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143150 articles · Page 283 of 7158
CodeNotes
CodeNotes
May 23, 2026 · Frontend Development

Mastering CSS: Animations, Transitions, and Responsive Design (Part 3)

This article walks through CSS transition syntax and parameters, demonstrates common transition effects, explains 2D and 3D transforms, details @keyframes animation properties and fill‑modes, introduces CSS custom properties for theming, shows media‑query‑based responsive design techniques, and covers performance tips such as will‑change and scroll‑snap.

CSSanimationscss-variables
0 likes · 22 min read
Mastering CSS: Animations, Transitions, and Responsive Design (Part 3)
Code Mala Tang
Code Mala Tang
May 23, 2026 · Artificial Intelligence

By 2026, AI Programming Rewards Context Management Over Pure Coding

The article argues that as AI coding agents evolve from autocomplete to task‑level assistants, developers’ most valuable skill shifts from writing code to orchestrating context, breaking down tasks, defining boundaries, and managing agents within the software production workflow.

AI programmingContext Engineeringcoding agents
0 likes · 11 min read
By 2026, AI Programming Rewards Context Management Over Pure Coding
SuanNi
SuanNi
May 23, 2026 · Artificial Intelligence

Deploy the Open-Source ChatLaw Legal LLM on the SuanWang Platform

This article introduces ChatLaw, an open‑source legal large language model trained on 936,727 real cases, explains its high‑dimensional embedding ChatLaw‑Text2Vec for fast knowledge alignment, and provides a step‑by‑step guide to deploy it on the SuanWang cloud platform using Python and MLU resources.

ChatLawDeploymentLLM
0 likes · 3 min read
Deploy the Open-Source ChatLaw Legal LLM on the SuanWang Platform
SuanNi
SuanNi
May 23, 2026 · Artificial Intelligence

How Andrej‑Karpathy‑Skills Fixes Karpathy’s AI Coding Pitfalls

The article examines the open‑source "andrej‑karpathy‑skills" project, which encodes four principled rules to curb LLM‑driven coding errors identified by Andrej Karpathy, and shows how applying these rules improves developer productivity and code quality.

AI agentsClaude CodeKarpathy
0 likes · 10 min read
How Andrej‑Karpathy‑Skills Fixes Karpathy’s AI Coding Pitfalls
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
May 23, 2026 · Artificial Intelligence

Google I/O Introduces Gemini 3.5 Flash – Faster, Cheaper Than 3.1 Pro – and Antigravity 2.0

Google's I/O unveiled Gemini 3.5 Flash, a model that runs four times faster and costs far less than the previous 3.1 Pro while topping benchmark leaderboards, alongside the Antigravity 2.0 "Claude Code" development environment, new Gemini Spark agents, the multimodal Gemini Omni world‑model, and major Search upgrades that add information agents and generative UI capabilities.

AI agentsAntigravity 2.0Gemini 3.5 Flash
0 likes · 10 min read
Google I/O Introduces Gemini 3.5 Flash – Faster, Cheaper Than 3.1 Pro – and Antigravity 2.0
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
May 23, 2026 · Industry Insights

OpenAI Codex’s Major Update: Screen‑Free Coding, AI “Goal” Mode, and PowerPoint Integration

OpenAI’s latest Codex upgrade adds Appshots for double‑Command screen reading, a 24/7 “Goal” mode for long‑running tasks, locked‑Mac remote control, and a ChatGPT‑for‑PowerPoint plugin that auto‑generates editable slides, signaling a shift from a coding assistant to a full‑stack AI coworker.

AI automationAppshotsCodeX
0 likes · 9 min read
OpenAI Codex’s Major Update: Screen‑Free Coding, AI “Goal” Mode, and PowerPoint Integration
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
May 23, 2026 · Artificial Intelligence

10M‑Parameter Model Solves ARC and Sudoku – Bengio Team Bets on Multi‑Trajectory Reasoning

A 10‑million‑parameter GRAM model from Bengio, KAIST, Mila and NYU achieves 97% accuracy on Sudoku‑Extreme and competitive scores on ARC‑AGI tasks by replacing deterministic recursive updates with a probabilistic multi‑trajectory process, and extensive ablations show that both random guidance and depth‑supervised training are essential for its performance.

ARC‑AGIGRAMGenerative Recursive Reasoning
0 likes · 9 min read
10M‑Parameter Model Solves ARC and Sudoku – Bengio Team Bets on Multi‑Trajectory Reasoning
Spring Full-Stack Practical Cases
Spring Full-Stack Practical Cases
May 23, 2026 · Backend Development

How to Use @Lock in Spring Boot to Solve Concurrency Issues

This article explains how Spring Boot 3.5.0 leverages the @Lock annotation and JPA LockModeType to apply pessimistic read or write locks, shows custom repository implementations, provides concrete code snippets and generated SQL, and emphasizes that all lock operations must run inside a transaction.

Spring Bootcustom-repositoryjpa
0 likes · 7 min read
How to Use @Lock in Spring Boot to Solve Concurrency Issues
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
May 23, 2026 · Operations

Why Offline Deployment of Dify Is So Challenging – 10 Common Pitfalls and Solutions

Deploying Dify in an offline environment is fraught with hidden traps—from missing Docker images and vector‑database dependencies to network subnet conflicts, plugin‑daemon crashes, and silent external service time‑outs—requiring careful preparation, configuration, and maintenance to achieve a stable setup.

