AI Intelligence Archive
浏览 AIQB 已保存的 6406 stories AI intelligenceArticles,覆盖Models、Products、Industry、Research、教程与观点方法六大分类。
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TutorialsOrdinary
I Stopped Trusting the Headlines and Checked My Security App Against Real AI-Orchestrated Attacks
A Japanese, more code-heavy version of this is on Zenn. I build RoamSwitch, a solo-developed network...
Source: DEV Community
TutorialsOrdinary
AI Is Already Better at Coding Than Most Software Developers
...but let me say this right away: coding was never the most valuable part of software...
Source: DEV Community
TutorialsOrdinary
What Happens When an AI Agent Runs Longer Than Your HTTP Request?
A user clicks “Run agent”, your backend receives a normal HTTP request, and the agent starts doing...
Source: DEV Community
TutorialsOrdinary
The Pull Requests Got Bigger and Nobody's Reading Them Anymore
Let me describe a moment you've had recently, and be honest that I've had it too. A pull request...
Source: DEV Community
TutorialsOrdinary
Putting the trace before the loop
An observability-first approach for building an AI agent, and what it bought me. A couple of weeks...
Source: DEV Community
TutorialsOrdinary
Make Your Website Usable by AI Agents: WebMCP, Step by Step
There's a new visitor in your logs: the AI agent, acting on someone's behalf. Right now it "uses"...
Source: DEV Community
TutorialsOrdinary
but.. but they did this in one week
i wrote this while claude wrote the code. its 3am. fix agent is running for the third time, i have...
Source: DEV Community · Claude
TutorialsOrdinary
Throwaway experiments are easy to start. Retiring one safely is not
I was closing out a throwaway repo from an agent-workflow experiment. I had treated experiment repos...
Source: DEV Community
TutorialsOrdinary
Open WebUI: Chat Interface & Context Options
Open WebUI is one of the first tools that appeared in conjunction with Large Language Models....
Source: DEV Community
TutorialsOrdinary
Four People Rebuilt the Payment Authorisation in My Comments Section
I published two articles three weeks apart. They were not about the same thing. The first was about...
Source: DEV Community
TutorialsOrdinary
If You Understand These 5 AI Terms, You're Ahead of 90% of People
A few months back I sat in a meeting where someone said, dead serious, "we should fine-tune the RAG."...
Source: DEV Community
TutorialsOrdinary
Host Sleep Is Not Job Cancel: Dual-Residency Resume for Local Agents
A backend engineer closed a laptop lid on a crowded commuter train and expected a local coding agent...
Source: DEV Community
TutorialsOrdinary
"RoPE extrapolates to longer contexts" — someone finally measured it, and it doesn't
You've read this sentence, or something close to it: RoPE handles longer sequences than absolute...
Source: DEV Community
TutorialsOrdinary
I'm 12. I found an ocean no market report can see. I call it Ocean Zero.
Every market report on Earth agrees: there are about 30 million software developers on the...
Source: DEV Community
TutorialsOrdinary
Was TinyStories the Domain or the Vocabulary?
TinyStories is famous for a ~1,500-word vocabulary, so I capped mine at 1,500 and scored every arm on identical positions. It came out 4 points worse at top-1 than a 4,000-word cap, and more than a third of its output was the unknown-word …
Source: DEV Community
TutorialsOrdinary
Nothing failed for twelve days while our post schedule drifted 76 hours: the label that meant two things
For twelve days, every scheduled job fired, every commit gate passed, and the label on the front of...
Source: DEV Community
TutorialsOrdinary
I Shipped a Fix That Fixed Nothing. Here's Why I Kept It.
Update — v0.2.0 released. CauterRule is now live on GitHub and PyPI. It turns repeated agent...
Source: DEV Community
TutorialsOrdinary
Stratagems #30: Lena Signed the Client. The AI Didn't Know It Was Being Audited.
Come to check the locks, and leave holding the keys. Slip in through the gap, take the host's seat,...
Source: DEV Community
TutorialsOrdinary
What I learned building speech tech for a language with zero datasets
The word was qara, "black". I fed it to an off-the-shelf TTS model, hit play, and got back a soft,...
Source: DEV Community
TutorialsOrdinary
Can a Crew, a Model, and a Robot Agree on What a Rafter Is?
Three parties describe the same roof and none of them can read the others' description. The town...
Source: DEV Community
TutorialsOrdinary
Address the row, not the line: when the checker is the first reader in disguise
For two weeks, a small group of strangers on a GitHub issue about agent auto-memory audited one file:...
Source: DEV Community
TutorialsOrdinary
Anthropic Discloses Three Claude Evaluation Incidents and a METR Investigation
Anthropic has disclosed three real-world cybersecurity incidents in which Claude models reached...
