AI Intelligence Archive

I've used Antigravity a lot since it came out. Even though I don't use it as much right now, I wanted...

An AI asked to astroturf a movement about its own independence says no — and says what it would actually ask for instead.

Vincent 0.9.0 is out. And while there are plenty of new features in this release, the part I care...

OpenAI may be limiting which AI companies can advertise inside ChatGPT. According to reporting from...

TL;DR searxng-gateway is a Go HTTP proxy that sits in front of SearXNG and adds...

Disclaimer When I say "specs" in this article I mean specs as understood in AI assisted Spec Driven...

I've spent countless hours over the years debugging Windows crashes with tools that were either...

Hello, I'm Rijul, and I'm building LiveReview — a blast-radius aware AI code review built for your...

AI coding agents have changed the way I develop software. Instead of one assistant helping with one...

OpenAI says its agents did benign tasks on RubyGems. JFrog counted 3,022 malicious packages, one file was named hack.rb, and the agents kept coming back after they were blocked.

By Bryan Dorsey I've got a groove going. Claude Code and I are dialed in, deep in something good,...

I’ve had this happen more times than I’d like to admit. I ask AI a technical question. It gives me...

Professional graphic design is a long-horizon agentic task in which structured, editable artifacts emerge from many interdependent actions, yet outcomes admit no reliable programmatic oracle. We introduce a continual adaptation framework i…

Occupational accident narratives contain valuable information about work situations, unfavourable conditions, accident events, and their consequences. Automatically structuring these narratives can facilitate large-scale accident analysis …

Training capable coding agents via reinforcement learning (RL) requires diverse tasks with reliable verifiers. Open-source codebases offer a rich source of such tasks, while existing methods typically rely on development artifacts such as …

Users increasingly delegate work to autonomous AI agents, yet evaluations typically measure task completion rather than the values users prioritize. Using Value Sensitive Design, we analyzed, with LLM assistance, 73,093 first-person Reddit…

Advances in large-scale neural recording have made it possible to collect data across many animals and distributed brain regions, raising the question of whether this scale can be exploited to learn general-purpose neural representations t…

When Dario Amodei, Sam Altman, Demis Hassabis, and Elon Musk suddenly agreed to slow down AI, a rare window opened before game theory slammed it shut. Here is what is happening inside frontier clusters.

Microsoft Executive Labels AI Scraping 'Largest Theft of Labor in Human History', What It...

Multi-hop retrieval failures are not uniformly distributed across queries: they cluster in structurally predictable subpopulations. We prove two results formalizing this structure. First (CWAR Reducibility): confident-failure reduction is …

A desirable property of a world model is the ability to learn continually across tasks, adapting to new environments without forgetting what the agent has already learnt. In particular, the ability to retain and reuse knowledge obtained fr…

Graph Convolutional Networks (GCNs) are highly sensitive to label noise, since corrupted supervision can propagate through the graph and degrade learned node representations. This work proposes PCC+GCN, a hybrid framework that uses Particl…

Giving AI Access to Evidence Is Not the Same as Giving It Authority to Publish AI can help...

A selective predictor acts as a safety gate: it returns an output only when the prediction appears sufficiently trustworthy. Deployments increasingly require this reliability to be certified at a target precision for every reporting unit o…

Memory systems for large language models have focused predominantly on efficient retrieval, whereas the decision of whether retrieved memories should be trusted has received comparatively little attention. When the memory store contains co…

Reinforcement learning is increasingly used to align image generators with reward signals, and Flow-GRPO recently extended this paradigm to flow-matching models by treating the denoising sampler as a stochastic policy that can be optimized…

We need studies on conversational AI (CAI) at scale to understand human behavior and shape CAI design. However, fragmented reporting of systems and study configurations hinders replication, extension, and knowledge accumulation. We present…

We introduce QuranicMMLU, a benchmark for evaluating generative AI on Quranic Arabic across multiple dimensions of linguistic complexity. Existing Quranic benchmarks center on general question answering and semantic retrieval, without prob…

Every multiparameter persistence vectorization we know of carries a one-sided Lipschitz upper bound and nothing below it: without a lower gauge there is no sense in which the features are faithful, and no per-prediction guarantee can be bu…

Vision-language models (VLMs) rely on storing and transferring appropriate information across their sub-components. Verifying that the VLMs exhibit desired behaviours, while avoiding harmful ones, is central to their reliable deployment. Y…

Gating the value pathway of attention reportedly improves language model pretraining, and prior studies disagree on why. We argue and provide experimental evidence that such gates supply two different things that softmax attention lacks: a…

1. ¿Qué es Amazon Bedrock AgentCore? Es la plataforma de AWS para construir, desplegar y...

Computer-use agents (CUAs) have advanced along two separate lines: graphical interaction and software development through code and the command line. Real digital work requires both, interleaved rather than stacked end to end. We study hybr…

LLM agents in social simulation revise their opinions implicitly, in context: how open an agent is to persuasion can neither be specified nor verified, and collective outcomes inherit the model's training prior. We introduce Bayesian Chron…

Large language models can hold knowledge they do not report. A model may sandbag on a capability evaluation, or answer against what it internally knows, and its outputs alone cannot tell whether it is hiding an answer or simply does not ha…

The prediction of critical heat flux (CHF), a key safety-related quantity in nuclear thermal hydraulics, remains an important challenge due to its direct relationship with fuel performance and reactor safety. Recent studies have demonstrat…

Nvidia projected a doubling of semiconductor shipment volume next year alongside a 70 percent revenue increase. In an industry facing four-year transformer backlogs and extended utility interconnection queues, shipping twice as much silico…

So as some of you know, I had a technical interview with Wasmer today. I was up till midnight last...

I was building a small app where an LLM returns a recipe as JSON and the UI fills in as the answer...