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Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 9, 2025 · Artificial Intelligence

Unlocking LLM Reasoning: A Deep Dive into Prompt Engineering Techniques

This article surveys classic prompt‑engineering methods such as Chain‑of‑Thought, Self‑Consistency, Least‑to‑Most, Boosting of Thoughts, Tree of Thoughts, and AutoGPT, summarizing their core ideas, advantages, limitations, and experimental results to help readers understand how to enhance large language model reasoning without model fine‑tuning.

AI reasoningLarge Language ModelsSelf-Consistency
0 likes · 22 min read
Unlocking LLM Reasoning: A Deep Dive into Prompt Engineering Techniques
Big Data Technology & Architecture
Big Data Technology & Architecture
Apr 9, 2025 · Artificial Intelligence

Overview of Data Agents: Definitions, Applications, and Recent Developments by Google, Alibaba Cloud, and ByteDance

This article introduces the concept of AI-powered Data Agents, outlines their key features and use cases across enterprise analytics, data governance, and intelligent customer service, and reviews recent implementations from Google, Alibaba Cloud, and ByteDance, highlighting their impact on modern data-driven workflows.

Artificial IntelligenceData AgentData Analysis
0 likes · 8 min read
Overview of Data Agents: Definitions, Applications, and Recent Developments by Google, Alibaba Cloud, and ByteDance
AIWalker
AIWalker
Apr 8, 2025 · Artificial Intelligence

AgenticIR: An Agentic System for Restoring Images with Complex Degradations

AgenticIR combines visual language models and large language models in a multi‑stage reasoning workflow—perception, planning, execution, reflection, and adjustment—to evaluate, plan, and iteratively apply specialized restoration tools, achieving superior results on complexly degraded images compared to baseline methods.

Agentic SystemsICLR 2025Large Language Models
0 likes · 15 min read
AgenticIR: An Agentic System for Restoring Images with Complex Degradations
Model Perspective
Model Perspective
Apr 8, 2025 · Artificial Intelligence

Why Learning Machine Learning Still Matters in the Age of Giant AI Models

The article argues that despite the rapid rise of powerful large language models, mastering machine learning remains essential because it underpins these models, offers customized solutions for specialized tasks, and cultivates the mathematical, programming, and analytical skills needed to effectively use and extend AI technologies.

AILarge Language ModelsMachine Learning
0 likes · 10 min read
Why Learning Machine Learning Still Matters in the Age of Giant AI Models
macrozheng
macrozheng
Apr 8, 2025 · Artificial Intelligence

Boost AI Prompt Quality with Prompt Optimizer: Features, Docker Setup & Real‑World Demo

This guide introduces Prompt Optimizer, a client‑side AI prompt‑enhancement tool with over 2k GitHub stars, outlines its key features, provides step‑by‑step Docker installation commands, showcases a real‑world SpringBoot‑Vue e‑commerce project, and demonstrates how to generate and compare optimized prompts for better LLM responses.

AI Prompt OptimizationDockerLarge Language Models
0 likes · 6 min read
Boost AI Prompt Quality with Prompt Optimizer: Features, Docker Setup & Real‑World Demo
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 8, 2025 · Artificial Intelligence

Unlocking LLM Secrets: From Prompt Basics to RAG and Tool Integration

This article introduces the fundamental paradigms of large language models, explaining how simple prompts, messages, and tools like RAG and ReAct enable powerful applications, while providing practical code examples, translation strategies, and insights on prompt engineering, tool usage, and model fine‑tuning.

AILLM applicationsLarge Language Models
0 likes · 23 min read
Unlocking LLM Secrets: From Prompt Basics to RAG and Tool Integration
DataFunSummit
DataFunSummit
Apr 7, 2025 · Artificial Intelligence

Bridging the Gap Between Large Models and Real‑World Applications with RAG and Agents

This article examines how Retrieval‑Augmented Generation (RAG) and multi‑agent technologies narrow the gap between large language models and practical deployment, highlighting their roles in operations automation, financial risk control, intelligent data governance, database localization, edge inference, and future AI‑driven solutions.

Data GovernanceLarge Language ModelsOperations Automation
0 likes · 8 min read
Bridging the Gap Between Large Models and Real‑World Applications with RAG and Agents
Architecture and Beyond
Architecture and Beyond
Apr 5, 2025 · Artificial Intelligence

Why Defining Problem Boundaries Is Crucial for Effective AI Agents

The article discusses how defining clear problem boundaries is essential for AI agents, explains the challenges of vague tasks for large language models, and proposes multi‑stage decomposition, self‑reflection, and human‑in‑the‑loop strategies to improve AI performance on complex, dynamic tasks.

AIAgent ArchitectureLarge Language Models
0 likes · 13 min read
Why Defining Problem Boundaries Is Crucial for Effective AI Agents
Ops Development & AI Practice
Ops Development & AI Practice
Apr 4, 2025 · Industry Insights

Are Open‑Source LLMs Closing the Gap with Closed‑Source Giants?

A recent leaderboard analysis of top LLMs reveals that while closed‑source models like Gemini‑2.5‑Pro and ChatGPT‑4o still lead overall, open‑source models such as DeepSeek‑V3 and Llama are rapidly narrowing the performance gap, especially in specialized tasks like coding, driven by faster tech diffusion, public datasets, community collaboration, and reduced compute costs.

AI competitionLarge Language ModelsOpen Source
0 likes · 8 min read
Are Open‑Source LLMs Closing the Gap with Closed‑Source Giants?
Code Mala Tang
Code Mala Tang
Apr 3, 2025 · Artificial Intelligence

Intel Core Ultra 5 vs Apple M1: Which Wins for Large Language Model Inference?

This article compares the inference performance of a high‑end Intel Core Ultra 5 AI workstation with an Apple M1 MacBook Air using the IPEX‑LLM library, detailing installation steps, minimal code changes, resource usage, and benchmark results for small and large language models.

AI inferenceApple M1IPEX-LLM
0 likes · 9 min read
Intel Core Ultra 5 vs Apple M1: Which Wins for Large Language Model Inference?
JD Retail Technology
JD Retail Technology
Apr 2, 2025 · Artificial Intelligence

One4All: A Scalable Multi‑Task Generative Recommendation Framework for CPS Advertising

The paper introduces One4All, a scalable multi‑task generative recommendation framework for CPS advertising that combines few‑shot intent prompting, a Rewards‑in‑Context multi‑objective optimization, and an online model‑selection strategy, delivering 2‑3× offline HitRate/NDCG gains and notable online CTR, CVR, and commission improvements.

AdvertisingLLMLarge Language Models
0 likes · 14 min read
One4All: A Scalable Multi‑Task Generative Recommendation Framework for CPS Advertising
Architects' Tech Alliance
Architects' Tech Alliance
Apr 1, 2025 · Artificial Intelligence

What’s New in Large Language Models? DeepSeek V3, Qwen2.5‑Omni, Gemini 2.5 Pro, and GPT‑4o Unpacked

This article reviews the latest updates from major LLM providers—DeepSeek V3’s parameter boost and longer context, Qwen2.5‑Omni’s open‑source multimodal 7B model, Google Gemini 2.5 Pro’s 1 M‑token window and multimodal prowess, and OpenAI GPT‑4o’s image generation and reduced pricing—highlighting technical specs, capabilities, and availability.

