GRPO is gaining traction in large‑model fine‑tuning, discusses associated risks, and offers practical guidance on group size selection for engineers preparing for interviews.

GRPOPPORLHF

0 likes · 9 min read

Interview Guide: Core Differences Between PPO and GRPO Algorithms for Large Model Fine‑Tuning

Data Thinking Notes

Sep 21, 2025 · Artificial Intelligence

From RAG to DeepSearch & DeepResearch: How AI Is Mastering Knowledge Retrieval

Amid the rapid rise of generative AI, this article examines the limitations of large language models and explains how Retrieval‑Augmented Generation (RAG), followed by the advanced paradigms DeepSearch and DeepResearch, progressively enhance knowledge handling through dynamic retrieval, multi‑agent reasoning, and autonomous research capabilities.

AI Knowledge ManagementDeepResearchDeepSearch

0 likes · 16 min read

From RAG to DeepSearch & DeepResearch: How AI Is Mastering Knowledge Retrieval

Bighead's Algorithm Notes

Sep 20, 2025 · Artificial Intelligence

Weekly Quantitative Finance Paper Digest (Sep 13‑19, 2025)

This digest summarizes seven recent arXiv papers that apply reinforcement learning, multi‑agent frameworks, dynamic factor models, high‑frequency trading LLMs, quantum GANs, multi‑LLM sentiment analysis, and context‑aware language models to advance quantitative finance and AI‑driven market prediction.

Multi-Agent SystemsQuantum Machine Learninglarge language models

0 likes · 12 min read

Weekly Quantitative Finance Paper Digest (Sep 13‑19, 2025)

DataFunTalk

Sep 19, 2025 · Artificial Intelligence

How Tencent’s Large Language Models Transform Business with RAG, GraphRAG, and Agents

This article examines Tencent's large language model deployments across diverse business scenarios, detailing how Retrieval‑Augmented Generation, GraphRAG, and autonomous agents boost model intelligence, improve user experience, and enable advanced content generation, understanding, and multi‑step reasoning.

Artificial IntelligenceAutonomous AgentsGraphRAG

0 likes · 4 min read

How Tencent’s Large Language Models Transform Business with RAG, GraphRAG, and Agents

Data Party THU

Sep 19, 2025 · Artificial Intelligence

How RepoMaster Enables AI Agents to Master GitHub Repositories for Complex Tasks

RepoMaster is an AI‑driven framework that automatically discovers, analyzes, and executes code from massive GitHub repositories, turning them into reusable tools and achieving state‑of‑the‑art performance on challenging benchmarks while drastically reducing token consumption and engineering effort.

AI agentsRepoMasterautonomous execution

0 likes · 9 min read

How RepoMaster Enables AI Agents to Master GitHub Repositories for Complex Tasks

Data Party THU

Sep 19, 2025 · Artificial Intelligence

How DeepSeek R1 Redefines AI Reasoning with Pure Reinforcement Learning

DeepSeek R1 replaces traditional supervised fine‑tuning with a pure reinforcement‑learning pipeline, introducing the GRPO algorithm and a four‑stage training regime that dramatically lowers cost, boosts reasoning and code‑generation performance, and raises important ethical, privacy, and societal considerations for large language models.

AI reasoningDeepSeekGRPO

0 likes · 14 min read

How DeepSeek R1 Redefines AI Reasoning with Pure Reinforcement Learning

HyperAI Super Neural

Sep 19, 2025 · Artificial Intelligence

Weekly AI Paper Roundup: RL Advances, Tree‑Structured QA, and GraphRAG Breakthroughs

This article surveys five recent AI papers, covering reinforcement learning for large reasoning models, a tree‑structured table QA framework (ST‑Raptor), visual representation alignment for multimodal LLMs, GraphRAG‑based generation, and an LLM‑driven cryptographic vulnerability detector, each with key insights and links.

cryptographic vulnerability detectiongraph retrievallarge language models

0 likes · 5 min read

Weekly AI Paper Roundup: RL Advances, Tree‑Structured QA, and GraphRAG Breakthroughs

AsiaInfo Technology: New Tech Exploration

Sep 16, 2025 · Industry Insights

Can Ontology Bridge the Gap Between Large Language Models and Executable Code?

This article analyzes how combining ontology with large language models can create a new intelligent application development paradigm that unites semantic understanding and executable behavior, proposing a three‑layer architecture, a Model Control Protocol, and real‑world case studies to illustrate its potential and challenges.

AI integrationSoftware Architectureknowledge representation

0 likes · 22 min read

Can Ontology Bridge the Gap Between Large Language Models and Executable Code?

DataFunTalk

Sep 15, 2025 · Artificial Intelligence

How AI+Data Agents Are Transforming the Automotive Industry’s Digital Leap

In an interview, Di Xingxing of Autohome details their AI+Data framework—unified lake‑warehouse, intelligent engine, and agent services—that breaks data silos, blends traditional models with LLMs, leverages causal inference and RAG knowledge bases, and uses continuous feedback to build explainable, evolving data agents for accurate sales forecasting, competitive analysis, and end‑to‑end business automation in the automotive industry.

AIAutomotiveRAG

0 likes · 10 min read

How AI+Data Agents Are Transforming the Automotive Industry’s Digital Leap

DataFunSummit

Sep 14, 2025 · Artificial Intelligence

How AI is Revolutionizing Chemistry and Drug Discovery: From Data to Breakthroughs

This article explores how AI-driven models and data pipelines are transforming the chemistry and pharmaceutical sectors by accelerating drug design, improving protein‑antibody predictions, automating patent data extraction, and outlining future goals for end‑to‑end AI‑enabled scientific discovery.

AI for ScienceChemistry AIDrug discovery

0 likes · 13 min read

How AI is Revolutionizing Chemistry and Drug Discovery: From Data to Breakthroughs

Alibaba Cloud Developer

Sep 12, 2025 · Operations

How to Build End‑to‑End Observability for Large‑Model Applications on Alibaba Cloud

This guide explains how to design and implement a complete observability solution for large‑model AI services on Alibaba Cloud, covering architecture, core metrics, logging standards, demo code, log collection, dashboard design, alerting, monitoring tools, troubleshooting SOPs, and recovery procedures.

AI operationsAlibaba Cloudcloud monitoring

0 likes · 21 min read

How to Build End‑to‑End Observability for Large‑Model Applications on Alibaba Cloud

Fun with Large Models

Sep 12, 2025 · Artificial Intelligence

When to Choose Model Fine‑Tuning vs RAG for Large‑Model Engineering Interviews

The article explains the technical background and suitable scenarios for Retrieval‑Augmented Generation (RAG) and model fine‑tuning, compares their strengths, discusses how they can be combined, and provides interview‑style Q&A on their capabilities, risks, and differences from model distillation.

AI InterviewFine‑TuningRAG

0 likes · 7 min read

When to Choose Model Fine‑Tuning vs RAG for Large‑Model Engineering Interviews

AI2ML AI to Machine Learning

Sep 11, 2025 · Industry Insights

Key Takeaways from Asset Management Leaders on Large‑Model AI at the Bund Conference

The article compiles senior asset‑management executives' perspectives on applying large‑model AI—covering vertical versus generic models, integration strategies, talent and cost considerations, innovative C2C development, AI‑native platforms, and the practical challenges of using LLMs in investment research.

