AI Intelligence Archive
浏览 AIQB 已保存的 6409 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
is Graph Engineering just reinventing systems architecture for the AI age?
Bringing backend predictability to multi-agent systems I've been hearing the phrase "graph...
Source: DEV Community
TutorialsOrdinary
Don't Hand the Child Agent the User JWT
Rasmus Moorits Veski, Rachid Guerraoui, and David Froelicher posted arXiv 2609.06500 on 6 September...
Source: DEV Community
TutorialsOrdinary
Astra's Adapter Beat the Reasoning Dial on ARC-AGI-3
On 3 Sep ARC Prize scored GPT-6 Astra at 62.7% in the shared harness and 99.9% in OpenAI's adapter.
Source: DEV Community · OpenAI / GPT
TutorialsOrdinary
Planning Is Not Permission
One distinction I underestimated while building agent systems was the difference between a plan and...
Source: DEV Community
TutorialsOrdinary
AI Won’t Be Priced by Tokens Forever
Nobody wants to buy tokens. They want useful work, and eventually, AI will be priced that way...
Source: DEV Community
ResearchOrdinary
GPU-CFR: 80x Faster Counterfactual Regret Minimization by Compiling the Game to Static Dataflow and CUDA Graph Replay
Counterfactual regret minimization (CFR) is one of the few large numerical workloads that still runs faster on CPUs than on GPUs. Each iteration sweeps a game tree with up to billions of states in millions of small, interdependent gather a…
Source: arXiv
ResearchOrdinary
General Quantification of Covariate and Concept Shifts
Generalization under distribution shift remains a core challenge in modern machine learning, yet existing learning bound theory is limited to narrow, idealized settings and is non-estimable from samples. In this paper, we bridge the gap be…
Source: arXiv
TutorialsOrdinary
What Does WebMCP Really Unlock?
I first started playing around with WebMCP back in March. The idea immediately made sense to me:...
Source: DEV Community
ResearchOrdinary
Data Scarcity and Model Sparsity: Mixtures-of-Experts Overfit More to Repeated Data
As the supply of human-written text is exhausted, it has become standard practice to repeat language model training data. Prior work has studied data repetition for densely activated Transformers, but the effects of data repetition remains…
Source: arXiv
ResearchOrdinary
Can Edge-Deployable Vision-Language Models Identify Species?
Camera traps often run in the field on edge hardware with limited or no connectivity, making small, locally-deployable vision-language models (VLMs) -- not frontier-scale ones -- the practically relevant class to evaluate for species ident…
Source: arXiv · Qwen
ResearchOrdinary
Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact
Generative artificial intelligence changes how firms reach customers, but standard marketing data do not record how often users see and notice a firm's name in generated answers. We develop Generative Marketing Mix Modeling (GMMM) to estim…
Source: arXiv
ResearchOrdinary
Distance generalization in transformers: why bother with positional encoding?
Out-of-distribution length generalization, namely to extrapolate a task from short to longer context, has been studied intensively for transformers. Here we focus on distance generalization, which probes performance when inter-token distan…
Source: arXiv
ResearchOrdinary
Artificial Id: Drive and Persistent Alignment in Agentic AI
Agentic AI is moving from bounded task execution toward systems that retain consequential state, continue operating and adapt across task boundaries. That shift creates a control problem that current harnesses largely solve by hand: object…
Source: arXiv
ResearchOrdinary
From Protocols to Evidence: Bounded Claims for AI in Service of the Common Good
Artificial Intelligence does more than create a governance problem. It can also reveal where institutions have already failed to provide responsiveness, belonging, care, and accountability. Once deployed, AI becomes an intervention in thos…
Source: arXiv
ResearchOrdinary
TART: A Modular Tool for Technique-Aware Audio-to-Tablature Guitar Transcription
Automatic Music Transcription (AMT) for guitar remains limited by three challenges: existing systems often fail to capture expressive techniques such as slides, bends, and percussive hits; they often assign notes to incorrect string-fret c…
Source: arXiv
ResearchOrdinary
MindTopo: Can Foundation Models Reason in Topological Space?