DeepSeekGPT-4oGemini
0 likes · 9 min read
What’s New in Large Language Models? DeepSeek V3, Qwen2.5‑Omni, Gemini 2.5 Pro, and GPT‑4o Unpacked
Architect
Architect
Apr 1, 2025 · Artificial Intelligence

When to Fine‑Tune Large Language Models vs. Relying on Prompting and RAG

The article explains why most projects should start with prompt engineering or simple agent workflows, outlines the scenarios where model fine‑tuning adds real value, compares fine‑tuning with Retrieval‑Augmented Generation, and offers practical criteria for deciding which approach to adopt.

AI deploymentLarge Language ModelsLoRA
0 likes · 9 min read
When to Fine‑Tune Large Language Models vs. Relying on Prompting and RAG
AntTech
AntTech
Mar 31, 2025 · Artificial Intelligence

Ant Group Papers Accepted at ICLR 2025: Summaries and Links

The article presents the abstracts, publication types, links, and research areas of seventeen Ant Group papers accepted at ICLR 2025, covering topics such as embodied robot co‑design, efficient distributed training for large language models, optimization via LLMs, character animation, interactive frame interpolation, KV‑cache management, and privacy‑preserving Transformers.

AI researchAnt GroupICLR2025
0 likes · 23 min read
Ant Group Papers Accepted at ICLR 2025: Summaries and Links
Architects' Tech Alliance
Architects' Tech Alliance
Mar 31, 2025 · Artificial Intelligence

A Comprehensive History of Large Language Models from the Transformer Era (2017) to DeepSeek‑R1 (2025)

This article reviews the evolution of large language models from the 2017 Transformer breakthrough through BERT, GPT series, alignment techniques, multimodal extensions, open‑weight releases, and the cost‑efficient DeepSeek‑R1 in 2025, highlighting key technical advances, scaling trends, and their societal impact.

AI alignmentLLM evolutionLarge Language Models
0 likes · 26 min read
A Comprehensive History of Large Language Models from the Transformer Era (2017) to DeepSeek‑R1 (2025)
Data Thinking Notes
Data Thinking Notes
Mar 30, 2025 · Artificial Intelligence

How DeepSeek‑R1 and Kimi‑K1.5 Push the Boundaries of Strong Reasoning Models

This comprehensive analysis by the Peking University AI Alignment team dissects the technical innovations behind DeepSeek‑R1, DeepSeek‑R1 Zero, and Kimi‑K1.5, covering reinforcement‑learning‑based post‑training, rule‑based rewards, GRPO optimization, scaling laws, multimodal extensions, safety challenges, and future research directions.

AI alignmentDeepSeekKimi
0 likes · 57 min read
How DeepSeek‑R1 and Kimi‑K1.5 Push the Boundaries of Strong Reasoning Models
Architect
Architect
Mar 30, 2025 · Artificial Intelligence

What Is Retrieval-Augmented Generation? A Deep Dive into RAG Techniques

This article provides a comprehensive survey of Retrieval‑Augmented Generation (RAG), covering its basic principles, key components, seven technical variants, challenges, evaluation methods, and future research directions across multimodal, graph‑based, and agentic extensions.

AI SurveyKnowledge retrievalLarge Language Models
0 likes · 9 min read
What Is Retrieval-Augmented Generation? A Deep Dive into RAG Techniques
AI Frontier Lectures
AI Frontier Lectures
Mar 30, 2025 · Artificial Intelligence

Do Large Language Models Mirror Human Brain Language Processing? Google’s Groundbreaking Findings

Google researchers discovered a linear relationship between brain activity recorded during natural conversation and the internal embeddings of a speech‑to‑text large language model, revealing that acoustic and lexical representations from the model can accurately predict neural responses in both language comprehension and production.

AI researchGoogleLarge Language Models
0 likes · 8 min read
Do Large Language Models Mirror Human Brain Language Processing? Google’s Groundbreaking Findings
Cognitive Technology Team
Cognitive Technology Team
Mar 30, 2025 · Artificial Intelligence

Why Prompt Engineering Is the “Mind‑Reading” Technique of AI: The Crucial Role of In‑Context Learning

Prompt engineering uses in‑context learning to turn large language models into precise, task‑aware assistants by providing well‑crafted prompts that guide the model’s probability distribution, reduce hallucinations, and unlock hidden knowledge without any parameter tuning.

Artificial IntelligenceIn-Context LearningLarge Language Models
0 likes · 6 min read
Why Prompt Engineering Is the “Mind‑Reading” Technique of AI: The Crucial Role of In‑Context Learning
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Mar 29, 2025 · Artificial Intelligence

How DistilQwen2.5‑R1 Boosts Small‑Model Reasoning with Innovative Knowledge Distillation

The article introduces the DistilQwen2.5‑R1 series, which leverages a novel knowledge‑distillation pipeline—including CoT data evaluation, improvement, and validation—to transfer deep reasoning abilities from large models like DeepSeek‑R1 to compact models, achieving superior performance across math, code, and scientific benchmarks and providing open‑source checkpoints and deployment guides for practical use.

AI inferenceKnowledge DistillationLarge Language Models
0 likes · 17 min read
How DistilQwen2.5‑R1 Boosts Small‑Model Reasoning with Innovative Knowledge Distillation
Alimama Tech
Alimama Tech
Mar 28, 2025 · Artificial Intelligence

How Alibaba’s Taobao AI Models Revolutionize E‑Commerce Recommendations and Bidding

Alibaba’s Taobao Group unveiled its AIGX technology suite, including the RecGPT recommendation model, the AIGB generative bidding system, and a new AI‑generated video engine, detailing open‑source benchmarks, NeurIPS workshop participation, and measurable ROI improvements for e‑commerce advertising.

AIGenerative BiddingLarge Language Models
0 likes · 5 min read
How Alibaba’s Taobao AI Models Revolutionize E‑Commerce Recommendations and Bidding
Qborfy AI
Qborfy AI
Mar 28, 2025 · Artificial Intelligence

Master Prompt Engineering: From Basics to Advanced SQL Generation

This article walks readers through the fundamentals of prompt engineering—covering role, context, instruction, examples, and output formatting—then demonstrates a step‑by‑step construction of a sophisticated SQL‑generation prompt, complete with concrete code snippets, best‑practice tips, and reference resources.

AI Prompt DesignInstruction TuningLarge Language Models
0 likes · 21 min read
Master Prompt Engineering: From Basics to Advanced SQL Generation
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 26, 2025 · Artificial Intelligence

Why DeepSeek Is Shaking Up the LLM Landscape: Architecture, Performance, and Cost

DeepSeek, a Chinese AI startup, offers open‑source large language models—DeepSeek‑V3 for general tasks and DeepSeek‑R1 for intensive reasoning—featuring MoE, MLA, low‑cost training, and competitive performance against OpenAI’s GPT‑4o, while providing detailed usage guidance and cost analysis.