AI ApplicationsC2C developmentModel Integration

0 likes · 5 min read

Key Takeaways from Asset Management Leaders on Large‑Model AI at the Bund Conference

Baidu Geek Talk

Sep 10, 2025 · Artificial Intelligence

How to Cut Through the LLM SOTA Hype: Practical Evaluation Strategies for 2025

Amid the 2025 surge of large language models, this article demystifies misleading SOTA claims, critiques benchmark reliability, and presents a comprehensive, business‑focused evaluation framework—including dataset construction, metric selection, automated scoring, and practical guidelines—to help developers and product teams choose the right model for real‑world applications.

AI benchmarkingLLM-as-judgeModel Evaluation

0 likes · 18 min read

How to Cut Through the LLM SOTA Hype: Practical Evaluation Strategies for 2025

Baobao Algorithm Notes

Sep 10, 2025 · Artificial Intelligence

Qwen3-Next Unveiled: Sparse MoE, Hybrid Attention & Multi‑Token Prediction

A recent Hugging Face pull request reveals Alibaba’s upcoming Qwen3‑Next series, highlighting its extreme‑context, parameter‑efficient design that combines a 1:50 high‑sparsity MoE, a hybrid attention architecture mixing gated attention with Gated DeltaNet, and a Multi‑Token Prediction technique, promising ten‑fold throughput gains for 32K‑plus token contexts.

AI architectureHybrid AttentionMulti-Token Prediction

0 likes · 8 min read

Qwen3-Next Unveiled: Sparse MoE, Hybrid Attention & Multi‑Token Prediction

DataFunSummit

Sep 9, 2025 · Artificial Intelligence

How Baidu’s GRAB Model Uses Scaling Laws to Transform Ad Ranking

This article explains Baidu's generative ranking model GRAB, detailing how scaling laws from large language models inspire a new recommendation paradigm, the model's architecture, custom attention mechanisms, training strategies, deployment optimizations, and the resulting business gains in CTR and revenue.

BaiduCTR predictionRecommendation Systems

0 likes · 22 min read

How Baidu’s GRAB Model Uses Scaling Laws to Transform Ad Ranking

JD Cloud Developers

Sep 9, 2025 · Artificial Intelligence

How JD’s PODM‑MI Framework Revolutionized E‑commerce Search Ranking

This article recounts a JD engineer’s journey from theory to practice, detailing the development of the PODM‑MI re‑ranking framework, its three‑layer distribution‑based design, the discovery of a novel SID bottleneck, and the resulting multi‑million‑order impact validated at SIGIR 2024.

Re‑rankingSIGIRdistribution modeling

0 likes · 8 min read

How JD’s PODM‑MI Framework Revolutionized E‑commerce Search Ranking

DataFunSummit

Sep 8, 2025 · Artificial Intelligence

How High‑Quality Inference Data Is Powering the Next AI Revolution

This article explores how high‑quality inference data has become a new paradigm driving AI breakthroughs, detailing Ant Group's research on inference data paradigms, financial‑sector applications, intelligent labeling and quality inspection, and the AIGD AI data synthesis platform, followed by a technical Q&A.

AI dataAIGDdata synthesis

0 likes · 11 min read

How High‑Quality Inference Data Is Powering the Next AI Revolution

DaTaobao Tech

Sep 8, 2025 · Artificial Intelligence

How to Make Large Language Models Understand Third‑Party Java Packages: From Failure to Success

This article explains why AI coding assistants like Cursor and Claude fail to read external Java libraries, explores naive "feed‑the‑code" tricks, evaluates built‑in IDE tools, and ultimately presents a robust solution using a local decompilation pipeline (MCP) that lets LLMs query class definitions and generate correct backend code.

AI code generationJava decompilationThird‑party libraries

0 likes · 19 min read

How to Make Large Language Models Understand Third‑Party Java Packages: From Failure to Success

DataFunTalk

Sep 8, 2025 · Artificial Intelligence

When Claude Leaves China: How Domestic AI Models Are Rising to Fill the Gap

Anthropic's new ban on Claude for Chinese‑controlled firms forces developers to seek home‑grown alternatives, prompting a deep dive into Claude's strengths, the rapid rise of Chinese large‑language models, and the gaps that still separate them from the world‑leading offering.

AI modelsAI safetyChinese AI

0 likes · 11 min read

When Claude Leaves China: How Domestic AI Models Are Rising to Fill the Gap

Bighead's Algorithm Notes

Sep 5, 2025 · Artificial Intelligence

Weekly Quantitative Finance Paper Digest (Aug 30 – Sep 5, 2025)

This digest reviews four recent AI‑driven finance papers: a robust MCVaR portfolio optimizer with ellipsoidal support and RKHS uncertainty, a PPO‑based adaptive weighting system for LLM‑generated alphas, an empirical comparison of price‑based, GICS‑based, and LLM‑embedding stock clustering, and a diffusion‑model approach that generates future financial chart images from current charts and text prompts.

diffusion modelslarge language modelsportfolio optimization

0 likes · 9 min read

Weekly Quantitative Finance Paper Digest (Aug 30 – Sep 5, 2025)

ShiZhen AI

Sep 5, 2025 · Artificial Intelligence

Andrew Ng Highlights Core AI Engineer Skills Amidst Major AI Industry Updates

The article reports that ChatGPT now supports branch conversations, Anthropic restricts service use in certain regions, Andrew Ng outlines essential AI engineer capabilities such as AI‑assisted software building, prompting and agentic workflows, and highlights the market demand, while also covering the Kimi K2 model upgrade, Hugging Face’s FineVision dataset release, and Google’s AI‑driven Deep Loop Shaping method published in *Science*.

AI EngineeringAI for astronomyAI safety

0 likes · 8 min read

Andrew Ng Highlights Core AI Engineer Skills Amidst Major AI Industry Updates

Instant Consumer Technology Team

Sep 5, 2025 · Artificial Intelligence

Why Context Engineering Is the Next Frontier for Large Language Models

This article surveys over 1,400 papers to define context engineering as a systematic discipline that structures retrieval, memory, tools, and multi‑agent coordination for LLMs, highlighting the critical asymmetry between understanding long contexts and generating equally complex outputs.

LLM evaluationMulti-Agent AIRetrieval Augmented Generation

0 likes · 8 min read

Why Context Engineering Is the Next Frontier for Large Language Models

DataFunSummit

Sep 4, 2025 · Artificial Intelligence

Unlocking Multi‑Agent AI: How Ant Group’s agentUniverse Transforms Financial Services

The article explores Ant Group’s agentUniverse team’s experience applying multi‑agent technology in finance, covering background on large language models, the agentUniverse framework, real‑world implementations, and the advantages of coordinated multi‑agent collaboration for complex analytical and decision‑making tasks.

AI collaborationMulti-AgentagentUniverse

0 likes · 4 min read

Unlocking Multi‑Agent AI: How Ant Group’s agentUniverse Transforms Financial Services

Amap Tech

Sep 4, 2025 · Artificial Intelligence

How Hierarchical Sampling Boosts Self‑Taught Reasoning in LLMs

HS‑STAR introduces a three‑stage hierarchical sampling framework that identifies high‑utility boundary problems, reallocates computation budget to them, and fine‑tunes large language models, achieving significant accuracy gains on math reasoning benchmarks without extra sampling cost.

