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Old Zhang's AI Learning
Old Zhang's AI Learning
Apr 19, 2026 · Artificial Intelligence

Qwen3.6-35B: 4‑bit Quantization, DFlash Speedup, Claude Opus Distillation

The article reviews three optimization paths for the Qwen3.6‑35B model—four‑bit AWQ quantization variants, the DFlash speculative decoding accelerator, and a Claude Opus‑based distillation—detailing their implementation steps, benchmark results, and guidance on selecting the best version for different hardware and performance needs.

AIDFlashDistillation
0 likes · 11 min read
Qwen3.6-35B: 4‑bit Quantization, DFlash Speedup, Claude Opus Distillation
AI Architect Hub
AI Architect Hub
Apr 19, 2026 · Artificial Intelligence

Mastering RAG: From Data Cleaning to Vector DBs in AI Applications

This article introduces the second stage of a large‑model application series, detailing the value of Retrieval‑Augmented Generation (RAG), its architecture, and a step‑by‑step outline covering data cleaning, text chunking, vectorization, vector‑DB selection, recall strategies, reranking, and prompt construction.

AILLMPrompt engineering
0 likes · 4 min read
Mastering RAG: From Data Cleaning to Vector DBs in AI Applications
Smart Workplace Lab
Smart Workplace Lab
Apr 19, 2026 · Industry Insights

How to Turn AI-Boosted Productivity into Visible Performance Metrics

This article presents a practical framework for documenting AI‑enhanced work contributions, introducing a weekly performance‑evidence matrix that quantifies decision density, risk interception, and asset accumulation, along with communication scripts tailored to different manager types and step‑by‑step SOPs for archiving proof, helping professionals turn speed gains into measurable performance value.

AIEvidencemetrics
0 likes · 7 min read
How to Turn AI-Boosted Productivity into Visible Performance Metrics
Raymond Ops
Raymond Ops
Apr 19, 2026 · Cloud Native

How to Double K8s Ingress Performance: Nginx vs Envoy Gateway Tuning Guide

This article walks through a real‑world performance bottleneck on a high‑traffic e‑commerce platform, explains step‑by‑step deep tuning of Nginx Ingress Controller, compares it with Envoy Gateway, and provides concrete configurations, benchmark results, monitoring rules, and best‑practice recommendations for Kubernetes Ingress optimization.

EnvoyIngressKubernetes
0 likes · 27 min read
How to Double K8s Ingress Performance: Nginx vs Envoy Gateway Tuning Guide
DataFunSummit
DataFunSummit
Apr 19, 2026 · Big Data

How OPPO Built a Multi‑Modal Data Lake with Gravitino and Curvine

OPPO’s data‑lake team, led by David, detailed their transition from Hive‑Spark to a unified multi‑modal lake, leveraging Gravitino for cross‑engine metadata management and the open‑source Curvine cache to eliminate data silos, boost I/O performance, and support massive image, recommendation, and AI‑Agent workloads.

Data LakeDistributed Cachebig data
0 likes · 11 min read
How OPPO Built a Multi‑Modal Data Lake with Gravitino and Curvine
DataFunSummit
DataFunSummit
Apr 19, 2026 · Artificial Intelligence

How to Build a Multimodal Product Search Engine with Embedding and Vector Retrieval on Elasticsearch Serverless

This article explains a complete multimodal product search solution that combines text and image embeddings, dense, sparse, and hybrid models, vector similarity metrics, and Elasticsearch Serverless features such as dense_vector, sparse_vector, hybrid search, quantization, and RRF ranking to achieve fast, accurate, and cost‑effective retrieval.

AIElasticsearchEmbedding
0 likes · 20 min read
How to Build a Multimodal Product Search Engine with Embedding and Vector Retrieval on Elasticsearch Serverless
FunTester
FunTester
Apr 19, 2026 · Artificial Intelligence

How AI Can Reduce Deployment Failures by Up to 50% and Boost Team Efficiency

This article analyzes why software deployment failures pose systemic risks, enumerates the most common root causes, and explains how AI‑driven automation—covering intelligent version control, automatic rollback, test optimization, dependency management, database migration, observability, security checks, self‑documenting pipelines, backup verification, and predictive scaling—can transform DevOps from reactive firefighting to proactive, self‑healing delivery.

AIContinuous IntegrationDeployment Automation
0 likes · 15 min read
How AI Can Reduce Deployment Failures by Up to 50% and Boost Team Efficiency
IT Services Circle
IT Services Circle
Apr 19, 2026 · Industry Insights

Why AI Is the Next Battleground for Web Browsers

The article analyzes how major browser vendors—from Microsoft and Google to Chinese players like Tencent and Meituan—are embedding AI features, categorizes the emerging AI‑assisted and AI‑autonomous browsers, and examines the technical, privacy, and user‑experience challenges shaping this new industry frontier.

AI browsersAI integrationChinese browsers
0 likes · 7 min read
Why AI Is the Next Battleground for Web Browsers
IT Services Circle
IT Services Circle
Apr 19, 2026 · Artificial Intelligence

How to Seamlessly Add AI Coding Assistants to IntelliJ IDEA

This guide walks you through configuring IntelliJ IDEA to use AI coding assistants like Claude, Codex, OpenAI‑compatible APIs, and local models via Ollama, covering plugin installation, provider setup, API key entry, and usage tips with screenshots.