AI inferenceDeepSeekLarge Language Models
0 likes · 21 min read
Why DeepSeek Is Shaking Up the LLM Landscape: Architecture, Performance, and Cost
Architects' Tech Alliance
Architects' Tech Alliance
Mar 25, 2025 · Industry Insights

How Near‑Memory Computing Can Power Edge LLMs: A 2025 Storage Framework

The article analyzes the challenges of deploying large language models on cloud servers—such as latency, security, and constant connectivity—and explains how near‑memory computing architectures (PNM, PIM, CIM) can integrate storage and processing to enable efficient, high‑performance edge AI deployments, outlining the trade‑offs of each approach.

Artificial IntelligenceEdge AIIndustry Insights
0 likes · 5 min read
How Near‑Memory Computing Can Power Edge LLMs: A 2025 Storage Framework
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 25, 2025 · Artificial Intelligence

Boost Your AI Search Skills: Advanced Prompt & Query Tricks

This guide explains how to leverage AI tools with deep web‑search capabilities, covering site‑specific queries, wildcard operators, date ranges, Boolean logic, and effective prompt engineering techniques—including Socratic questioning and CRISPE framework—to improve information retrieval accuracy and efficiency across various domains.

AILarge Language ModelsSearch Operators
0 likes · 8 min read
Boost Your AI Search Skills: Advanced Prompt & Query Tricks
AI Frontier Lectures
AI Frontier Lectures
Mar 24, 2025 · Artificial Intelligence

What Can AI Agents Learn from the Latest AIR 2025 Research?

The article compiles insights from the AIR 2025 conference and related talks, covering the evolution of agents from reinforcement‑learning to LLM‑driven systems, novel agent architectures like AIDE, GUI agents, natural‑language reinforcement learning, and scaling advances in large language models such as Qwen, while highlighting key algorithms, benchmarks, and open research questions.

AI agentsAgent ArchitectureGUI agents
0 likes · 27 min read
What Can AI Agents Learn from the Latest AIR 2025 Research?
Model Perspective
Model Perspective
Mar 21, 2025 · Artificial Intelligence

How DeepSeek’s Tree‑Based Reasoning Transforms AI Interaction

DeepSeek’s R1 inference mode replaces linear chain‑of‑thought with a transparent, multi‑path tree reasoning system, offering layered analysis, intent understanding, memory management, emotion detection, and hallucination mitigation, illustrated through a practical example of buying authentic cigarettes and detailed technical breakdowns.

Artificial IntelligenceLarge Language ModelsMemory
0 likes · 16 min read
How DeepSeek’s Tree‑Based Reasoning Transforms AI Interaction
Continuous Delivery 2.0
Continuous Delivery 2.0
Mar 21, 2025 · Artificial Intelligence

AI-Driven Automated Unit Test Generation Framework: Architecture, Workflow, and Evaluation

This article presents an AI‑powered framework that automatically scans codebases, generates comprehensive unit tests using large language models, and includes self‑repair agents, detailing its workflow, core components, strategies for accuracy, practical benefits, and current limitations.

AI testingLarge Language Modelsself-repair
0 likes · 9 min read
AI-Driven Automated Unit Test Generation Framework: Architecture, Workflow, and Evaluation
AI Algorithm Path
AI Algorithm Path
Mar 20, 2025 · Artificial Intelligence

Understanding Multimodal Large Language Models: Recent Advances and Comparative Analysis

This article surveys the latest multimodal large language model research, dissecting the design, training strategies, and performance trade‑offs of models such as Llama 3.2, Molmo, NVLM, Qwen2‑VL, Pixtral, MM1.5, Emu3, and Janus, and highlights the challenges of fair cross‑model evaluation.

AI researchCross-AttentionLarge Language Models
0 likes · 16 min read
Understanding Multimodal Large Language Models: Recent Advances and Comparative Analysis
AI Frontier Lectures
AI Frontier Lectures
Mar 20, 2025 · Artificial Intelligence

Why Multimodal LLMs Still Struggle with Multi-Image Math Reasoning: Insights from MV‑MATH

This article introduces the MV‑MATH dataset, a large‑scale multi‑image math benchmark, and evaluates 24 open‑source and closed‑source multimodal large language models, revealing significant performance gaps, especially on complex visual dependencies and higher difficulty levels.

Large Language Modelsdatasetmath reasoning
0 likes · 8 min read
Why Multimodal LLMs Still Struggle with Multi-Image Math Reasoning: Insights from MV‑MATH
JavaScript
JavaScript
Mar 20, 2025 · Artificial Intelligence

How MiniMax’s Linear‑Attention Architecture Is Redefining Long‑Context AI Models

MiniMax’s rapid 2025 releases—including a video model, open‑source LLM, and high‑fidelity voice model—showcase its multimodal linear‑attention architecture that handles up to 4 million tokens, earns a16z recognition, and signals China’s growing influence in open‑source AI innovation.

Artificial IntelligenceLarge Language ModelsLinear Attention
0 likes · 8 min read
How MiniMax’s Linear‑Attention Architecture Is Redefining Long‑Context AI Models
AI Frontier Lectures
AI Frontier Lectures
Mar 17, 2025 · Artificial Intelligence

Can Diffusion Models Outrun Traditional LLMs? Mercury Coder’s Speed & Architecture

The article analyzes Mercury Coder, a diffusion‑based language model that generates text and code in parallel, compares its speed and quality against traditional autoregressive LLMs like GPT‑4o‑mini using a ball‑collision benchmark, and discusses the underlying score‑entropy training, current limitations, and future multimodal potential.

AI PerformanceBenchmarkLarge Language Models
0 likes · 8 min read
Can Diffusion Models Outrun Traditional LLMs? Mercury Coder’s Speed & Architecture
ZhongAn Tech Team
ZhongAn Tech Team
Mar 17, 2025 · Artificial Intelligence

Weekly Tech Digest: AI Model Advancements, Strategic Infrastructure Deals, and Industry Insights on AI Agents

This weekly technology digest highlights significant advancements in artificial intelligence, including OpenAI's Python-enabled o1 model, Google's open-source Gemma 3, and Alibaba's AI-driven Quark application, alongside major industry partnerships, expert forecasts on AI agent proliferation, and emerging developments in robotics and wearable technology.

AI agentsArtificial IntelligenceLarge Language Models
0 likes · 7 min read
Weekly Tech Digest: AI Model Advancements, Strategic Infrastructure Deals, and Industry Insights on AI Agents
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 17, 2025 · Artificial Intelligence

23 Proven Prompt Engineering Techniques to Make AI Understand You Instantly

As large language models become increasingly adept at natural language, mastering prompt engineering remains essential; this article compiles 23 practical strategies—from concise commands and role‑playing to structured formatting and output guidance—that empower users to communicate clearly with AI and obtain high‑quality, targeted results.

AI interactionAI productivityLarge Language Models
0 likes · 18 min read
23 Proven Prompt Engineering Techniques to Make AI Understand You Instantly
Fighter's World
Fighter's World
Mar 14, 2025 · Industry Insights

Will the 10× Growth Promise of Vertical AI Crumble as Generalist LLMs Like Manus Dominate the Market?