HS-STARHierarchical Samplingdifficulty estimation

0 likes · 10 min read

How Hierarchical Sampling Boosts Self‑Taught Reasoning in LLMs

Data Party THU

Sep 3, 2025 · Artificial Intelligence

Exploring Multimodal Generative AI: A Tsinghua Tutorial at IJCAI 2025

This article introduces a 1.5‑hour tutorial presented by Tsinghua researchers at IJCAI 2025, covering the latest advances in multimodal generative AI, including multimodal large language models, diffusion models, post‑training generalization techniques, and unified understanding‑generation frameworks.

Generative ModelsIJCAI 2025diffusion models

0 likes · 5 min read

Exploring Multimodal Generative AI: A Tsinghua Tutorial at IJCAI 2025

AI2ML AI to Machine Learning

Sep 2, 2025 · Artificial Intelligence

Why Enterprise Large‑Model Digitalization Is So Hard: Key Challenges and Capabilities

The article analyzes why enterprise‑wide large‑model AI projects face steep hurdles, outlining required human capabilities, historical labor shifts, current hot technologies such as RAG, Agent, CoT and multimodal, their limits, a three‑stage implementation roadmap, typical case pitfalls, and the key success factors for sustainable digital transformation.

AgentCoTEnterprise AI

0 likes · 15 min read

Why Enterprise Large‑Model Digitalization Is So Hard: Key Challenges and Capabilities

Amap Tech

Sep 2, 2025 · Artificial Intelligence

How Pos2Distill Eliminates Positional Bias in Large Language Models

This article introduces Pos2Distill, a novel knowledge‑distillation framework that transfers capabilities from advantageous to disadvantaged positions in large language models, effectively mitigating positional bias and improving performance on long‑text retrieval and in‑context reasoning tasks.

in-context reasoningknowledge distillationlarge language models

0 likes · 10 min read

How Pos2Distill Eliminates Positional Bias in Large Language Models

Alibaba Cloud Developer

Sep 2, 2025 · Artificial Intelligence

Turning Large Language Models into Business Results: Alibaba Cloud’s Playbook

In this talk, Alibaba Cloud CIO Jiang Linquan shares how his team systematically tackled organizational, technical, and operational challenges to deploy large‑language‑model applications across dozens of enterprise scenarios, presenting real‑world case studies, a RIDE methodology, and practical metrics for success.

AIEnterprise AIRIDE methodology

0 likes · 36 min read

Turning Large Language Models into Business Results: Alibaba Cloud’s Playbook

Software Engineering 3.0 Era

Sep 1, 2025 · Industry Insights

How Large AI Models Will Redefine Software Development in the Next Few Years

The article analyzes how emerging large AI models are moving from simple code copying to intent‑driven programming, examines current tactical uses versus strategic design limits, presents real‑world examples like Vibe Coding, and forecasts both the opportunities and risks for software engineering over the next 2‑3 years.

AI agentsSoftware ArchitectureVibe Coding

0 likes · 10 min read

How Large AI Models Will Redefine Software Development in the Next Few Years

DataFunSummit

Sep 1, 2025 · Artificial Intelligence

Turning Large AI Models into Real Business Value: A Logistics Ops Expert’s Playbook

In this interview, senior AI product operations manager Lu Xinting shares how to identify high‑value AI scenarios, apply three practical metrics, build a closed‑loop AIGC operation framework, and design user incentives to achieve product‑market fit for large language models in logistics.

AI operationsAIGClarge language models

0 likes · 8 min read

Turning Large AI Models into Real Business Value: A Logistics Ops Expert’s Playbook

DataFunSummit

Aug 28, 2025 · Artificial Intelligence

Why Finance Needs Its Own Large Language Model: Insights from Du Xiaoman

This article explains how the unique data‑driven, knowledge‑intensive, and complex nature of the financial industry makes large language models especially valuable, outlines the limitations of generic models, and shows how domain‑specific, cost‑effective models can deliver superior performance for finance.

AICost Efficiencyindustry AI

0 likes · 5 min read

Why Finance Needs Its Own Large Language Model: Insights from Du Xiaoman

Architects' Tech Alliance

Aug 26, 2025 · Artificial Intelligence

How DeepSeek‑V3.1’s New FP8 Precision Supercharges Domestic Chip Performance

DeepSeek‑V3.1 introduces the UE8M0 FP8 Scale precision, cutting memory usage by up to 75% and enabling next‑generation Chinese chips such as Ascend 910B to run 128K context models efficiently, while the ecosystem rapidly adopts FP8, yet challenges in IP autonomy and software maturity remain before global competitiveness is achieved.

AI hardwareDeepSeekFP8

0 likes · 10 min read

How DeepSeek‑V3.1’s New FP8 Precision Supercharges Domestic Chip Performance

JD Tech

Aug 25, 2025 · Artificial Intelligence

How JD’s Large‑Model Tools are Shaping AI in Enterprise: Insights & Roadmap

JD’s recent technical salon reveals the rapid evolution of large‑model tools, detailing industry trends, JD’s JoyAI ecosystem—including JoyAgent, OxyGent and JoyCode—real‑world applications across office, code review, logistics and local services, and future policy and multi‑agent visions.

AI ApplicationsAI toolsAgent platforms

0 likes · 13 min read

How JD’s Large‑Model Tools are Shaping AI in Enterprise: Insights & Roadmap

Architecture and Beyond

Aug 24, 2025 · Artificial Intelligence

Why Master‑Slave Architecture Powers Modern Multi‑Agent AI Systems

The article explains how the master‑slave (or manager‑worker) architecture, inspired by both software micro‑services and biological systems, solves context fragmentation and coordination challenges in large‑model multi‑agent applications, detailing design principles, technical implementations, advantages, limitations, and suitable use cases.

AI CoordinationMulti-Agentcontext management

0 likes · 15 min read

Why Master‑Slave Architecture Powers Modern Multi‑Agent AI Systems

Wu Shixiong's Large Model Academy

Aug 23, 2025 · Artificial Intelligence

Why LoRA, QLoRA, Prompt & Prefix Tuning Are Changing Large‑Model Fine‑Tuning

This article explains the mathematical basis of LoRA, compares it with QLoRA, Prompt Tuning, Prefix Tuning and P‑tuning, shows practical PyTorch implementations, and provides mixed‑precision training tips so readers can choose the most memory‑efficient fine‑tuning method for their large language models.

LoRAPrompt TuningQLoRA

0 likes · 17 min read

Why LoRA, QLoRA, Prompt & Prefix Tuning Are Changing Large‑Model Fine‑Tuning

DataFunSummit

Aug 23, 2025 · Artificial Intelligence

Mastering Role‑Playing AI Agents: Challenges, Techniques, and Future Directions

This article surveys the latest research on role‑playing AI agents, covering their definition, core components, application scenarios, three main challenges—role fidelity, long‑term memory, and evaluation—and presents four technical approaches for each challenge along with future research directions and references.

