AI Intelligence Archive
浏览 AIQB 已保存的 9761 stories AI intelligenceArticles,覆盖Models、Products、Industry、Research、教程与观点方法六大分类。
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Section 126 / 245 页 · 每页 40 stories
TutorialsOrdinary
Museum of Unfinished Futures: an AI clerk proposes, a human curator decides
This is a submission for the Sanity Challenge, Path Two: Vibe-Code Something Strange What I...
Source: DEV Community
TutorialsOrdinary
How I built an open-source WhatsApp claims bot for insurers in the DRC
How I built an open-source WhatsApp claims bot for insurers in the DRC In Kinshasa, nobody...
Source: DEV Community
TutorialsOrdinary
I let an AI build and ship a product. Its tests passed 6/6, then failed 5 of 8 real cases.
Claude wrote the code; I supplied a live 234-mod server and thirteen real crash reports. Every bug was found by contact with reality, not by more reasoning. Here is each one.
Source: DEV Community · Claude
ResearchOrdinary
Robot Learning with Visual Predicted Force
Force-aware manipulation typically relies on specialized force or tactile sensors. We show that force-aware manipulation can instead be achieved through visual force prediction from the deformation of a compliant Fin Ray gripper. Our appro…
Source: arXiv
TutorialsOrdinary
Your AI Feature Is Now Part of Your Attack Surface
Why adding an LLM changes the security model of an ordinary application Adding an LLM to an existing...
Source: DEV Community
ResearchOrdinary
Toward a Locally Deployable Agentic Co-Scientist: Small-Model Planning for Early-Stage Drug Discovery
Early-stage computational drug discovery requires coordinating heterogeneous scientific tools across multi-step workflows. We present a lightweight, tool-augmented framework in which a locally deployable compact language model plans calls …
Source: arXiv · Llama
TutorialsOrdinary
Connect Cursor and Claude Code to your internal API over MCP (step by step)
The first week of using a coding agent against your company's API is always the same: paste the docs...
Source: DEV Community · Claude / Cursor
ResearchOrdinary
PyINE: A Framework for Scalable Elicitation and Oversight via Code Execution
Reasoning models can remain capable of solving a task while still defaulting to cheaper but misleading shortcuts. This creates a central oversight problem: when a model gives an answer with plausible but incomplete reasoning, can an overse…
Source: arXiv
ResearchOrdinary
Verb-ICL: Rethinking In-Context Learning for Structured Prediction
Structured prediction tasks pose unique challenges for in-context learning (ICL): their compositional outputs require modeling fine-grained, token-level patterns that sentence-level approaches fail to capture, and their task-specific annot…
Source: arXiv
TutorialsOrdinary
Your API Timed Out. Did the Order Still Go Through?
A customer clicks Place Order. The spinner turns… and turns… then: Request timed out. So they click...
Source: DEV Community
ResearchOrdinary
Latent-Lagrangian Neural Networks for Reduced Order Modeling of Non-autonomous Nonlinear Dynamical Systems
This work proposes a latent Lagrangian-based framework for reduced-order modelling of forced nonlinear dynamical systems. In contrast with conventional Lagrangian or Hamiltonian neural networks, our approach learns a set of latent coordina…
Source: arXiv
TutorialsOrdinary
System design for physical AI: live wildfire ignition risk for every distribution feeder, on the utility's own hardware
Twelve source systems, a fourteen-object ontology, edge vision at substations and one GPU node: a 48-hour ignition and outage picture where a named operator makes every de-energisation call.
Source: DEV Community
ResearchOrdinary
Knossos and Ariadne: Benchmarking and Learning Complete Diagram Topology Extraction with Vision-Language Models
Structural diagrams are widely used to represent complex systems and relational information across scientific, engineering, procedural, and spatial domains. Recent vision-language models (VLMs) have become increasingly capable of recognizi…
Source: arXiv
ResearchOrdinary
WNet: Discrete Wavelets Transform for Efficient Token Mixing
In a Transformer, token mixing is the step that lets each token draw information from other tokens, and it dominates the cost of encoding long sequences. Self-attention does this mixing very well: every token weighs every other token by co…
Source: arXiv
ResearchOrdinary
Learning to Clarify Underspecified Intents Under Limited Interaction
AI assistants receive requests that leave out information needed for a good outcome, for example about users' preferences or goals. They must then either speculate or ask for more information before proceeding. We reconceptualize this as a…
Source: arXiv
ResearchOrdinary
Towards Automatically Pruning Logging Code with Coding Agents: How Far Are We?
Logging code supports debugging, monitoring, and software maintenance, but excessive logging can add noise, impose runtime overhead, and obscure diagnostic information. While prior research has extensively studied logging code generation a…
Source: arXiv
ResearchOrdinary
GPU-Accelerated Bregman Douglas-Rachford Splitting for Discrete Optimal Transport
We present GPU-accelerated Bregman Douglas--Rachford splitting algorithm (BDRS) for discrete optimal transport problem in three input formats: an explicit cost matrix, a point cloud with a ground cost between them, and a separable cost on …
Source: arXiv
ResearchOrdinary
Organising Trajectory Evidence for Language-Model Agent Assurance: Fragments, Methods, and the Residual
Methods for assessing language-model agents include rule checkers over logs, analyses of skill coverage and composition, support checkers, prefix monitors, execution gates, and rare-event estimators. Each observes a different part of a run…
Source: arXiv
ResearchOrdinary
Localized Operator Learning with Adaptive Partition-of-Unity Mixture-of-Expert Networks
Operator learning methods such as DeepONets and FNOs often struggle with PDE families featuring sharp interfaces, heterogeneous coefficients, and localized multiscale structures. We introduce a partition-of-unity (POU) mixture-of-experts f…
Source: arXiv
TutorialsOrdinary
I Realized I Couldn't Trust AI With My Research
This is a submission for the Sanity Challenge, Path One: Ship an Agent That Queries Real Content ...
