AI Intelligence Archive
浏览 AIQB 已保存的 6310 stories AI intelligenceArticles,覆盖Models、Products、Industry、Research、教程与观点方法六大分类。
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ModelsOrdinary
SpaceXSI 亮相 Vercel Ship
Vercel Ship 🤝 SpaceXSI
Source: X:Matt Palmer(SpaceXSI,Grok Bot) (@mattyp) · Grok
TutorialsOrdinary
Scope-Creep Guard: A Local Gemma AI That Tells Clients "That's Out of Scope" (So You Don't Have To) published: true
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle ...
Source: DEV Community
TutorialsOrdinary
Eight Minutes to Live. Was It Cursor, or Was It the Spec?
A tip calculator, a stopwatch, and a lot of pesos. TL;DR: I built a USD/MXN tip calculator with...
Source: DEV Community · Cursor
ModelsOrdinary
Gemini 4 Argon 登 ARC Prize 排行榜
@Google - 排行榜:https://arcprize.org/leaderboard - 复现公开结果:https://github.com/arcprize/arc-agi-benchmarking - 测试政策:https://arcprize.org/policy - Gemini 4 Argon 完整结果:https://arcprize.org/results/google-gemini-4-argon
Source: X:ARC Prize (@arcprize) · Gemini
ProductsOrdinary
NVIDIA Nemotron 3.5 Super 上线 fal
立即体验。 文本:https://fal.ai/models/nvidia/nemotron-3-5-super/text 视觉:https://fal.ai/models/nvidia/nemotron-3-5-super/vision 视频:https://fal.ai/models/nvidia/nemotron-3-5-super/video
Source: X:fal (@fal) · NVIDIA
TutorialsOrdinary
Architecting Autonomous Lakehouse Agents: Governed Iceberg Analytics with Gemini 2.5 Flash and BigLake
The decoupling of compute from storage has positioned Apache Iceberg as the de facto open table...
Source: DEV Community · Gemini
ProductsOrdinary
fal 上线 Krea Realtime Models
@krea_ai Realtime:https://fal.ai/models/krea/v3/realtime
Source: X:fal (@fal)
ProductsOrdinary
NVIDIA Nemotron-3.5 免费试用
试用:https://openrouter.ai/nvidia/nemotron-3.5-super-vl:free
Source: X:OpenRouter (@OpenRouter) · NVIDIA
TutorialsOrdinary
OpenAI Conference Room Bug, Anthropic's Scion vs. Meta's Mononoke, and Cloudflare's Yandex Bot Trace
Inside the $23.99 ESP32 audio recorder found in an OpenAI executive conference room, why Anthropic replaced Git with Scion at 30,000 merges a day, and Cloudflare's JA4 bo
Source: DEV Community · OpenAI / Claude
TutorialsOrdinary
AI-Generated Tests Can Agree With the Bug
When an AI agent writes both the implementation and its tests, a green build may only prove that the same wrong assumption was encoded twice.
Source: DEV Community
TutorialsOrdinary
Local image generation with llamadart for the Llama Village storybook
Beyond chat with llamadart · Part 4 Dash missed it. Pip’s scarf is by the pond, and all he has is...
Source: DEV Community · Llama
TutorialsOrdinary
Introducing B-TAP: Because Your AI Infrastructure Hasn't Attributed Its Fair Share
Context isn't free. Retrieval isn't free. Observability isn't free. And an international standards...
Source: DEV Community
ProductsOrdinary
Luma 推出 Shot Coverage 功能
在 Luma 中试试 Shot Coverage - https://app.lumalabs.ai/solutions/shot-coverage?utm_source=x&utm_medium=p-social&utm_campaign=q4-social&utm_content=shotcoverage&utm_aud=plg
Source: X:Luma AI (@LumaLabsAI)
TutorialsOrdinary
RevCheck, compare the cars you want before you buy your next daily driver
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle ...
Source: DEV Community
TutorialsOrdinary
It caught "partner" "pareja" in an IRS rule and missed "return" "devolución": an offline MT checker for translators
An offline checker that ranks machine-translated segments by the risk of a major meaning error: a $1.22 Tinker LoRA, Gemma 4 on DigitalOcean, Sentry tracing.
Source: DEV Community
PerspectivesOrdinary
https://x.com/SaitoWu/status/2110701932390256871
Source: X:Saito 硬地骇客 (@SaitoWu)
TutorialsOrdinary
Your AI Agent Just Got a Passport: Agent Identity on Google Cloud and the Redeploy Trap Nobody Talks About
Why your agents need their own identity Most teams run every AI agent under one shared...
Source: DEV Community
TutorialsOrdinary
State of AI Instruction Quality: A Third of Repos Shout
IMPORTANT. CRITICAL. You MUST. NEVER. A third of the repos in the Q3 report, 3,319 of the 9,784 with...
Source: DEV Community
TutorialsOrdinary
ScopeGuard: an open-weight model that tells freelancers when "quick one" means "paid one"
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle ...
Source: DEV Community
TutorialsOrdinary
I built a lie detector for AI coding agents. Then I read the rules.
When an AI agent commits a change to code, it makes a claim about what it changed: "fixed typos" or...
Source: DEV Community
TutorialsOrdinary
I Vibe-Coded My Way Out of Angular Upgrades
Do you also hate upgrading Angular versions? Because I do. I maintain a few open-source projects, and...
Source: DEV Community
TutorialsOrdinary
Gemma 4's MTP Drafter, Explained: Speculative Decoding and a 4-Bit Drafter at 60% of the Size
What speculative decoding is, how Gemma 4's multi-token prediction drafter rides on the main model, why you would add one, and an exact Q4_0 repack of Google's QAT drafters on Hugging Face that cuts the file to 60% of the size and the memo…
Source: DEV Community · Hugging Face
TutorialsOrdinary
AI Engineering Is Easy. So How Do We Change How We Work?