AI agentsMemoryevaluation

0 likes · 22 min read

Mastering Role‑Playing AI Agents: Challenges, Techniques, and Future Directions

JD Retail Technology

Aug 22, 2025 · Artificial Intelligence

How JD’s Open‑Source Large‑Model Tools Are Shaping the Future of Enterprise AI

This article explores the rapid evolution of large‑model AI tools, outlines JD’s open‑source solutions such as JoyAI, JoyAgent, OxyGent and JoyCode, and examines real‑world applications, design principles, policy considerations, and future directions for AI agents and embodied intelligence.

AI ApplicationsAI policyEnterprise AI

0 likes · 12 min read

How JD’s Open‑Source Large‑Model Tools Are Shaping the Future of Enterprise AI

JD Tech Talk

Aug 20, 2025 · Artificial Intelligence

How Large AI Models Are Transforming Software Testing

This article explains what large AI models are, how they enhance capabilities across domains, and details their practical use in software testing—covering code review, automated test case generation, security and performance checks—while envisioning future impacts on manual testing efficiency.

AI in QASoftware testingTest Automation

0 likes · 4 min read

How Large AI Models Are Transforming Software Testing

Data Party THU

Aug 20, 2025 · Artificial Intelligence

How Dual‑Granularity Prompting Boosts Graph‑Enhanced LLMs for Fraud Detection

The article analyzes the Dual Granularity Prompting (DGP) framework, which mitigates information overload in graph‑enhanced large language models for fraud detection by applying fine‑grained processing to target nodes and coarse‑grained summarization to neighbors, achieving superior accuracy and token efficiency across multiple public and industrial datasets.

dual granularity promptingfraud detectiongraph foundation model

0 likes · 6 min read

How Dual‑Granularity Prompting Boosts Graph‑Enhanced LLMs for Fraud Detection

Kuaishou Large Model

Aug 19, 2025 · Artificial Intelligence

How Klear-Reasoner Achieves SOTA Math & Code Reasoning with GPPO

Klear-Reasoner, built on Qwen3‑8B‑Base, introduces the Gradient‑Preserving Clipping Policy Optimization (GPPO) algorithm to overcome traditional clip limitations, achieving state‑of‑the‑art performance on AIME2024/2025 and LiveCodeBench while providing detailed experimental analysis and data‑quality insights.

GPPOGradient Clippingcode reasoning

0 likes · 11 min read

How Klear-Reasoner Achieves SOTA Math & Code Reasoning with GPPO

Alibaba Cloud Developer

Aug 18, 2025 · Artificial Intelligence

Mastering Claude Prompt Engineering: 9 Proven Strategies to Boost LLM Performance

This guide systematically breaks down Anthropic's official prompt‑engineering recommendations—clear instructions, multishot examples, chain‑of‑thought prompting, XML structuring, response pre‑filling, prompt chaining, long‑context handling, extended thinking, and practical code snippets—showing how to unlock Claude's full potential across complex tasks.

AIChain-of-ThoughtClaude

0 likes · 15 min read

Mastering Claude Prompt Engineering: 9 Proven Strategies to Boost LLM Performance

Fighter's World

Aug 15, 2025 · Artificial Intelligence

Why GPT‑5 Is Still Far From AGI Yet Near Scalable Profitability

The article analyzes GPT‑5’s release, its unified multi‑model architecture with a real‑time router, improved reasoning, coding and tool‑use capabilities, reduced hallucinations, and how these technical shifts reshape AI commercialization, investment logic, competition and enterprise adoption.

AI commercializationAgentic AIGPT-5

0 likes · 20 min read

Why GPT‑5 Is Still Far From AGI Yet Near Scalable Profitability

Data Party THU

Aug 14, 2025 · Artificial Intelligence

How FilterLLM Turns One LLM Pass into Billion‑User Cold‑Start Recommendations

The article analyzes the FilterLLM approach, which augments a frozen LLM with billions of learnable user tokens to predict a full‑user interaction probability distribution in a single forward pass, dramatically speeding up cold‑start recommendation while preserving recommendation quality across multiple benchmarks.

AICold StartFilterLLM

0 likes · 8 min read

How FilterLLM Turns One LLM Pass into Billion‑User Cold‑Start Recommendations

Data Party THU

Aug 13, 2025 · Artificial Intelligence

How Large Language Models Are Revolutionizing Automated Scholarly Paper Review

This survey examines the rapid rise of large language models in automated scholarly paper review (ASPR), analyzing model types, technical breakthroughs such as long‑text, multimodal, and multi‑turn capabilities, new generation methods, datasets, open‑source tools, current challenges, publisher policies, and future research directions.

ASPRResearch ethicsautomated paper review

0 likes · 19 min read

How Large Language Models Are Revolutionizing Automated Scholarly Paper Review

AI Info Trend

Aug 13, 2025 · Industry Insights

How China’s AI Labs Are Closing the Gap with the US in Q2 2025

The Q2 2025 State of AI report analyzes Chinese AI labs’ rapid progress across language models, open‑source weights, and multimodal generation, showing a shrinking performance gap with US leaders, detailed benchmark scores, ecosystem classifications, and emerging competitive dynamics.

AIBenchmarkChina

0 likes · 10 min read

How China’s AI Labs Are Closing the Gap with the US in Q2 2025

AI Info Trend

Aug 11, 2025 · Industry Insights

What Q2 2025 Reveals About the AI Landscape: Key Trends and Model Rankings

The Q2 2025 State of AI Highlights Report analyzes benchmark data, model performance, and market dynamics, revealing five major industry trends, the rise of AI agents, rapid advances in language, vision, and speech models, and shifting hardware acceleration strategies that shape the future of artificial intelligence.

AIAI agentsBenchmark

0 likes · 11 min read

What Q2 2025 Reveals About the AI Landscape: Key Trends and Model Rankings

Data Party THU

Aug 11, 2025 · Artificial Intelligence

Can Hidden Signals Reveal Multimodal Model Jailbreaks? Introducing HiddenDetect

This article presents HiddenDetect, a training‑free method that leverages refusal‑semantic vectors and layer‑wise activation analysis to detect jailbreak attempts in multimodal large language models, revealing distinct safety signals across text and image modalities and demonstrating strong performance on several LVLM benchmarks.

LVLMMultimodalactivation analysis

0 likes · 7 min read

Can Hidden Signals Reveal Multimodal Model Jailbreaks? Introducing HiddenDetect

Alibaba Cloud Big Data AI Platform

Aug 8, 2025 · Artificial Intelligence

Unlocking Big Data Ops with Large Models: Opportunities, Challenges, Design

This article summarizes a Cloud Summit talk where Alibaba Cloud’s AI expert Zhang Yingying explains how large language models can enhance big‑data intelligent operations, covering opportunities, challenges, RAG‑based Q&A, multi‑agent diagnostics, and the engineering architecture needed for reliable, scalable deployment.

AI EngineeringBig Data OperationsRAG

0 likes · 20 min read

Unlocking Big Data Ops with Large Models: Opportunities, Challenges, Design

Alibaba Cloud Big Data AI Platform

Aug 8, 2025 · Artificial Intelligence

What Von Neumann’s Brain Theory Reveals About Prompt Engineering for LLMs

The article explores how Von Neumann’s insights on the brain‑computer analogy illuminate modern large‑language‑model prompt engineering, comparing logical reasoning chains, memory mechanisms, and DSL‑driven computation to improve accuracy, reduce hallucinations, and balance reasoning depth with precise calculation.