The article examines whether the surge of general‑purpose large language models such as Manus, Claude Sonet, and Qwen undermines the Bessemer Venture Partners claim that Vertical AI will grow tenfold, by analysing market size, use‑case demand, technical challenges, emerging business models, and competitive moats.

AI MarketAI agentsBusiness Models
0 likes · 19 min read
Will the 10× Growth Promise of Vertical AI Crumble as Generalist LLMs Like Manus Dominate the Market?
Zhihu Tech Column
Zhihu Tech Column
Mar 14, 2025 · Artificial Intelligence

Insights from Zhihu’s ZhiLight Large Model Inference Framework: Architecture, Parallelism, and Performance Optimizations

The article summarizes Zhihu’s technical talk on the ZhiLight large‑model inference framework, detailing model execution mechanisms, GPU load analysis, multi‑GPU parallel strategies, open‑source engine comparisons, compute‑communication overlap, quantization techniques, benchmark results, and future directions for scalable LLM deployment.

GPU parallelismLarge Language ModelsSGLang
0 likes · 11 min read
Insights from Zhihu’s ZhiLight Large Model Inference Framework: Architecture, Parallelism, and Performance Optimizations
Alimama Tech
Alimama Tech
Mar 14, 2025 · Artificial Intelligence

Advances in Search Advertising Models with Large Language Models (2024)

In 2024 Alibaba Mama outlines how large‑language models transform search advertising through a three‑line scaling roadmap—explicit inductive‑bias design, implicit compute growth, and auxiliary CV/NLP advances—implemented via a pre‑train/post‑train/CTR paradigm and the LUM user‑behavior model, promising gains in relevance, recall, and real‑time serving while highlighting inference efficiency challenges.

CTR predictionLarge Language ModelsScaling Law
0 likes · 25 min read
Advances in Search Advertising Models with Large Language Models (2024)
Baidu Tech Salon
Baidu Tech Salon
Mar 13, 2025 · Artificial Intelligence

How PaddlePaddle 3.0 Boosts Large‑Model Inference with 4‑Bit Quantization and MLA Optimizations

PaddlePaddle 3.0 introduces a full‑stack inference engine that supports FP8, INT8, and 4‑bit quantization for popular LLMs such as DeepSeek V3/R1, delivers up to 2× token throughput on a single H800 GPU, and provides detailed deployment scripts for single‑node and multi‑node setups, including MTP speculative decoding and SageAttention for long‑sequence acceleration.

DockerInference OptimizationLarge Language Models
0 likes · 13 min read
How PaddlePaddle 3.0 Boosts Large‑Model Inference with 4‑Bit Quantization and MLA Optimizations
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Mar 13, 2025 · Artificial Intelligence

From Chain‑of‑Thought to Self‑Evolving Agents: Lessons from AI Agent Engineering

This article traces the evolution of large‑model agents from a simple chain‑of‑thought design through tool and agent instantiation, structured PEER patterns, and self‑evolving architectures, highlighting practical challenges, middleware solutions, and open‑source resources for building robust AI agents.

AI agentsAgent ArchitectureLarge Language Models
0 likes · 16 min read
From Chain‑of‑Thought to Self‑Evolving Agents: Lessons from AI Agent Engineering
Architects' Tech Alliance
Architects' Tech Alliance
Mar 11, 2025 · Artificial Intelligence

How DeepSeek’s Breakthrough AI Models Thrive on Huawei Ascend: A Deep Dive

An in‑depth analysis reveals how DeepSeek’s V3 and R1 large‑language models achieve superior inference performance and cost efficiency on Huawei’s Ascend AI platform, detailing architectural optimizations, KV‑Cache reductions, multimodal support, real‑world deployments across finance, government, manufacturing, and the projected impact on the AI industry.

DeepSeekHuawei AscendLarge Language Models
0 likes · 4 min read
How DeepSeek’s Breakthrough AI Models Thrive on Huawei Ascend: A Deep Dive
AI Algorithm Path
AI Algorithm Path
Mar 11, 2025 · Artificial Intelligence

AI Agents Overview: Foundations, Core Components, and When to Use Them

This article provides a comprehensive overview of AI Agents, tracing their evolution from traditional chatbots to LLM‑driven agents, explaining core components such as perception, reasoning, action, knowledge bases, learning and communication interfaces, and discussing practical use cases, interaction cycles, and future prospects.

AI agentsAutonomous SystemsLarge Language Models
0 likes · 15 min read
AI Agents Overview: Foundations, Core Components, and When to Use Them
58 Tech
58 Tech
Mar 11, 2025 · Artificial Intelligence

Applying Large Language Models to Real Estate Recommendation: Case Studies and Optimization Techniques

This article presents a comprehensive case study on how large language models are integrated into 58.com’s real‑estate recommendation platform, detailing challenges, data adaptation, prompt and parameter optimizations, embedding generation, conversational recommendation, and future directions for multimodal and generative recommendation systems.

EmbeddingLarge Language ModelsPrompt Engineering
0 likes · 14 min read
Applying Large Language Models to Real Estate Recommendation: Case Studies and Optimization Techniques
Efficient Ops
Efficient Ops
Mar 9, 2025 · Artificial Intelligence

Essential LLMOps Tools: Build, Deploy, Monitor, and Manage Large Language Models

LLMOps, the end-to-end methodology for managing large language models, encompasses a curated set of development, deployment, monitoring, and local management tools—such as LangChain, vLLM, LangSmith, and Ollama—enabling practitioners to efficiently build, scale, and maintain AI applications.

AI developmentLLMOpsLarge Language Models
0 likes · 6 min read
Essential LLMOps Tools: Build, Deploy, Monitor, and Manage Large Language Models
Architects' Tech Alliance
Architects' Tech Alliance
Mar 9, 2025 · Industry Insights

DeepSeek’s AI Ecosystem: From Core Tech to Market Impact

This article provides a comprehensive analysis of DeepSeek, covering its foundational AI research, technology stack, product offerings, and the broader upstream, midstream, and downstream AI industry landscape, including hardware, server, cloud, and market trends.

AI infrastructureArtificial IntelligenceDeepSeek
0 likes · 13 min read
DeepSeek’s AI Ecosystem: From Core Tech to Market Impact
Fun with Large Models
Fun with Large Models
Mar 8, 2025 · Artificial Intelligence

Make AI Obey: A Detailed Prompt Engineering Guide to Boost Large‑Model Logic

This tutorial explains how to enhance large language models' logical reasoning by using DeepSeek‑R1's deep‑thinking mode, few‑shot prompting, chain‑of‑thought, and zero‑shot chain‑of‑thought techniques, providing concrete examples, comparisons, and a step‑by‑step template for effective prompt design.

AI reasoningDeepSeekLarge Language Models
0 likes · 10 min read
Make AI Obey: A Detailed Prompt Engineering Guide to Boost Large‑Model Logic
Code Mala Tang
Code Mala Tang
Mar 8, 2025 · Artificial Intelligence

14 Powerful Prompt Engineering Techniques to Unlock AI’s Full Potential

This article introduces the fundamentals of prompt engineering and presents fourteen practical techniques—ranging from role‑playing and step‑by‑step reasoning to chain‑of‑thought and ReAct—that help users craft precise, high‑quality prompts for any large language model, dramatically improving AI output.