In Part 1, I wrote about the uncomfortable part of AI-assisted engineering: the tools are becoming...
Source: DEV Community
ModelsOrdinary
https://x.ai/bot/plugin/9717366
https://x.ai/bot/plugin/9717366
Source: X:Lauren Tan(SpaceXSI,Grok Bot 工程负责人) (@poteto) · Grok
PerspectivesOrdinary
Dex Horthy 提及 aiDotEngineer 与 vikhyatk
@aiDotEngineer @vikhyatk 提到了
Source: X:Dex Horthy(HumanLayer)(@dexhorthy)
TutorialsOrdinary
Requests, Promises, Assertions, and Declarations: Rewriting Our AI Agent Workflow as a 1986 'Committed Speech' Machine
Why do 200-line agent prompts, Asimov's Three Laws, and sequential pre-landing checklists all fail the same way? How Fernando Flores's 1986 Committed Speech, Nuel Belnap's 1977 4-Valued Logic, and Tony Hoare's 1978 CSP turned our Makefile …
Source: DEV Community
ResearchOrdinary
Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance
Mobile Manipulation (MoMa) is a cornerstone of autonomous robotic systems, yet real-world fine-tuning remains a formidable challenge because of high-dimensional action spaces and intricate coupling between heterogeneous modules. In this pa…
Source: arXiv
ResearchOrdinary
Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion
Recent advances in robot learning have driven rapid progress in humanoid control, enabling increasingly agile behaviors in the real world. However, humanoid control networks are typically obtained through conventional training procedures, …
Source: arXiv
ResearchOrdinary
Co-Evolving Acting and Forecasting for Language Agents
Training language agents is bottlenecked by the high cost of long-horizon rollouts, yet standard agentic reinforcement learning (RL) learns only from a terminal scalar reward, leaving the supervision in intermediate steps largely unused. P…
Source: arXiv
ResearchOrdinary
Your Transformer Is Secretly Elastic
Scaling up transformers has produced models with broad capabilities, deployed across heterogeneous hardware and fluctuating workloads. Yet, model families offer only a few fixed sizes (e.g., S, B, L), forcing users to commit to a model bas…
Source: arXiv
ResearchOrdinary
Price of Anarchy of First-Price Auctions in Agentic Markets
An agentic market is a decentralized serving-time market where AI agents bid to claim each user prompt. An agent's bid is based on its expected value for the prompt, which is the expectation of the reward for its response minus its inferen…
Source: arXiv
ResearchOrdinary
Continuum Attention
We introduce Continuum Attention (CA), a causal Transformer attention operator that replaces discrete key and value lookup with integration over a continuous, piecewise linear memory curve. Each query induces an exponential relevance densi…
Source: arXiv
ResearchOrdinary
Learnable Hodge-Laplacian Driven Mixture of Experts for Steady-PDE Surrogates on Coarse Unstructured Meshes
Current approaches for steady partial differential equations surrogate models on unstructured meshes apply a single mixing mechanism to the whole solution. This paper proposes an architecture that partitions the solution among vanilla tran…
Source: arXiv
ResearchOrdinary
Player-1: Learning to Play from Synthetic Experience
Computer-use agents have demonstrated strong capabilities in interpreting screens and executing keyboard and mouse actions. However, games, with their visually rich worlds and diverse mechanics, remain challenging and offer a demanding nex…
Source: arXiv
ResearchOrdinary
Latent Compaction with Test-Time Training
Long contexts enlarge key--value (KV) caches, increasing memory use and attention costs during generation. Compressing these caches must preserve information for unseen questions. We introduce **Latent Compaction**, which learns a compact …
Source: arXiv · Qwen
ResearchOrdinary
One Task, Many Interfaces: Simple Cross-Interface Consistency Training Improves LLM Agent Robustness
Post-training binds the competence of an LLM agent to the interface it was trained on. Semantics-preserving perturbations of that interface, such as renaming an action or changing the notation, leave the underlying task unchanged yet make …
Source: arXiv
ResearchOrdinary
Beyond LLM Judge: Mechanical Verification for Agentic Autoformalization
We introduce a novel method for verifying Lean formalizations that goes beyond LLM-judged faithfulness. Unlike most verification methods, which rely on LLMs or trained models, our method combines LLM-based semantic review with mechanical n…
Source: arXiv
ResearchOrdinary
Recovering Reliable Supervision via Critique-Guided On-Policy Distillation
On-policy distillation (OPD) trains a student model on its own rollouts with token-level supervision from a teacher, assuming that the teacher can reach a correct answer from any prefix the student writes. We call this property the recover…
Source: arXiv · Qwen
ResearchOrdinary
Manacá-1B-Instruct-2: Reproducible Safety Alignment for a Native Brazilian-Portuguese LLM. Negative DPO Results, a Controlled Composition Scan, and a Silent Failure Mode of the LL…
Brazilian Portuguese remains underserved by open-source language models, and the few that are safety-aligned rarely document what did not work or validate comparisons with statistical significance. We present Manacá-1B-Instruct-2, the seco…
Source: arXiv
ModelsOrdinary
https://x.ai/news/grok-voice-3#used-by-millions-of-customers-at-tesla--spacex
https://x.ai/news/grok-voice-3#used-by-millions-of-customers-at-tesla--spacex
Source: X:Lauren Tan(SpaceXSI,Grok Bot 工程负责人) (@poteto) · Grok