DSLRAGcomputation

0 likes · 14 min read

What Von Neumann’s Brain Theory Reveals About Prompt Engineering for LLMs

Data Thinking Notes

Aug 6, 2025 · Artificial Intelligence

OpenAI Unveils gpt-oss 120B & 20B: Open‑Source MoE Models with 4‑Bit Quantization

OpenAI's gpt-oss series introduces two open‑source large language models—gpt‑oss‑120b and gpt‑oss‑20b—featuring Mixture‑of‑Experts architecture, 4‑bit MXFP4 quantization, extensive benchmark results, and broad deployment options across cloud and consumer hardware.

4-bit quantizationAI InferenceGPT-OSS

0 likes · 11 min read

OpenAI Unveils gpt-oss 120B & 20B: Open‑Source MoE Models with 4‑Bit Quantization

AI Frontier Lectures

Jul 31, 2025 · Artificial Intelligence

What’s Driving the Latest LLM Architecture Trends? DeepSeek, OLMo, Gemma, and More Explained

This article examines the evolution of large language model architectures over the past seven years, comparing key design choices such as Multi‑Head Latent Attention, Grouped‑Query Attention, Mixture‑of‑Experts, sliding‑window attention, normalization placement, and optimizer variants across models like DeepSeek V3, OLMo 2, Gemma 3, Llama 4, Qwen 3, SmolLM 3, and Kimi 2.

AI researchAttention MechanismsLLM comparison

0 likes · 30 min read

What’s Driving the Latest LLM Architecture Trends? DeepSeek, OLMo, Gemma, and More Explained

Data Thinking Notes

Jul 30, 2025 · Artificial Intelligence

Tracing the Evolution of Large Language Models: Key Papers and Breakthroughs

This article reviews the most influential papers in large language model research since 2017, covering foundational works such as the Transformer, GPT‑3, BERT, scaling laws, and recent innovations like FlashAttention, Mamba, and QLoRA, highlighting their core contributions and impact on AI development.

AI researchModel OptimizationTransformer

0 likes · 28 min read

Tracing the Evolution of Large Language Models: Key Papers and Breakthroughs

JD Tech

Jul 29, 2025 · Artificial Intelligence

How Causal Inference Meets Large Language Models to Revolutionize E‑commerce Pricing

This article describes a QCon talk that combines causal inference with large language models to build a retrieval‑augmented generation pricing system for e‑commerce, detailing the three‑step algorithm, LLM‑driven modeling challenges, process‑reward tree search, reinforcement‑learning fine‑tuning, and experimental gains in accuracy and speed.

Retrieval Augmented Generationcausal inferencee‑commerce pricing

0 likes · 17 min read

How Causal Inference Meets Large Language Models to Revolutionize E‑commerce Pricing

FunTester

Jul 29, 2025 · Artificial Intelligence

Why AI Hallucinations Happen and How Test Engineers Can Reset Conversations

AI-generated content can produce hallucinations—misleading or illogical answers—especially during lengthy testing dialogues, caused by context overload, limited training data, ambiguous prompts, and the model’s creative tendencies; resetting the conversation with a new session and proper handoff can dramatically improve accuracy and efficiency for software test engineers.

AI hallucinationSoftware testingconversation management

0 likes · 10 min read

Why AI Hallucinations Happen and How Test Engineers Can Reset Conversations

AI Algorithm Path

Jul 27, 2025 · Artificial Intelligence

Understanding RLHF: How Human Feedback Trains Modern LLMs

This article explains the RLHF (Reinforcement Learning from Human Feedback) pipeline that powers ChatGPT and other large language models, covering the limitations of traditional fine‑tuning, the creation of human‑feedback datasets, reward‑model training, loss design, and the final PPO‑based fine‑tuning step.

ChatGPTHuman FeedbackPPO

0 likes · 8 min read

Understanding RLHF: How Human Feedback Trains Modern LLMs

AI Info Trend

Jul 24, 2025 · Industry Insights

What’s Driving AI Adoption in 2025? Six Key Trends Uncovered

The AI Adoption Survey H1 2025 reveals that nearly half of organizations have deployed AI in production, engineering and R&D lead usage, Chinese LLMs gain overseas interest, and cost, reliability and intelligence remain the top challenges, while tool preferences and multimodal trends reshape the market.

AI adoptionAI infrastructureAI trends

0 likes · 7 min read

What’s Driving AI Adoption in 2025? Six Key Trends Uncovered

AI2ML AI to Machine Learning

Jul 24, 2025 · Artificial Intelligence

Exploring Recent Large‑Model Agent Papers: Insights and Analyses

This article reviews a series of recent research papers on large‑model agents, covering topics such as reinforcement‑learning‑driven ML agents, premise‑critique ability of LLMs, long‑term tool‑augmented LLM evaluation, agentic RAG, set‑based retrieval for multi‑hop QA, mobile VLM agents, and broader surveys of LLM applications, summarizing each work’s problem statement, prior approaches, novel contributions, experimental results, limitations, and future directions.

Agentic AIBenchmarkLLM evaluation

0 likes · 46 min read

Exploring Recent Large‑Model Agent Papers: Insights and Analyses

Alibaba Cloud Big Data AI Platform

Jul 23, 2025 · Artificial Intelligence

How to Distill Large Language Models for Efficient Text Generation with EasyDistill

This guide explains how to use the EasyDistill framework and Alibaba Cloud PAI to distill large language models for high‑quality text generation, covering model deployment, SFT and DPO training data construction, code examples, configuration files, and best practices for achieving resource‑efficient, high‑performance student models.

DPOEasyDistillPAI

0 likes · 14 min read

How to Distill Large Language Models for Efficient Text Generation with EasyDistill

Alibaba Cloud Big Data AI Platform

Jul 23, 2025 · Artificial Intelligence

Unlock Efficient LLMs: How Alibaba’s PAI EasyDistill Powers Model Post‑Training

This article explains how Alibaba Cloud's AI platform PAI leverages the EasyDistill framework for post‑training model optimization, covering knowledge distillation concepts, data synthesis techniques, basic and advanced distillation training, the DistilQwen model family, real‑world customer cases, and step‑by‑step practical demos.

AI PlatformEasyDistillLLM Optimization

0 likes · 12 min read

Unlock Efficient LLMs: How Alibaba’s PAI EasyDistill Powers Model Post‑Training

Tencent Cloud Developer

Jul 23, 2025 · Artificial Intelligence

Why Retrieval‑Augmented Generation Is Evolving Into Agentic AI Search

This article explains how the inherent knowledge limits of large language models drive the rise of Retrieval‑Augmented Generation (RAG), outlines its three evolutionary stages, introduces Agentic RAG and DeepSearch, and discusses the knowledge and ability boundaries that shape future AI search systems.

AI SearchAgentic AIDeepSearch

0 likes · 19 min read

Why Retrieval‑Augmented Generation Is Evolving Into Agentic AI Search

Alibaba Cloud Developer

Jul 21, 2025 · Artificial Intelligence

Unlocking LLM Power: How Context Engineering Transforms AI Assistants

Context engineering, the emerging discipline of structuring and managing input information for large language models, goes beyond simple prompt design by addressing issues such as context poisoning, overload, and conflict, offering strategies like intelligent retrieval, isolation, pruning, and compression to build reliable, high‑performing AI agents.