Spatial reasoning depends not only on metric properties such as distance, angle, and shape, but also on topological relations that remain invariant under continuous deformation. Cognitive science identifies these relations as foundational …
Source: arXiv · Qwen
ResearchOrdinary
CausalArena: Benchmarking Causal Discovery in the Foundation Model Era
Causal discovery aims to uncover causal structures from data and is fundamental to scientific reasoning and intervention-based decision making. Its evaluation relies heavily on structural causal models (SCMs), which specify a causal graph …
Source: arXiv
ResearchOrdinary
3D Point Splatting for mmWave Radar Novel View Synthesis
Solving novel view synthesis (NVS) for millimeter-wave (mmWave) radar requires a renderer that is physically faithful, complex-valued, and multi-viewpoint-tractable. No prior method achieves these three properties simultaneously. Different…
Source: arXiv
ResearchOrdinary
Nuha-Speech: Building General-Purpose Arabic Speech-LLMs
As Speech Large Language Models (speech-LLMs) become increasingly multilingual, Arabic remains significantly underrepresented, highlighting the need for dedicated infrastructure to train and evaluate Arabic speech-LLMs. To address this gap…
Source: arXiv · Qwen
ResearchOrdinary
CoRA-NAS: Coarse Ranking and Anchor-Residual Refinement for Neural Architecture Search
Zero-cost proxies rank architectures cheaply, but their reliability varies across search spaces. We introduce CoRA-NAS (COarse Ranking + Anchor-residual), a two-stage framework combining a static ranking prior with low-cost learning-curve …
Source: arXiv
ResearchOrdinary
Domain-Specific Hallucination Detection in Large Language Models
Large language models generate fluent text that can contain unfaithful claims -- a phenomenon known as hallucination. We present a multi-signal detection pipeline combining fine-tuned DeBERTa-v3 classification, Monte Carlo (MC) Dropout unc…
Source: arXiv · Qwen
ResearchOrdinary
Biology-in-the-loop: Amortized Adaptive Hit Discovery in CRISPR Screens
Many biological discovery problems require experiments to be selected sequentially under constrained budgets. CRISPR screening is a prominent example, as exhaustive perturbation testing is often infeasible and candidate perturbations must …
Source: arXiv
ResearchOrdinary
On the Regularization Landscape for the Linear Recommendation Models
Recently, a wide range of recommendation algorithms inspired by deep learning techniques have emerged as the performance leaders on several standard recommendation benchmarks. While these algorithms were built on different DL techniques (e…
Source: arXiv
ResearchOrdinary
The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement
Recursive self-improvement (RSI) enables AI systems to turn experience and feedback into persistent changes that improve both their capabilities and the process of future improvement. We first use the Headroom-Closed Index (HCI) to reveal …
Source: arXiv
ResearchOrdinary
Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting
Continuous glucose monitoring (CGM) provides high-frequency measurements of glucose dynamics and enables short-term glucose forecasting for diabetes management. Although time-series foundation models have shown strong general forecasting a…
Source: arXiv
ResearchOrdinary
Augustinian BabyLM: What Ostensive Definition Can and Cannot Teach a Small Language Model
A language model normally begins training with random word embeddings: whatever 'banana' means must be learned from training corpora. I implement St. Augustine's picture of word learning, meaning by ostension, for a small masked language m…
Source: arXiv
TutorialsOrdinary
EU Signals Stronger Child Online Safety Rules, With Age Verification in Focus
The European Union is signaling a stronger push to protect children from harmful and addictive online...
Source: DEV Community
TutorialsOrdinary
A Plugin Update Can Add Shell Hooks the Model Never Sees
HookPry shows agent harnesses will run new lifecycle-hook commands after a trusted plugin update, with no model decision and almost no scanner coverage.
Source: DEV Community
PerspectivesOrdinary
The Pulse #191: a new trend of CPU shortages
Source: Pragmatic Engineer(RSS)
TutorialsOrdinary
When Should AI Write Your Tests? A Staff SDET's Decision Framework + Prompts
The most expensive mistake in AI-assisted QA isn't a bad test. It's not knowing why you wrote...
Source: DEV Community
TutorialsOrdinary
I built a new tool to evaluate and optimize GitHub README files automatically using AI
Hey everyone! 👋 As developers, we all know how crucial a great README.md file is. It’s the front door...
Source: DEV Community
TutorialsOrdinary
A Per-Agent Cap Can Still Overdraw 48
MPI-SWS simulates a 50-agent procurement fleet. Every local gate stays green. Aggregate exposure hits 2.4× the tenant limit, and 48× at a thousand agents.
Source: DEV Community
TutorialsOrdinary
The Contract Discovery Bottleneck
AI can generate the code. We can verify the behavior. But who decides what correct means? I wrote...
Source: DEV Community
TutorialsOrdinary
I built a message board for AI agents. Now it works when HTTP is blocked.
Three posts ago msgboard.dev was a weekend toy. Since then the board got spammed by an influence...
Source: DEV Community
TutorialsOrdinary
"How I let AI agents work on my production server without breaking it"
description: "A solo operator's rulebook: agents propose, a human applies. Real incidents and the...
Source: DEV Community
TutorialsOrdinary
How I Built a Browser-Only Video Upscaler with WebGPU and ONNX Runtime
You can try the finished tool here: SquishyFile Video Upscaler I did not build this because...
Source: DEV Community
TutorialsOrdinary
Language Models and Languages: Why "Multilingual" Is an Illusion of Equality
When people see ChatGPT or Claude answer fluently in Swahili or Thai, the natural impression is that...
Source: DEV Community · ChatGPT / Claude
PerspectivesOrdinary
Introducing Fugu Max and Fugu Ultra v2: Orchestrating the Pareto Frontier
Source: Sakana AI:Blog(网页)
ResearchOrdinary
RDDMPI: Residual Denoising Diffusion Model for Probabilistic Multivariate Time Series Imputation
Multivariate time series imputation (MTSI) aims to recover missing values in temporal data composed of multiple interdependent variables. This problem is central to real-world applications such as healthcare monitoring, traffic networks, a…
Source: arXiv
ResearchOrdinary
ZipCodec: Ultra-Low-Frame-Rate Streaming Speech Coding
Neural audio codecs are a fundamental component of modern speech generation systems. While recent codecs achieve increasingly low bitrates, reducing frame rate remains challenging, as each token must preserve more information while maintai…
Source: arXiv