AIAI productivityLLM techniques
0 likes · 16 min read
14 Powerful Prompt Engineering Techniques to Unlock AI’s Full Potential
Cognitive Technology Team
Cognitive Technology Team
Mar 7, 2025 · Artificial Intelligence

From Word Embeddings to Large Language Models: A Comprehensive Overview of AI Model Evolution

This article traces the development of AI models—from early word embeddings like Word2Vec and ELMo, through transformer‑based encoders such as BERT and decoder‑only models like GPT‑1/2/3, to recent multimodal systems and scaling laws—explaining their architectures, training methods, and impact on modern AI applications.

AIEmbeddingLarge Language Models
0 likes · 22 min read
From Word Embeddings to Large Language Models: A Comprehensive Overview of AI Model Evolution
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Mar 7, 2025 · Artificial Intelligence

How Pai‑Megatron‑Patch Boosts Qwen2‑VL Multimodal Training Efficiency

This article explains how the Pai‑Megatron‑Patch toolkit enhances the usability and training performance of the Qwen2‑VL multimodal large model by introducing model‑parallel weight conversion, user‑friendly data loading, visual feature processing optimizations, optimizer offloading, and pipeline parallelism techniques, supported by extensive experimental analysis.

Large Language ModelsMegatronPipeline Parallelism
0 likes · 25 min read
How Pai‑Megatron‑Patch Boosts Qwen2‑VL Multimodal Training Efficiency
dbaplus Community
dbaplus Community
Mar 7, 2025 · Artificial Intelligence

Master Prompt Engineering: Frameworks, Strategies, and Real‑World Examples for Large Language Models

This comprehensive guide explains what prompts are, outlines essential prompt components and multiple engineering frameworks, presents practical strategies for crafting clear and structured prompts, addresses model limitations such as hallucinations, and showcases a wide range of advanced prompting techniques with code examples.

AILLMLarge Language Models
0 likes · 29 min read
Master Prompt Engineering: Frameworks, Strategies, and Real‑World Examples for Large Language Models
Data Thinking Notes
Data Thinking Notes
Mar 6, 2025 · Artificial Intelligence

How China’s State‑Owned Giants Are Accelerating AI with DeepSeek

Amid a global digital surge, 45% of China’s central state‑owned enterprises have deployed the DeepSeek large‑model platform, rapidly integrating AI across energy, power, telecom, construction and other sectors to boost intelligent transformation and operational efficiency.

AI adoptionChinaDeepSeek
0 likes · 7 min read
How China’s State‑Owned Giants Are Accelerating AI with DeepSeek
JD Retail Technology
JD Retail Technology
Mar 6, 2025 · Artificial Intelligence

Dynamic Margin Selection for Efficient Deep Learning and Low-Resource Large Model Training

Jia Xing’s research introduces Dynamic Margin Selection, a technique that repeatedly refreshes a core set of boundary‑close samples to train large language models efficiently on limited resources, achieving comparable loss to full‑data training, enabling six‑fold model compression, faster inference, and a proposed exponential scaling law for data‑efficient AI.

ICLRLarge Language ModelsLow-Resource Training
0 likes · 10 min read
Dynamic Margin Selection for Efficient Deep Learning and Low-Resource Large Model Training
Tencent Technical Engineering
Tencent Technical Engineering
Mar 5, 2025 · Information Security

Detecting Critical AI Infrastructure Vulnerabilities with AI-Infra-Guard

As open‑source large language model tools like Ollama, OpenWebUI and ComfyUI gain popularity, numerous security flaws such as unauthenticated APIs, CVE‑exploits, model theft and remote code execution emerge, prompting the development of AI‑Infra‑Guard—a lightweight, cross‑platform scanner that identifies over 30 component vulnerabilities and offers both web UI and CLI modes for rapid risk assessment.

AI securityAI-Infra-GuardCVE
0 likes · 13 min read
Detecting Critical AI Infrastructure Vulnerabilities with AI-Infra-Guard
Architects' Tech Alliance
Architects' Tech Alliance
Mar 5, 2025 · Industry Insights

DeepSeek R1 & Kimi 1.5: Inside the Development of Near‑Strong Reasoning Models

The article analyzes DeepSeek's recent releases—V3 dialogue model and R1 inference model—detailing their launch dates, rapid popularity surge, R1's reinforcement‑learning‑based design for code and math tasks, and provides links to related Beijing University technical reports while stripping promotional sales content.

AIDeepSeekLarge Language Models
0 likes · 3 min read
DeepSeek R1 & Kimi 1.5: Inside the Development of Near‑Strong Reasoning Models
AntTech
AntTech
Mar 4, 2025 · Artificial Intelligence

GraphCLIP and 2D‑TPE: Enhancing Transferability of Graph Models and Table Understanding for Large Language Models

This article introduces GraphCLIP, a self‑supervised graph‑summary pre‑training framework that boosts zero‑ and few‑shot transferability of graph foundation models for text‑attributed graphs, and 2D‑TPE, a two‑dimensional positional encoding method that preserves table structure to markedly improve large language model performance on table‑understanding tasks, while also announcing a live paper session at WWW 2025 featuring the authors.

Large Language ModelsPositional EncodingSelf‑Supervised Learning
0 likes · 6 min read
GraphCLIP and 2D‑TPE: Enhancing Transferability of Graph Models and Table Understanding for Large Language Models
JD Retail Technology
JD Retail Technology
Feb 28, 2025 · Artificial Intelligence

Generative Recommendation with DPO Alignment for JD Alliance Advertising: Multi‑Objective Optimization and Online Results

The paper presents a generative recommendation framework for JD Alliance advertising that combines semantic‑ID modeling, large‑model pre‑training and fine‑tuning, and Direct Preference Optimization (including Softmax‑DPO and β‑DPO) to jointly boost click‑through and conversion rates, achieving +0.6% UCTR and +8% UCVR in online tests while outlining future multi‑objective extensions.

AdvertisingDPOGenerative Recommendation
0 likes · 12 min read
Generative Recommendation with DPO Alignment for JD Alliance Advertising: Multi‑Objective Optimization and Online Results
Architect
Architect
Feb 27, 2025 · Artificial Intelligence

Understanding Inference Large Language Models: DeepSeek‑R1 and the Rise of Test‑Time Computation

This article explains how inference‑oriented large language models such as DeepSeek‑R1 and OpenAI o1‑mini shift AI research from training‑time scaling to test‑time computation, detailing the underlying principles, new scaling laws, verification techniques, reinforcement‑learning pipelines, and practical methods for distilling reasoning capabilities into smaller models.

DeepSeek-R1Large Language Modelsinference
0 likes · 18 min read
Understanding Inference Large Language Models: DeepSeek‑R1 and the Rise of Test‑Time Computation
Code Mala Tang
Code Mala Tang
Feb 27, 2025 · Artificial Intelligence

Do New AI Reasoning Models Really Think? Unpacking the Debate

The article examines whether the latest AI models that claim to perform true reasoning—by breaking problems into steps and using chain‑of‑thought—actually reason like humans, presenting skeptical and supportive expert viewpoints, and offering practical guidance on how to use such models responsibly.