AI productivityAgent designcontext engineering

0 likes · 19 min read

Unlocking LLM Power: How Context Engineering Transforms AI Assistants

DataFunTalk

Jul 21, 2025 · Artificial Intelligence

From Prompt Engineering to Context Engineering: Transforming LLM Interactions

This article traces the evolution from prompt engineering to context engineering, detailing technical milestones, core concepts, practical strategies, and future trends that together reshape large language model applications and enable sophisticated AI agents across diverse domains.

Retrieval Augmented Generationlarge language modelsmemory management

0 likes · 35 min read

From Prompt Engineering to Context Engineering: Transforming LLM Interactions

Data Thinking Notes

Jul 20, 2025 · Artificial Intelligence

Mastering Context Engineering: Boost LLM Performance with Advanced Techniques

Context Engineering, a new discipline for optimizing large language model inputs, expands context windows, compares with prompt engineering, outlines core techniques like information organization, dynamic management, semantic retrieval, and offers practical applications and recommendations to enhance AI performance across domains.

ai-optimizationlarge language modelsprompt engineering

0 likes · 11 min read

Mastering Context Engineering: Boost LLM Performance with Advanced Techniques

Fun with Large Models

Jul 17, 2025 · Artificial Intelligence

How to Integrate Large Models with LangChain: A Step‑by‑Step Tutorial

This tutorial explains LangChain's core modules and three‑layer architecture, shows how to set up a Python environment, and provides concrete code examples for connecting SiliconFlow Qwen3‑8B and DeepSeek models via the init_chat_model API, including result inspection and references to official documentation.

DeepSeekLangChainModel Integration

0 likes · 9 min read

How to Integrate Large Models with LangChain: A Step‑by‑Step Tutorial

Alibaba Cloud Big Data AI Platform

Jul 16, 2025 · Artificial Intelligence

ChunkFlow: Accelerating Long‑Context Model Fine‑Tuning Up to 4.5× Faster

The paper introduces ChunkFlow, an efficient training framework for variable‑length and ultra‑long sequence datasets that powers Qwen models, achieving up to 4.53× speedup over Megatron‑LM and more than 2× overall performance gains by reorganizing data into fixed‑size chunks and employing a state‑aware scheduler.

AI performanceChunkFlowDistributed Training

0 likes · 7 min read

ChunkFlow: Accelerating Long‑Context Model Fine‑Tuning Up to 4.5× Faster

DataFunTalk

Jul 16, 2025 · Artificial Intelligence

How Jason Wei’s Breakthroughs Are Shaping the Future of Large Language Models

Jason Wei, a former Google Brain and OpenAI researcher now at Meta, has driven key advances in large language models—including chain‑of‑thought prompting, instruction tuning, emergent abilities, zero‑shot learning, and data augmentation—shaping both AI research paradigms and real‑world applications.

Chain-of-ThoughtInstruction Tuningemergent abilities

0 likes · 7 min read

How Jason Wei’s Breakthroughs Are Shaping the Future of Large Language Models

DataFunTalk

Jul 16, 2025 · Artificial Intelligence

MiniMax-M1 Revealed: Hybrid Attention, RL Training, and 1M Token Context

MiniMax’s latest M1 model, unveiled after a $300 million funding round, showcases a 4.56‑trillion‑parameter hybrid‑expert architecture with lightning attention, supporting up to one million tokens, and leverages reinforcement‑learning techniques to enhance long‑context handling, inference efficiency, and system‑2 reasoning capabilities.

AI scalingHybrid Attentionlarge language models

0 likes · 16 min read

MiniMax-M1 Revealed: Hybrid Attention, RL Training, and 1M Token Context

DataFunSummit

Jul 15, 2025 · Artificial Intelligence

Unlocking Semantic Search: Elasticsearch Vector Search & RAG Applications

This article explains why traditional keyword search falls short, introduces Elasticsearch's vector search and hybrid retrieval capabilities, and shows how combining it with large language models enables Retrieval‑Augmented Generation (RAG) for more accurate, context‑aware AI-driven search across text and multimedia data.

AIElasticsearchRAG

0 likes · 5 min read

Unlocking Semantic Search: Elasticsearch Vector Search & RAG Applications

DataFunTalk

Jul 13, 2025 · Artificial Intelligence

What 2025’s AI API Market Data Reveals About the Future of Large Models

An in‑depth analysis of 2025 H1 OpenRouter token usage shows explosive growth in Q1, highlights Google Gemini’s market dominance, reveals diverse long‑tail demand across domains, and examines shifting API preferences, offering key insights into the evolving landscape of large‑model services.

AI market analysisAPI trendsOpenRouter

0 likes · 10 min read

What 2025’s AI API Market Data Reveals About the Future of Large Models

DataFunSummit

Jul 13, 2025 · Artificial Intelligence

How Alibaba Tackles Low-Resource Language Data for Multilingual LLMs

In this interview, Alibaba International’s senior data‑science expert Li Haijun explains the challenges of low‑resource languages for multilingual large models and details a five‑step data‑collection, augmentation, quality‑optimization, engineering, and evaluation framework that powers their cross‑border e‑commerce AI applications.

AIlarge language modelslow-resource languages

0 likes · 12 min read

How Alibaba Tackles Low-Resource Language Data for Multilingual LLMs

AI Frontier Lectures

Jul 11, 2025 · Artificial Intelligence

How Llama Evolved: From Llama‑1 to Llama‑3 – Architecture, Data, and Performance Insights

This article provides a comprehensive technical analysis of Meta's Llama series, tracing the evolution from Llama‑1 through Llama‑2 to Llama‑3, detailing model architectures, training data pipelines, optimization methods, benchmark results, and the broader impact on the open‑source AI community.

AI researchLlamalarge language models

0 likes · 25 min read

How Llama Evolved: From Llama‑1 to Llama‑3 – Architecture, Data, and Performance Insights

Kuaishou Tech

Jul 10, 2025 · Artificial Intelligence

How MODA’s Modular Duplex Attention Solves Multimodal Attention Imbalance and Boosts Emotion Understanding

The paper introduces MODA, a modular duplex attention multimodal model that addresses severe cross‑modal attention imbalance in existing large multimodal models, proposes a novel attention paradigm and masking scheme, and demonstrates significant performance gains across 21 benchmarks in perception, cognition, and emotion tasks, earning a Spotlight paper at ICML 2025.

Attention MechanismsEmotion RecognitionMoDA

0 likes · 13 min read

How MODA’s Modular Duplex Attention Solves Multimodal Attention Imbalance and Boosts Emotion Understanding

Alibaba Middleware

Jul 10, 2025 · Artificial Intelligence

How Context Engineering Builds a Moat for Vertical and Domain Agents

The article explains how context engineering—evolving from simple prompts to structured information pipelines—enhances the reliability of vertical and domain-specific AI agents, outlines common failure modes such as context poisoning, and presents practical strategies like intelligent retrieval, isolation, pruning, and compression to construct robust agent systems.

AI agentsRetrieval Augmentationagent orchestration

0 likes · 19 min read

How Context Engineering Builds a Moat for Vertical and Domain Agents

Nightwalker Tech

Jul 10, 2025 · Artificial Intelligence

Master Prompt Engineering: From Basics to Advanced AI Prompt Techniques

This comprehensive guide introduces Prompt Engineering, explaining its core concepts, why clear prompts matter, and how to craft effective instructions using roles, tasks, requirements, and examples, while covering beginner to advanced techniques such as chain‑of‑thought, self‑correction, and building reusable prompt workflows for AI models.

