#kernel function
489 related articles
·2 min
From Beginner to Advanced AI Agent Development: A Deep Dive into One Essential Hands-On Book
A deep dive into a hands-on AI Agent development book covering component architecture, RAG, multi-agent systems, Function Calling, and production observability.
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Zig Creator Calls Out Anthropic: The G…
·2 min
Zig Creator Calls Out Anthropic: The Gap Between AI Hype and Technical Reality
Zig creator Andrew Kelley publicly criticizes Anthropic for "blowing smoke" in AI marketing. A deep dive into the tension between AI hype and engineering integrity.
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Clawk: Creating Disposable Linux Sandb…
·2 min
Clawk: Creating Disposable Linux Sandbox Environments for AI Coding Assistants
Clawk offers a core solution to AI coding assistant security risks: disposable Linux VMs that isolate SSH keys, API tokens, and sensitive data from agents like Claude Code and Cursor.
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·3 min
Distributed AI Systems in Practice: A Complete Guide to Training, Inference, and Production Deployment
A deep dive into Distributed AI Systems: a new book distilling 10 years of AI engineering experience covering distributed training, inference optimization, and production model serving.
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·3 min
GitHub Daily · July 13: Rust Rewrite of Postgres Ignites the Community, Claude Ecosystem and Local-First Wave Surge Together
GitHub Daily July 13: pgrust rewrites Postgres in Rust and passes 100% regression tests, surging 789 stars in a day. Claude cookbooks and local-first Home Assistant also trend.
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·4 min
Claude Code vs. Codex vs. Cursor: A Deep Comparison of Three AI Coding Tools
Claude Code, Codex, or Cursor? This in-depth comparison covers each tool's positioning, ideal users, and how to combine them for maximum productivity in your AI coding workflow.
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·2 min
Run Python in Your Browser! Why This Free Machine Learning Course Is Worth a Try
ai.coredump.digital is a completely free, no-signup, from-scratch machine learning course that runs Python directly in your browser, covering 11 ordered learning tracks with 970 quiz questions and an interview drill mode.
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·3 min
Anthropic's Project Glass Wing: The Arms Race in AI Code Security Auditing
Anthropic launches Project Glass Wing—its Mythos Preview model found over 10,000 critical infrastructure vulnerabilities in hours, spanning 150 organizations across 15 countries. A deep dive into AI security auditing.
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·2 min
AI Over-Engineering: A Deep Reflection on Why One Line of Code Becomes a Thousand
A Reddit meme struck a collective nerve among developers: AI coding assistants routinely over-engineer simple tasks—turning one line into a thousand. This article dissects the technical roots of this phenomenon.
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·3 min
pgrust: Rewriting Postgres in Rust — 100% Regression Tests Passing
pgrust is an open-source project rewriting PostgreSQL entirely in Rust, claiming 100% regression test passage. This article analyzes the technical motivation, implementation approach, and key challenges.
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·4 min
Do You Still Need to Hand-Code Machine Learning Algorithms in the AI Era? The Answer and the Method
With AI tools everywhere, is it still worth hand-coding SVM, decision trees, and other ML algorithms? This article explores the real value of hand-coding, the limits of AI tools, and smarter learning strategies for beginners in the AI era.
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·5 min
Complete Guide to the National Mathematical Modeling Contest: Modeling, Topic Selection, and Award-Winning Strategies in the AI Era
A comprehensive guide to preparing for the National Mathematical Modeling Contest: covering the essence of modeling, judging rules, topic selection, AI usage guidelines, and a four-day schedule to boost your chances of winning.
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·4 min
6 Months of Self-Taught Machine Learning: A Complete Roadmap from Zero to Job-Ready
A self-learner completed a full progression from math foundations and core ML to deep learning in 6 months—hand-writing a Transformer and implementing gradient boosting from scratch. This article breaks down the highlights and blind spots of this real roadmap.
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·7 min
Building a Published App with Zero Code in Four Days: A Complete HarmonyOS Development Journey
A tech blogger with zero programming knowledge built a retro DV app in four days using AI tools like Cursor and Codex, and got it published on Huawei App Gallery. A full vibe coding walkthrough.
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The Theory of Deep Learning: Why Do Ne…
·4 min
The Theory of Deep Learning: Why Do Neural Networks Work? A Complete Overview of Theoretical Research
Deep learning shines in practice, but why does theory always lag behind? This article surveys the over-parameterization paradox, implicit regularization, NTK, the information bottleneck, and more.
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·4 min
AI + Automated Testing: Building an Engine-Agnostic Quality System with Skill + CLI
An in-depth analysis of the AI-driven software testing paradigm: with Skill and CLI as the core hub, supporting both platformized management and digital employees, helping testing teams transform from script writers into capability builders.
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·4 min
Home Assistant: The Local-First Open Source Smart Home Platform That Puts Privacy and Freedom First
Home Assistant is the most mature open source smart home hub, prioritizing local control and privacy, supporting thousands of devices across ecosystems with 88,000+ GitHub stars.
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·7 min
Breaking Down the Core Skills of an AI Application Engineer: From Beginner to Industrial-Grade Deployment
Knowing how to call an API doesn't make you an AI engineer. This article breaks down the complete skill structure of an AI application engineer, covering Python fundamentals, LLM fine-tuning, Agent development, and enterprise projects.
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·5 min
The Five Unsolved Challenges of Production MLOps: A Deep Dive into GPU Scheduling, Fault-Tolerant Training, and Model Observability
A deep dive into the five genuinely tough challenges of production MLOps: fault-tolerant training on Spot instances, cross-team GPU scheduling, data reproducibility, model observability, and inference cost optimization.
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·3 min
Multiple AI Agents Sharing a Codebase: Parallel Collaboration Conflicts and Practical Solutions
When multiple AI coding agents work on the same codebase simultaneously, how do you avoid interface conflicts and coordination chaos? A deep dive into Git worktree isolation, contract-first design, and intent declaration.
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