AI assistantClaudeCodex
0 likes · 6 min read
How to Seamlessly Add AI Coding Assistants to IntelliJ IDEA
IT Services Circle
IT Services Circle
Apr 19, 2026 · Industry Insights

Why DeepSeek Is Moving Its AI Heart to the Mongolian Grasslands

DeepSeek’s latest hiring push reveals a strategic shift from algorithmic research to building and operating a high‑efficiency data center in Inner Mongolia’s Ulanqab, leveraging low‑temperature climate and existing cloud infrastructure to cut TCO, while gearing up for the upcoming V4 trillion‑parameter model.

AI infrastructureCloud ComputingDeepSeek
0 likes · 5 min read
Why DeepSeek Is Moving Its AI Heart to the Mongolian Grasslands
Java Tech Workshop
Java Tech Workshop
Apr 19, 2026 · Backend Development

Getting Started with Sharding-JDBC in SpringBoot: A Practical Guide to Database Sharding

When a single database table grows to millions of rows, query performance and storage become bottlenecks, and this article explains why sharding is needed, introduces Sharding-JDBC as a lightweight solution, and walks through the complete setup, configuration, code implementation, testing, and advanced concepts such as sharding strategies, key generation, binding tables, and broadcast tables for SpringBoot projects.

Horizontal PartitioningMyBatisMySQL
0 likes · 33 min read
Getting Started with Sharding-JDBC in SpringBoot: A Practical Guide to Database Sharding
AI Explorer
AI Explorer
Apr 19, 2026 · Artificial Intelligence

How Claude’s Design System Prompt Turns AI into an Expert Designer

The article reveals Claude’s design system prompt, detailing its role as an expert designer, a six‑step workflow, context‑driven methodology, exploration modes, strict technical rules, built‑in collaboration tools, and ethical content guidelines that together enable the AI to produce high‑quality, user‑centric designs.

AI DesignClaudePrompt engineering
0 likes · 6 min read
How Claude’s Design System Prompt Turns AI into an Expert Designer
Java Tech Enthusiast
Java Tech Enthusiast
Apr 19, 2026 · Interview Experience

Counting Boomerangs Efficiently: Hash‑Map Solution for LeetCode 447

This article explains how to count all boomerang tuples in a set of distinct points by using a hash‑map to store distance frequencies for each anchor point, achieving O(n²) time without costly square‑root calculations and providing Java, C++, and Python implementations.

BoomerangHashMapLeetCode
0 likes · 7 min read
Counting Boomerangs Efficiently: Hash‑Map Solution for LeetCode 447
Data Party THU
Data Party THU
Apr 19, 2026 · Artificial Intelligence

Mapping Large-Scale AI Agent Networks: A 3‑Dimensional Classification Framework

The article reviews recent growth in AI agent marketplaces and systems, introduces a three‑dimensional framework—topology, memory scope, and update behavior—to categorize large‑scale multi‑agent networks, and highlights world‑model inconsistency as the core scalability bottleneck.

AI agentsMulti-agent systemsScalability
0 likes · 8 min read
Mapping Large-Scale AI Agent Networks: A 3‑Dimensional Classification Framework
Su San Talks Tech
Su San Talks Tech
Apr 19, 2026 · Artificial Intelligence

Is MCP Dead? How CLI Is Redefining AI Agent Interactions

The article examines the rise and decline of the Model Context Protocol (MCP), outlines its four critical flaws—including context bloat, architectural complexity, security risks, and passive tool design—while presenting command‑line interfaces (CLI) as a more efficient, secure, and debuggable alternative for AI agents, and discusses hybrid approaches and practical implementations.

AI agentsCLIHybrid Architecture
0 likes · 15 min read
Is MCP Dead? How CLI Is Redefining AI Agent Interactions
Old Zhang's AI Learning
Old Zhang's AI Learning
Apr 19, 2026 · Artificial Intelligence

From Zero to Deployment: A Complete Qwen3.5 Fine‑Tuning Guide

This guide shows how to fine‑tune Qwen3.5 models—from 0.8B to 122B—using Unsloth Studio or pure code, covering text SFT, vision fine‑tuning, MoE models, reinforcement‑learning (GRPO), extensive GGUF quantization benchmarks, hardware requirements, export formats, and deployment tips.

Fine-tuningLLMQwen3.5
0 likes · 12 min read
From Zero to Deployment: A Complete Qwen3.5 Fine‑Tuning Guide
Old Zhang's AI Learning
Old Zhang's AI Learning
Apr 19, 2026 · Artificial Intelligence

8 Hard-Hitting AI Career Tips from Andrew Ng’s Stanford Lecture

In a dense 1‑hour‑44‑minute Stanford talk, Andrew Ng outlines eight actionable insights for AI professionals—including the rapid acceleration of AI capabilities, the shift from coding to product decisions, the importance of product intuition, rapid iteration, staying on cutting‑edge tools, leveraging supportive communities, and evaluating AI‑generated code debt.

AIAI toolsProduct Management
0 likes · 8 min read
8 Hard-Hitting AI Career Tips from Andrew Ng’s Stanford Lecture