AIChatGPTlarge language models

0 likes · 29 min read

Master Prompt Engineering: From Basics to Advanced AI Prompt Techniques

DataFunSummit

Jul 8, 2025 · Artificial Intelligence

Explore Cutting-Edge AI Knowledge Graphs: From Multimodal GraphRAG to Industry Applications

This article presents a curated catalog of cutting‑edge AI resources, covering multimodal GraphRAG, knowledge‑graph and large‑model integration, financial industry AI products, Chinese‑medicine decision support, AI‑driven knowledge‑graph evolution, private‑domain Q&A pipelines, and emerging trends and standards, with a QR code for the full ebook.

Artificial Intelligencedocument intelligenceknowledge graph

0 likes · 2 min read

Explore Cutting-Edge AI Knowledge Graphs: From Multimodal GraphRAG to Industry Applications

Data Thinking Notes

Jul 6, 2025 · Artificial Intelligence

How Quantization Shrinks Giant AI Models for Edge Devices

This article explains why quantizing massive AI models is essential for deploying them on resource‑constrained devices, outlines core quantization concepts, techniques, and methods, compares their pros and cons, and presents practical application scenarios such as smartphones, autonomous driving, IoT, and edge computing.

AI deploymentedge AIlarge language models

0 likes · 9 min read

How Quantization Shrinks Giant AI Models for Edge Devices

dbaplus Community

Jul 6, 2025 · Artificial Intelligence

Why Build AI Agents? Benefits, Challenges, and Real-World Examples

This article explores the definition of AI agents, examines why they are essential despite challenges like latency and hallucinations, highlights their advantages such as lowered development barriers and workflow simplification, and presents real-world cases and future multi‑agent prospects.

AI agentsMulti-Agent Systemslarge language models

0 likes · 25 min read

Why Build AI Agents? Benefits, Challenges, and Real-World Examples

DataFunTalk

Jul 5, 2025 · Artificial Intelligence

Is AI Turning Human Thought into a Uniform, Safe Echo Chamber?

Recent studies from MIT, Cornell and Santa Clara reveal that reliance on AI tools like ChatGPT reduces brain activity, narrows creative thinking, and drives cultural homogenization, prompting urgent reflection on the trade‑off between efficiency and originality in human expression.

Artificial IntelligenceCognitive ScienceCultural Homogenization

0 likes · 12 min read

Is AI Turning Human Thought into a Uniform, Safe Echo Chamber?

Nightwalker Tech

Jul 4, 2025 · Artificial Intelligence

Bypass Membership Limits: Access Overseas LLMs Easily with Chatbox

This guide explains how to overcome domestic membership restrictions and quickly connect to overseas large language models such as ChatGPT, Gemini, Claude, and Grok using the open‑source Chatbox client, covering download, configuration, model selection, and various interaction modes with step‑by‑step screenshots.

AI modelsChatboxlarge language models

0 likes · 8 min read

Bypass Membership Limits: Access Overseas LLMs Easily with Chatbox

Subtle Storm

Jul 3, 2025 · Artificial Intelligence

Why Large Language Models Measure Usage in Tokens

The article explains that tokens are the fundamental computational units of large language models, describes how tokenization works, why charging per token reflects the high inference cost, and outlines token characteristics, pricing, and their impact on applications such as dialogue and document Q&A.

AI pricingBPEinference cost

0 likes · 6 min read

Why Large Language Models Measure Usage in Tokens

Instant Consumer Technology Team

Jul 3, 2025 · Artificial Intelligence

Why Buying an AI Appliance Is a Strategic Pitfall for Enterprises

Enterprises rushing to purchase DeepSeek AI appliances and smart‑agent platforms often face hidden technical, data, and organizational challenges that turn promised "plug‑and‑play" solutions into costly missteps, highlighting the need for realistic strategy, robust data governance, and continuous capability building.

AI capability buildingAI deploymentRAG

0 likes · 28 min read

Why Buying an AI Appliance Is a Strategic Pitfall for Enterprises

iQIYI Technical Product Team

Jul 3, 2025 · Artificial Intelligence

Three iQIYI AI Papers Break New Ground at ACL 2025 & INTERSPEECH 2025

iQIYI’s AI research team secured three paper acceptances—two at ACL 2025 (including a main conference and a Findings paper) and one at INTERSPEECH 2025—covering long‑context large language model evaluation, Chinese novel summarization, and efficient Thai speech recognition, with links to each work.

ACL 2025AI researchINTERSPEECH 2025

0 likes · 7 min read

Three iQIYI AI Papers Break New Ground at ACL 2025 & INTERSPEECH 2025

AI Frontier Lectures

Jul 2, 2025 · Artificial Intelligence

Can Language Models Self‑Edit? Inside the SEAL Framework for Self‑Adapting LLMs

This article reviews recent AI self‑evolution research and provides an in‑depth analysis of the SEAL (Self‑Adapting Language) framework, which enables large language models to generate and learn from their own synthetic data through a nested reinforcement‑learning and fine‑tuning loop, with experimental results on few‑shot and knowledge‑integration tasks.

Knowledge IntegrationSEALfew-shot learning

0 likes · 11 min read

Can Language Models Self‑Edit? Inside the SEAL Framework for Self‑Adapting LLMs

DataFunTalk

Jul 2, 2025 · Artificial Intelligence

How Multimodal Large Models Are Revolutionizing Complex Document OCR

In a detailed interview, Zhao Chenyang explains how multimodal large models (VLM) overcome the limitations of traditional OCR in mixed layouts, table reconstruction, and handwritten text by leveraging self‑supervised pre‑training, lightweight fine‑tuning, and hybrid pipelines that dramatically cut annotation costs and improve recall rates.

AI deploymentdocument OCRhybrid pipeline

0 likes · 13 min read

How Multimodal Large Models Are Revolutionizing Complex Document OCR

Smart Era Software Development

Jul 2, 2025 · Artificial Intelligence

Is Prompt Engineering Obsolete? How Context Engineering Redefines AI Architecture

The article argues that as large language models become more capable, the key to successful AI applications shifts from clever prompting to robust context engineering—a dynamic, system‑level practice that supplies precise information, appropriate tools, and proper formatting to ensure stable, production‑grade agent behavior.

AI agentsSoftware Architecturecontext engineering

0 likes · 9 min read

Is Prompt Engineering Obsolete? How Context Engineering Redefines AI Architecture

Tencent Cloud Developer

Jul 2, 2025 · Artificial Intelligence

Big Model Evolution: From Transformers to Enterprise Deployment

This article surveys the rapid evolution of large language models from the Transformer breakthrough to trillion‑parameter capabilities, explains key techniques such as self‑attention, MoE and KV‑Cache, explores practical aspects like temperature tuning, sales AI applications, and compares private versus cloud deployment strategies for enterprises.