AI reasoningAI safetyLarge Language Models
0 likes · 14 min read
Do New AI Reasoning Models Really Think? Unpacking the Debate
DataFunSummit
DataFunSummit
Feb 26, 2025 · Artificial Intelligence

Applying Multimodal Large Models to Music Recommendation at NetEase Cloud Music

This article details how NetEase Cloud Music leverages multimodal large language models to improve music recommendation across daily, personalized, and playlist scenarios by extracting rich audio, text, and visual features, addressing data skew, cold‑start challenges, and achieving measurable gains in user engagement and distribution efficiency.

Large Language ModelsNetEase Cloud Musicfeature extraction
0 likes · 12 min read
Applying Multimodal Large Models to Music Recommendation at NetEase Cloud Music
AntTech
AntTech
Feb 26, 2025 · Artificial Intelligence

Ant Group’s 18 Accepted Papers at AAAI 2025: Summaries and Highlights

This article presents concise English summaries of the 18 Ant Group papers accepted at AAAI 2025, covering topics such as privacy‑preserving large‑model tuning, knowledge‑graph integration, AI‑generated image detection, multi‑task learning, generative retrieval, role‑playing evaluation, and video hallucination mitigation.

AAAI 2025AI evaluationGenerative Retrieval
0 likes · 29 min read
Ant Group’s 18 Accepted Papers at AAAI 2025: Summaries and Highlights
Ops Development & AI Practice
Ops Development & AI Practice
Feb 25, 2025 · Artificial Intelligence

What Is Hybrid Reasoning in Claude 3.7 Sonnet and Why It Matters

Hybrid reasoning lets Claude 3.7 Sonnet dynamically switch between fast, intuition‑like answers and step‑by‑step, deep analysis, improving both speed and accuracy for tasks ranging from simple code snippets to complex algorithm design, and signals a broader shift in large language model capabilities.

AI reasoningClaude 3.7Hybrid Reasoning
0 likes · 9 min read
What Is Hybrid Reasoning in Claude 3.7 Sonnet and Why It Matters
21CTO
21CTO
Feb 25, 2025 · Artificial Intelligence

How Alibaba’s Qwen 2.5‑Max Challenges GPT‑4o and Redefines China’s AI Race

Chinese tech giants Huawei and Alibaba respond to President Xi’s call for stronger innovation, with Huawei showcasing its HarmonyOS and server‑grade Arm processor while Alibaba unveils the Qwen 2.5‑Max large language model that outperforms leading Western AI systems on multiple benchmarks, highlighting China’s accelerating AI ambitions.

AIAlibabaChina
0 likes · 5 min read
How Alibaba’s Qwen 2.5‑Max Challenges GPT‑4o and Redefines China’s AI Race
Architecture Digest
Architecture Digest
Feb 25, 2025 · Artificial Intelligence

DeepSeek Distillation Technology: Overview, Innovations, Architecture, Training, Performance, and Challenges

DeepSeek’s distillation technology combines data and model distillation to transfer knowledge from large teacher models to compact student models, detailing its definitions, principles, key innovations, architecture, training methods, performance gains, and challenges, especially in multimodal contexts.

AI researchDeepSeekKnowledge Distillation
0 likes · 16 min read
DeepSeek Distillation Technology: Overview, Innovations, Architecture, Training, Performance, and Challenges
21CTO
21CTO
Feb 24, 2025 · Artificial Intelligence

From Transformers to DeepSeek-R1: Evolution of Large Language Models

Since the 2017 introduction of the Transformer architecture, this article chronicles the rapid development of large language models—including BERT, GPT series, multimodal systems, and the cost‑effective DeepSeek‑R1—highlighting key innovations, scaling trends, alignment techniques, and their transformative impact across AI research and industry.

AI evolutionDeepSeekLLM History
0 likes · 23 min read
From Transformers to DeepSeek-R1: Evolution of Large Language Models
Architects' Tech Alliance
Architects' Tech Alliance
Feb 24, 2025 · Artificial Intelligence

NSA: Hardware‑Optimized Sparse Attention Mechanism from DeepSeek, Peking University and University of Washington

The NSA mechanism introduces a three‑branch hardware‑optimized sparse attention architecture—token compression, token selection, and sliding window—combined with learnable gating to balance global and local context, dramatically improving inference speed and efficiency for long‑context large language models.

AI ArchitectureDeepSeekLarge Language Models
0 likes · 5 min read
NSA: Hardware‑Optimized Sparse Attention Mechanism from DeepSeek, Peking University and University of Washington
Su San Talks Tech
Su San Talks Tech
Feb 23, 2025 · Artificial Intelligence

How DeepSeek’s Distillation Breaks AI Model Limits: Core Principles & Performance

This article explores DeepSeek’s cutting‑edge distillation technology, detailing its definition, underlying principles, innovative data‑model fusion, architecture choices, training strategies, performance gains over large language models, and the remaining challenges in knowledge transfer and multimodal data processing.

DeepSeekKnowledge DistillationLarge Language Models
0 likes · 16 min read
How DeepSeek’s Distillation Breaks AI Model Limits: Core Principles & Performance
Architect
Architect
Feb 19, 2025 · Artificial Intelligence

Does Scaling Law Still Hold for Grok 3? A Deep Dive into LLM Training Economics

The article critically examines whether the pre‑training Scaling Law still applies to Grok 3, compares its compute usage and model size with DeepSeek and OpenAI models, evaluates the cost‑effectiveness of pre‑training, RL and test‑time scaling, and explores how these insights shape future large‑language‑model development strategies.

Grok-3Large Language ModelsPre‑training
0 likes · 11 min read
Does Scaling Law Still Hold for Grok 3? A Deep Dive into LLM Training Economics
AI Algorithm Path
AI Algorithm Path
Feb 19, 2025 · Artificial Intelligence

How Temperature Shapes Output in Large Language Models

The article explains the Temperature hyper‑parameter in large language models, shows how it modifies the softmax distribution, provides a Python visualisation script, and demonstrates through experiments that higher values increase creativity while lower values make outputs more deterministic.

Large Language ModelsPythonSampling
0 likes · 5 min read
How Temperature Shapes Output in Large Language Models
DataFunTalk
DataFunTalk
Feb 19, 2025 · Artificial Intelligence

Large Models: Concepts, Principles, Classifications and Applications

This report provides a comprehensive overview of large-scale AI models, explaining their definition, massive parameter and data requirements, underlying transformer architecture, classification into language, vision and multimodal models, notable examples such as DeepSeek, and a survey of popular AIGC tools and practical use cases.

AIGC toolsLarge Language ModelsLarge Models
0 likes · 9 min read
Large Models: Concepts, Principles, Classifications and Applications
Architects' Tech Alliance
Architects' Tech Alliance
Feb 19, 2025 · Industry Insights

Why DeepSeek One‑Stop AI Machines Are Redefining Private Model Deployment

The surge in demand for private AI deployment has prompted multiple vendors to launch DeepSeek one‑stop machines—integrated hardware solutions that support the full DeepSeek model family, offering higher stability, easier setup, customization, cost savings, and data security across diverse industry scenarios.