DifyDockerEnvironment variables
0 likes · 14 min read
Why Offline Deployment of Dify Is So Challenging – 10 Common Pitfalls and Solutions
James' Growth Diary
James' Growth Diary
May 23, 2026 · Artificial Intelligence

Easter Egg: /thinkback Year‑in‑Review vs /btw Bypass – Two Commands, Two Engineering Philosophies

The article dissects Claude Code’s /thinkback command that generates a yearly ASCII animation via a delegated skill and a stateless UI, and the /btw bypass query that preserves main‑thread context through cloning and defensive checks, highlighting contrasting design philosophies of presentation versus isolation.

AI agentsClaude CodeContext Isolation
0 likes · 10 min read
Easter Egg: /thinkback Year‑in‑Review vs /btw Bypass – Two Commands, Two Engineering Philosophies
James' Growth Diary
James' Growth Diary
May 23, 2026 · Artificial Intelligence

Choosing the Right Retrieval Strategy: Full‑Text vs Vector vs Graph Search

This article breaks down the underlying logic, ideal scenarios, benchmark data, decision trees, and real‑world case studies for full‑text (BM25), vector, and graph retrieval, showing why hybrid approaches dominate production while each technique has distinct strengths and trade‑offs.

Full-Text SearchRAGVector Search
0 likes · 25 min read
Choosing the Right Retrieval Strategy: Full‑Text vs Vector vs Graph Search
PaperAgent
PaperAgent
May 23, 2026 · Artificial Intelligence

Why Large Language Models Can't Achieve Consciousness, According to Google

Google DeepMind researchers argue that, contrary to popular speculation, AI systems cannot possess consciousness because consciousness is a physical phenomenon that precedes computation, and the prevailing computational functionalism mistakenly treats computation as the bridge to consciousness, leading to a flawed ontological inversion.

AI consciousnessAI safetycomputational functionalism
0 likes · 8 min read
Why Large Language Models Can't Achieve Consciousness, According to Google
AI Agent Super App
AI Agent Super App
May 23, 2026 · Operations

Top 10 TCP/UDP Interview Questions Every Network Ops Engineer Must Know

This guide compiles ten high‑frequency interview questions on TCP and UDP, covering core concepts, handshake mechanics, reliability features, congestion control, packet framing issues, SYN‑Flood attacks, and essential Linux commands for inspecting and troubleshooting connections.

Interview QuestionsSYN FloodUDP
0 likes · 16 min read
Top 10 TCP/UDP Interview Questions Every Network Ops Engineer Must Know
Machine Heart
Machine Heart
May 23, 2026 · Artificial Intelligence

Bengio’s New Paper Pushes Recursive Reasoning Limits with Parallel Trajectories

The paper introduces GRAM (Generative Recursive Reasoning Models), a probabilistic multi‑trajectory recursive reasoning framework that injects learnable randomness into each recursion step, enabling parallel sampling and achieving higher accuracy than deterministic baselines across tasks such as Sudoku‑Extreme, N‑Queens, ARC‑AGI and unconditional generation.

AI modelsGRAMparallel sampling
0 likes · 12 min read
Bengio’s New Paper Pushes Recursive Reasoning Limits with Parallel Trajectories
Machine Heart
Machine Heart
May 23, 2026 · Artificial Intelligence

How FlashAR Achieves 22.9× Speedup with Only 0.05% of Training Data

FlashAR transforms pretrained autoregressive image models into highly parallel generators, delivering up to 22.9× end-to-end speedup while using just 0.05% of the original training data and preserving generation quality, thanks to intermediate branching, a learnable fusion gate, and a two-stage adaptation process.

FlashARParallel Decodingautoregressive generation
0 likes · 10 min read
How FlashAR Achieves 22.9× Speedup with Only 0.05% of Training Data
Old Zhang's AI Learning
Old Zhang's AI Learning
May 23, 2026 · Artificial Intelligence

The Underrated Lifesaving Template for Qwen Local Deployment

This article analyzes the hidden pitfalls of Qwen's official Jinja chat template, explains how the community‑maintained Qwen‑Fixed‑Chat‑Templates v19 fixes rendering errors, KV‑Cache loss, token waste and agent dead‑locks, and provides step‑by‑step installation instructions for LM Studio, llama.cpp, vLLM and MLX.

Agent LoopChat TemplateKV cache
0 likes · 10 min read
The Underrated Lifesaving Template for Qwen Local Deployment
DeepHub IMBA
DeepHub IMBA
May 23, 2026 · Artificial Intelligence

Reason → Act → Observe: Building an Agentic Loop with LangChain and Python

This article explains what an agentic loop is, contrasts it with single‑pass chatbots, outlines its five stages, shows a visual architecture, walks through a concrete multi‑step example, provides Python pseudocode and a LangChain implementation, and discusses when to use or avoid such loops.

AI agentsAgentic LoopLLM
0 likes · 8 min read
Reason → Act → Observe: Building an Agentic Loop with LangChain and Python