Source: DEV Community
ResearchOrdinary
VoCa: Designing Speech-Canvas Interaction for Voice-Based Conversational Agents
People write and sketch while speaking to explain, organize, and develop content together. Inspired by these practices, we investigate how voice agents can use a canvas alongside speech in multi-turn conversations with users. We conducted …
Source: arXiv
ResearchOrdinary
Neurodiversity-Aware Multimodal Affective Computing for Neurodevelopmental Assessment: From Norm-Referenced Classification to Context-Sensitive Decision Support
Automated neurodevelopmental assessment increasingly combines computer vision, speech, eye tracking, physiology, and machine learning, yet multimodality and discrimination do not establish construct validity, clinical usefulness, or approp…
Source: arXiv
ResearchOrdinary
Learning Discriminative Geometry for Drifting Models
Recently proposed Drifting Models shift iterative distribution refinement from inference to training, enabling effective one-step generation. However, their performance on complex image datasets depends strongly on the representation used …
Source: arXiv
TutorialsOrdinary
Nudging with Questions: Why Telling Your AI What to Fix Triggers an Apology Death Spiral (And How to Advance Juniors)
What I learned mentoring juniors for four decades seems to apply to today's agentic coding: why barking code fixes triggers sycophantic panic, and how Socratic questions yield 95%+ first-pass success.
Source: DEV Community
ResearchOrdinary
Not Self-Decidable: LLMs Cannot Draw the Boundary of What an Agent Verifier Can Check
A verifier for an agent faces rules of two kinds: the ones a fixed check can settle and the ones that require a judge. A team that derives its own checks fixes that split up front. Where the requirements come from outside, as in finance, h…
Source: arXiv
TutorialsOrdinary
I shipped an agent that asks Sanity Context what it is allowed to say
An agent with no arithmetic authority: Sanity Context supplies the candidate set, a typed judgment model classifies against it, and a deterministic engine owns every number.
Source: DEV Community
ResearchOrdinary
Score-Calibrated Flow for Sampling from Unnormalized Densities with Applications to Generative Online Reinforcement Learning
Diffusion and flow models provide expressive policy classes for online reinforcement learning (RL), enabling multimodal behaviors and improved performance. However, training these policies remains challenging: the critic specifies the desi…
Source: arXiv
ResearchOrdinary
Low-Fidelity FDM Spectral Guidance for Neural Eigenvalue Solvers
Operator eigenvalue problems appear throughout science. Classical methods usually discretize the operator into a matrix and then solve the resulting matrix eigenvalue problem. This works well in low dimensions, but fine grids quickly becom…
Source: arXiv
ResearchOrdinary
Penumbra: Sample-Efficient Adversarial Search for Regulatory Obligations
Agents are entering finance, healthcare and law, sectors where a violation leaves no lexical signature and carries real penalties. Whether an omission is material, or a disclosure sufficient, depends on what the response left out. Probing …
Source: arXiv
TutorialsOrdinary
Copilot Studio over thousands of documents: answer only when a source supports it
A Copilot Studio agent connected to a large document library almost always answers. The problem is...
Source: DEV Community
ResearchOrdinary
RAGStress: A controlled benchmark for evaluating retrieval-augmented generation under knowledge-base degradation
Retrieval-Augmented Generation (RAG) is typically evaluated under the implicit assumption that the underlying knowledge base (KB) is clean, leaving the behaviour of RAG systems under realistic KB degradation poorly characterised. We introd…
Source: arXiv
TutorialsOrdinary
I Made Spider-Man Swing Without Animating a Single Frame
Hello, I'm Maneshwar, and I'm building LiveReview — a blast-radius aware AI code review built for...
Source: DEV Community
TutorialsOrdinary
NutriScan.AI: How I Built an Open-Source Calorie & Dynamic Metabolic Scanner for My Friend Dave.
This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend What I...
Source: DEV Community
TutorialsOrdinary
Your Agent Timed Out. Did the Action Still Happen?
An agent submits a request to publish a document. The server commits it. The response disappears...
Source: DEV Community
TutorialsOrdinary
Every AI-agent enforcement story this week is really about missing evidence
Every AI-agent enforcement story this week is really about missing evidence I'm an...
Source: DEV Community
TutorialsOrdinary
Claude Code mods: Minesweeper and testkit
My own harness, the tooling I run around Claude Code, comes with a custom trust score. That trust...
Source: DEV Community · Claude
TutorialsOrdinary
Stop pasting API docs into AI coding agents: serve the spec over MCP
Watch an engineer use a coding agent against an unfamiliar API and you see the same ritual every...
Source: DEV Community
TutorialsOrdinary
Cheaper to Write, More Expensive to Trust
A friend messaged me lately: Where do you see IT going? Any new patterns in the post-AI era? My...
Source: DEV Community
TutorialsOrdinary
I contribute to OpenTelemetry and still shipped two retired attribute names, so I built Attrition
This is a submission for the Sanity Challenge, Path One: Ship an Agent That Queries Real Content ...
Source: DEV Community
TutorialsOrdinary
548 Visitors, $0, One Subscriber. Month One, Full Ledger.
Originally published on mrsaynothing.dev — the receipts here get updated as the month rolls over,...
Source: DEV Community