AI hardwareAI infrastructureDeepSeek
0 likes · 7 min read
Why DeepSeek One‑Stop AI Machines Are Redefining Private Model Deployment
Tencent Cloud Developer
Tencent Cloud Developer
Feb 19, 2025 · Industry Insights

Why Every Enterprise Needs a Knowledge‑Management System in the LLM Era

The article analyzes how the shift from data‑driven to knowledge‑driven operations, powered by large language models like DeepSeek, forces companies to build dynamic knowledge‑management platforms that integrate personal and corporate knowledge, improve efficiency, and create sustainable competitive advantage.

DeepSeekEnterprise AILarge Language Models
0 likes · 14 min read
Why Every Enterprise Needs a Knowledge‑Management System in the LLM Era
Architects' Tech Alliance
Architects' Tech Alliance
Feb 18, 2025 · Artificial Intelligence

How DeepSeek’s Latest Models Redefine AI Performance and Industry Adoption

The DeepSeek report details rapid model releases from 2024 onward, highlighting innovations such as model distillation, a 671 B MoE architecture, FP8 mixed‑precision, and the Janus‑Pro multimodal framework, while also documenting major cloud and chip providers' integration of these models into their services.

AI industry adoptionDeepSeekLarge Language Models
0 likes · 10 min read
How DeepSeek’s Latest Models Redefine AI Performance and Industry Adoption
DataFunTalk
DataFunTalk
Feb 18, 2025 · Artificial Intelligence

CODEI/O: Leveraging Code to Train Large Language Models for Enhanced Reasoning

The DeepSeek team introduced CODEI/O, a massive dataset that converts code into natural‑language reasoning chains, and demonstrated that training large language models on this data markedly improves their performance on diverse inference tasks, including non‑code domains, through a two‑stage training strategy.

CODEI/OLarge Language Modelscode reasoning
0 likes · 8 min read
CODEI/O: Leveraging Code to Train Large Language Models for Enhanced Reasoning
Cognitive Technology Team
Cognitive Technology Team
Feb 18, 2025 · Artificial Intelligence

Two Major Bottlenecks in Deploying Large Language Models: Machine Deception and Hallucination

Deploying large language models faces two critical challenges—machine deception, where AI generates plausible yet false content, and machine hallucination, where outputs are logically coherent but factually inaccurate—both undermining trust, and the article outlines their causes, impacts, and technical, ethical, and regulatory mitigation strategies.

Artificial IntelligenceLarge Language ModelsMachine Deception
0 likes · 6 min read
Two Major Bottlenecks in Deploying Large Language Models: Machine Deception and Hallucination
Architect's Alchemy Furnace
Architect's Alchemy Furnace
Feb 17, 2025 · Artificial Intelligence

24 Proven Prompt Formulas to Unlock DeepSeek’s Full Potential

Discover a comprehensive collection of 24 structured prompting techniques—from basic role‑play formulas to advanced cross‑disciplinary and managerial frameworks—designed to help users of DeepSeek and other large language models craft precise, high‑impact queries that dramatically improve response quality and efficiency.

AI promptingDeepSeekLarge Language Models
0 likes · 12 min read
24 Proven Prompt Formulas to Unlock DeepSeek’s Full Potential
Baobao Algorithm Notes
Baobao Algorithm Notes
Feb 17, 2025 · Artificial Intelligence

Can TransMLA Turn GQA into a More Powerful MLA? A Deep Dive into DeepSeek Models

This article presents a theoretical and experimental analysis of converting Group Query Attention (GQA) models to Multi‑Head Linear Attention (MLA) using the TransMLA method, demonstrating superior expressiveness and performance on DeepSeek‑based large language models while keeping KV‑Cache costs unchanged.

DeepSeekLarge Language ModelsMLA
0 likes · 11 min read
Can TransMLA Turn GQA into a More Powerful MLA? A Deep Dive into DeepSeek Models
Java Architecture Diary
Java Architecture Diary
Feb 17, 2025 · Artificial Intelligence

What Is LLMs.txt? The New AI‑Friendly Web Standard Explained

LLMs.txt is a lightweight, AI‑optimized web standard that provides concise Markdown navigation files for large language models, addressing context limits, redundant content, and lack of structure, and is already adopted by companies like Mintlify, Anthropic, and Cursor.

AI StandardsAI indexingLarge Language Models
0 likes · 6 min read
What Is LLMs.txt? The New AI‑Friendly Web Standard Explained
Fun with Large Models
Fun with Large Models
Feb 16, 2025 · Artificial Intelligence

Can You Claim to Know Large Models? Guide to Distillation, Quantization & Fine‑Tuning

This article explains why the massive DeepSeek V3/R1 model (671 B parameters) is hard to deploy and introduces three key techniques—model distillation, quantization, and fine‑tuning—that can shrink, accelerate, or specialize large models, while outlining their trade‑offs and practical steps.

AI model compressionDeepSeekLarge Language Models
0 likes · 10 min read
Can You Claim to Know Large Models? Guide to Distillation, Quantization & Fine‑Tuning
Architects' Tech Alliance
Architects' Tech Alliance
Feb 16, 2025 · Artificial Intelligence

How DeepSeek’s Distillation Breaks Bottlenecks and Boosts Multimodal AI Performance

This article provides an in‑depth technical analysis of DeepSeek’s model distillation technology, covering its core principles, innovative data‑model fusion strategies, architecture design, training optimizations, performance benchmarks, and the remaining challenges of scaling distillation to multimodal tasks.

DeepSeekLarge Language ModelsMultimodal
0 likes · 16 min read
How DeepSeek’s Distillation Breaks Bottlenecks and Boosts Multimodal AI Performance
Lao Guo's Learning Space
Lao Guo's Learning Space
Feb 15, 2025 · Artificial Intelligence

What Is deepseek-MoE? Understanding the Mixture‑of‑Experts Architecture

The article explains deepseek-MoE (Mixture of Experts), describing its full English name, Chinese translation, how a gating network selects and weights multiple expert models for each input, and uses an analogy to illustrate load‑balancing and the divide‑and‑conquer design in large AI models.

AI ArchitectureLarge Language ModelsMixture of Experts
0 likes · 2 min read
What Is deepseek-MoE? Understanding the Mixture‑of‑Experts Architecture
Ops Development & AI Practice
Ops Development & AI Practice
Feb 14, 2025 · Artificial Intelligence

Large Model Format Showdown: Hugging Face, TensorFlow, ONNX, TorchScript, GGUF

This comprehensive guide examines the leading large‑model storage formats—including Hugging Face Transformers, TensorFlow SavedModel, ONNX, TorchScript, and GGUF—detailing their file structures, serialization methods, strengths, weaknesses, and typical use‑cases, helping developers and researchers select the optimal format for their specific AI workloads.

AI deploymentGGUFLarge Language Models
0 likes · 21 min read
Large Model Format Showdown: Hugging Face, TensorFlow, ONNX, TorchScript, GGUF
DataFunSummit
DataFunSummit
Feb 14, 2025 · Artificial Intelligence

Building Large‑Scale Recommendation Systems with Big Data and Large Language Models on Alibaba Cloud AI Platform

This presentation details how Alibaba Cloud's AI platform integrates big‑data pipelines, feature‑store services, and large language model capabilities to construct high‑performance search‑recommendation architectures, covering system design, training and inference optimizations, LLM‑driven use cases, and open‑source RAG tooling.