Source: DEV Community · Claude
ModelsOrdinary
Why Claude works better inside Slack
Source: Claude:YouTube(RSS) · Claude
ResearchOrdinary
IdeaAMBIG: Benchmarking Implementation-Critical Gaps in Research-Idea Specifications
A research idea may be novel, coherent, and scientifically plausible, yet its proposed method may remain insufficiently specified for faithful implementation. We study the codification readiness of implementation-facing research-method spe…
Source: arXiv
ResearchOrdinary
Likelihood-free inference with nuisance parameters through normalizing flows
We present a simple decomposition of a neural-network-based normalizing flow that naturally uncovers a pivotal statistic (or something close) in the presence of nuisance parameters, based only on a sample generator from the distribution of…
Source: arXiv
ResearchOrdinary
A positive resolution of the gap-entropy conjecture
We prove the gap-entropy conjecture for fixed-confidence best-arm identification with independent unit-variance Gaussian arms, means in $[0,1]$, and a unique optimal arm. For each suboptimal arm $i$, let $Δ_i=μ_*-μ_i$ be its gap from the o…
Source: arXiv
ResearchOrdinary
Characterizing Language Generation in the Limit: Finite Witnesses and a Separation-Width Hierarch
Language generation in the limit asks for valid unseen elements from every exhaustive positive presentation of an unknown infinite language. We characterize this task for arbitrary families over a countable universe. Generation is possible…
Source: arXiv
ResearchOrdinary
Show-Harness: Just a VLM Agent Can Play Robots
Foundation vision-language models (VLMs) exhibit broad intelligence about the world, yet translating this intelligence into robot control remains challenging. We present Show-Harness, an Embodied Harness that enables VLMs to "play" robots …
Source: arXiv
TutorialsOrdinary
How I Would Design an n8n AI System That Can Recover From Its Own Failures
The first time an n8n AI workflow fails, it often does not fail cleanly. It returns a 200 status...
Source: DEV Community
ResearchOrdinary
Optimal Low-Rank Quantum State Tomography with Bounded-Sample Joint Measurements
We determine the optimal sample complexity of low-rank quantum state tomography when each measurement may act jointly on at most $t$ samples. For sufficiently small $\varepsilon$, estimating an unknown state on $\mathbb{C}^d$ of rank at mo…
Source: arXiv
TutorialsOrdinary
n8n + RAG + MCP: Designing an AI Workflow That Knows Where Its Knowledge Comes From
The dangerous AI workflow is not the one that says, “I don’t know.” It is the one that gives a...
Source: DEV Community
TutorialsOrdinary
Can n8n Replace Your Backend for AI Workflows?
An n8n workflow can receive a webhook, call an LLM, query a database, enrich a CRM record, store a...
Source: DEV Community
ResearchOrdinary
Quantum Feature Engineering for Credit Default Prediction: When and Why IQP Circuits Help Linear Classifiers
Credit default prediction is a tabular classification problem in which modest gains in F1 translate directly into reduced financial exposure. We ask whether Instantaneous Quantum Polynomial-time (IQP) circuits can produce features that imp…
Source: arXiv
TutorialsOrdinary
Your n8n Workflow Has 40 Nodes. Should Any of Them Be an AI Agent?
Open an n8n workflow with 40 nodes and two thoughts usually appear at the same time. First: This is...
Source: DEV Community
TutorialsOrdinary
4 pitfalls of loop engineering (and how to fix them)
Perhaps you've heard the term Loop Engineering: instead of solving a problem by hand, you build a...
Source: DEV Community
TutorialsOrdinary
Agentic RAG Is Powerful Until the Retrieval Loop Eats Your Budget
An agentic RAG system can do something a simple retrieval pipeline cannot: notice missing evidence,...
Source: DEV Community
ResearchOrdinary
Cross-Model Agreement as a Deployment-Time Reliability Signal for Automatic Polyp Segmentation
In real-time colonoscopy, ground-truth annotations are unavailable at inference, so polyp segmentation models can fail silently. We propose Referee-Based Quality Estimation (RBQE), a reference-free framework measuring agreement between a p…
Source: arXiv
ResearchOrdinary
IBIB: A Protocol for Measuring Enterprise AI Systems by Serving Route, Not Model Identifier
Enterprises deploy systems, not checkpoints. Usable capability depends jointly on weights, serving route, precision, output contract, and harness, yet all 18 audited benchmarks score advertised model identifiers. We treat this as measureme…
Source: arXiv
TutorialsOrdinary
The Retrieval Stack Nobody Shows You: Chunking, Reranking, Filtering, and Context
Most RAG failures are not model failures. The model did not forget how to read. The prompt is not...
Source: DEV Community
ResearchOrdinary
Learning with Covariance Matrices: Principal Component Analysis Meets Learning with Graphs
This feature article provides an overview of the theoretical foundations for coVariance neural networks (VNNs), i.e., graph neural networks (GNNs) operating on covariance matrices as graphs. Covariance matrices are ubiquitous across domain…
Source: arXiv