KV cacheenterprise deploymentlarge language models

0 likes · 6 min read

Big Model Evolution: From Transformers to Enterprise Deployment

DataFunTalk

Jul 1, 2025 · Artificial Intelligence

Will OpenAI Reach ASI First? Dylan Patel’s Bold Prediction

In a candid hour‑long interview, SemiAnalysis founder Dylan Patel predicts OpenAI will be the first to achieve artificial superintelligence (ASI), while dissecting GPT‑4.5’s failure, Meta’s costly AI missteps, Apple’s strategic lag, and the shifting partnership between OpenAI and Microsoft.

AI CompetitionASIApple

0 likes · 11 min read

Will OpenAI Reach ASI First? Dylan Patel’s Bold Prediction

Ops Development Stories

Jul 1, 2025 · Artificial Intelligence

From Lean to AIOps: How AI is Transforming Modern Operations

This comprehensive guide walks through the evolution from Lean and Agile practices to DevOps and finally AIOps, explaining core concepts, key algorithms, the role of large language models, RAG‑based root‑cause analysis, and practical implementation steps for intelligent operations.

AIOpsLeanRAG

0 likes · 19 min read

From Lean to AIOps: How AI is Transforming Modern Operations

DataFunSummit

Jun 30, 2025 · Artificial Intelligence

How Large Language Models Are Evolving Toward Autonomous Meta‑Learning Agents

This talk reviews the rapid evolution of generative large‑model AI from rule‑based systems to massive pre‑training, examines the current bottlenecks in continual learning and knowledge discovery, and proposes large‑scale meta‑learning—especially context‑based reinforcement learning (ICRL)—as a path toward truly autonomous, self‑learning agents.

AI researchAutonomous Agentscontextual learning

0 likes · 24 min read

How Large Language Models Are Evolving Toward Autonomous Meta‑Learning Agents

DataFunTalk

Jun 30, 2025 · Artificial Intelligence

Wenxin 4.5 Series: Open‑Source Multimodal MoE Models and FastDeploy Guide

The Wenxin 4.5 series introduces ten open‑source models—including large‑scale MoE and dense variants—featuring a novel multimodal heterogeneous architecture, high training efficiency, SOTA benchmark performance, and comprehensive toolkits (ERNIEKit, FastDeploy) for fine‑tuning and multi‑hardware deployment.

ERNIEKitFastDeployMoE

0 likes · 8 min read

Wenxin 4.5 Series: Open‑Source Multimodal MoE Models and FastDeploy Guide

Hailey Says

Jun 29, 2025 · Artificial Intelligence

If Life Were an RLHF, Who’s Shaping Your Rewards?

The article explains the three‑stage RLHF pipeline—pretraining, supervised fine‑tuning, and reward‑model reinforcement—and draws a detailed analogy to human life phases, showing how early data, personal values, and continual feedback act as a reward function that can be consciously re‑engineered.

AI AlignmentHuman FeedbackLife Analogy

0 likes · 13 min read

If Life Were an RLHF, Who’s Shaping Your Rewards?

DataFunTalk

Jun 29, 2025 · Artificial Intelligence

Large Models Boost Douyin User Experience: Expert Insights

In an interview at the DA Digital Intelligence Conference, ByteDance AI specialist Cai Conghuai explains how large language models, combined with techniques like SFT, DPO, and RAG, are reshaping Douyin's user‑experience signal detection, root‑cause analysis, and evaluation, while outlining future AI‑agent breakthroughs.

AIDPOMultimodal

0 likes · 12 min read

Large Models Boost Douyin User Experience: Expert Insights

Subtle Storm

Jun 26, 2025 · Artificial Intelligence

Why Large Language Models Hallucinate and How to Prevent It

The article explains that AI hallucination stems from probabilistic language modeling, imperfect training data, missing verification mechanisms, and ambiguous user prompts, and it outlines practical countermeasures such as retrieval‑augmented generation, fine‑tuning, temperature control, prompt engineering, and multi‑model voting to reduce fabricated outputs.

AI hallucinationFine-tuningRAG

0 likes · 8 min read

Why Large Language Models Hallucinate and How to Prevent It

Alibaba Cloud Big Data AI Platform

Jun 26, 2025 · Artificial Intelligence

Master Cloud AI Inference: Load‑Testing Strategies with Alibaba PAI‑EAS

This article explains how Alibaba Cloud’s PAI‑EAS platform enables efficient, scalable AI inference by detailing distributed architecture, serverless resource scheduling, comprehensive load‑testing modes, key performance metrics, and step‑by‑step usage instructions, helping developers optimize latency, throughput, and cost for large language models.

AI InferenceAlibaba PAICloud Computing

0 likes · 7 min read

Master Cloud AI Inference: Load‑Testing Strategies with Alibaba PAI‑EAS

Alimama Tech

Jun 25, 2025 · Artificial Intelligence

Introducing ROLL: A Scalable, User‑Friendly RL Framework for Large‑Scale LLM Training

ROLL is an open‑source reinforcement‑learning framework designed for large language model post‑training that combines multi‑task RL, agentic support, flexible algorithm configuration, elastic resource scheduling, and rich observability, delivering significant accuracy gains across benchmarks while remaining easy to use for researchers, product developers, and infrastructure engineers.

AI FrameworkRLHFScalable Training

0 likes · 11 min read

Introducing ROLL: A Scalable, User‑Friendly RL Framework for Large‑Scale LLM Training

DeWu Technology

Jun 25, 2025 · Artificial Intelligence

Engineering Large Language Models with Spring AI: From Basics to RAG and Function Calls

This article walks through the fundamentals of large language models, their stateless and structured-output nature, explains how Spring‑AI provides a Java‑friendly API for model integration, covers RAG architecture, the MCP protocol, and demonstrates end‑to‑end code examples for building intelligent agents.

AI integrationFunction CallingJava

0 likes · 15 min read

Engineering Large Language Models with Spring AI: From Basics to RAG and Function Calls

ITFLY8 Architecture Home

Jun 24, 2025 · Artificial Intelligence

How Transformers and Mixture-of-Experts Power Large Language Models

This article explores the role of Transformers and Mixture‑of‑Experts in large models, outlines five fine‑tuning methods, compares traditional and agentic RAG, presents classic agent design patterns, text‑chunking strategies, levels of intelligent agent systems, and explains KV‑caching techniques.

Fine-tuningMixture of ExpertsRAG

0 likes · 2 min read

How Transformers and Mixture-of-Experts Power Large Language Models

Subtle Storm

Jun 24, 2025 · Artificial Intelligence

Understanding Cosine Similarity in Large Language Models

The article explains the mathematical definition of cosine similarity, how large language models use it to compare vector directions, its key characteristics and importance for AI retrieval and generation, and includes a simple Python example using SentenceTransformer.

EmbeddingFAISSPython

0 likes · 7 min read

Understanding Cosine Similarity in Large Language Models

AsiaInfo Technology: New Tech Exploration

Jun 23, 2025 · Artificial Intelligence

How Generative Data‑Driven Model Distillation Boosts Large‑Model Performance and Cuts Compute

This article examines generative data‑driven model distillation as a technique that not only compresses large language models but also improves their accuracy, addresses data‑privacy constraints, and reduces computational costs, offering a practical roadmap and real‑world results from a corporate AI platform.

Knowledge TransferMaaS platformai-optimization

0 likes · 22 min read

How Generative Data‑Driven Model Distillation Boosts Large‑Model Performance and Cuts Compute