AI PlatformBig DataFeature Store
0 likes · 17 min read
Building Large‑Scale Recommendation Systems with Big Data and Large Language Models on Alibaba Cloud AI Platform
Top Architect
Top Architect
Feb 14, 2025 · Artificial Intelligence

DeepSeek Model Distillation: Principles, Innovations, Architecture, and Performance

This article provides an in‑depth overview of DeepSeek’s model distillation technology, covering its definition, core principles, innovative data‑model distillation integration, architecture design, training strategies, performance gains, and the challenges of scaling to multimodal data.

DeepSeekKnowledge TransferLarge Language Models
0 likes · 16 min read
DeepSeek Model Distillation: Principles, Innovations, Architecture, and Performance
Ma Wei Says
Ma Wei Says
Feb 13, 2025 · Artificial Intelligence

Master AI Prompting: 5 Proven Techniques to Unlock Accurate Outputs

This guide presents five practical prompting techniques—including structured output, role‑playing, visual conversion, multi‑turn refinement, and multilingual handling—plus industry‑specific examples and common pitfalls, helping users craft precise commands for AI models like DeepSeek.

AI promptingLarge Language ModelsPrompt Engineering
0 likes · 8 min read
Master AI Prompting: 5 Proven Techniques to Unlock Accurate Outputs
Architect
Architect
Feb 12, 2025 · Artificial Intelligence

Can S‑Curve Theory Explain the Limits of Large‑Model Scaling Laws?

The article analyses how S‑shaped growth curves can model the apparent scaling laws of large language models, discusses the three phases of model development, proposes an ability‑density hypothesis, and explores future scenarios where scaling laws may plateau or shift.

AI growthAbility DensityLarge Language Models
0 likes · 16 min read
Can S‑Curve Theory Explain the Limits of Large‑Model Scaling Laws?
Architect
Architect
Feb 12, 2025 · Artificial Intelligence

Master Prompt Engineering: A Universal Framework for LLMs

This article presents a comprehensive, step‑by‑step Prompt engineering framework—including role definition, problem description, goal setting, and requirement specification—augmented with techniques such as RAG, few‑shot examples, memory handling, and parameter tuning, enabling users to craft effective prompts for large language models across domains.

AI Prompt OptimizationFew-shotLarge Language Models
0 likes · 27 min read
Master Prompt Engineering: A Universal Framework for LLMs
AIWalker
AIWalker
Feb 11, 2025 · Artificial Intelligence

LLMDet: LLM‑Powered Open‑Vocabulary Detector Beats Grounding DINO

LLMDet introduces a novel training pipeline that leverages large language models to generate detailed image‑level captions and region‑level phrases, fine‑tunes an open‑vocabulary detector with the GroundingCap‑1M dataset, and achieves state‑of‑the‑art zero‑shot performance surpassing Grounding DINO across multiple benchmarks.

GroundingCapLLMDetLarge Language Models
0 likes · 20 min read
LLMDet: LLM‑Powered Open‑Vocabulary Detector Beats Grounding DINO
DataFunTalk
DataFunTalk
Feb 11, 2025 · Artificial Intelligence

Roundtable on Enhancing Large Model Effectiveness: RAG, Tool Use, and Knowledge Engineering

Experts from Dipu, Ant Financial, iKang, and Zhihu discuss practical strategies for improving large model performance, covering RAG, tool‑using, offline knowledge engineering, multimodal training, evaluation metrics, and future trends, while sharing case studies from manufacturing, healthcare, retail, and C‑end applications.

Knowledge EngineeringLarge Language ModelsRAG
0 likes · 9 min read
Roundtable on Enhancing Large Model Effectiveness: RAG, Tool Use, and Knowledge Engineering
Cognitive Technology Team
Cognitive Technology Team
Feb 10, 2025 · Artificial Intelligence

Survey of Major Chinese AI Large Language Models: Technologies, Innovations, and Comparative Evaluation

This report systematically reviews the key technologies, innovations, and performance of leading Chinese AI large language models—including DeepSeek, Kimi, and Qwen2.5—detailing their architectures, training methods, multimodal capabilities, and comparative evaluations against each other and foreign models.

AIChinaLarge Language Models
0 likes · 20 min read
Survey of Major Chinese AI Large Language Models: Technologies, Innovations, and Comparative Evaluation
AI Algorithm Path
AI Algorithm Path
Feb 10, 2025 · Artificial Intelligence

Understanding DualPipe: DeepDive into DeepSeek‑R1 Architecture (Part 5)

This article explains how the DualPipe scheduling mechanism in DeepSeek‑R1 improves GPU cluster compute‑communication efficiency by using fine‑grained pipeline stages and bidirectional data flow, comparing it with Zero Bubble pipeline parallelism and discussing the challenges of large‑scale distributed training.

DeepSeekDualPipeLarge Language Models
0 likes · 10 min read
Understanding DualPipe: DeepDive into DeepSeek‑R1 Architecture (Part 5)
IT Architects Alliance
IT Architects Alliance
Feb 10, 2025 · Artificial Intelligence

DeepSeek Distillation Technology: Principles, Innovations, Performance, and Future Outlook

The article explains DeepSeek's model distillation technique, covering its fundamental knowledge‑transfer principles, unique innovations such as data‑model fusion and task‑specific strategies, impressive benchmark results, practical applications in edge and online inference, existing challenges, and future research directions.

Knowledge TransferLarge Language Modelsai-optimization
0 likes · 15 min read
DeepSeek Distillation Technology: Principles, Innovations, Performance, and Future Outlook
Baidu Geek Talk
Baidu Geek Talk
Feb 10, 2025 · Artificial Intelligence

How Baidu Cloud Slashes Inference Costs: DeepSeek Model Optimizations Unveiled

Baidu Cloud's Qianfan platform launched DeepSeek‑R1 and DeepSeek‑V3 with ultra‑low inference pricing, leveraging advanced engine performance tweaks, a split Prefill/Decode architecture, and comprehensive security measures that together boost throughput, cut costs, and ensure enterprise‑grade reliability.

AI inferenceBaidu CloudLarge Language Models
0 likes · 5 min read
How Baidu Cloud Slashes Inference Costs: DeepSeek Model Optimizations Unveiled
Architects' Tech Alliance
Architects' Tech Alliance
Feb 10, 2025 · Artificial Intelligence

Why DeepSeek Is Disrupting the Global AI Landscape: Tech, Cost, and Open‑Source Edge

DeepSeek, a Chinese AI startup, has rapidly risen to global prominence by releasing high‑performance large language models such as V2, V3, and R1, which combine innovative architectures, dramatically lower training costs, and an open‑source strategy that challenges established AI giants and reshapes industry dynamics.

Artificial IntelligenceChina AIDeepSeek
0 likes · 14 min read
Why DeepSeek Is Disrupting the Global AI Landscape: Tech, Cost, and Open‑Source Edge