AI Intelligence Archive

A prompt-injection benchmark, three bugs in my own scorer, and the result I only found after fixing...

Agents burn turns guessing how to test, lint and reset your DB. Ten make targets, two lines in AGENTS.md, and make check as the done check.

Sensorized human demonstrations offer scalable data for mobile manipulation, but embodiment differences complicate policy learning. We present Pixel-UMI, a pipeline for learning environment-aware whole-body policies from human data. We fir…

General-purpose mobile manipulation requires a combination of capable robot hardware, scalable demonstration collection, expressive whole-body control, and effective policy learning. Yet these components are often developed independently, …

Chain-of-Thought (CoT) generation has substantially improved the performance of Large Language Models (LLMs) on complex reasoning tasks, including code generation, data analysis, and exam-style question answering. Despite these advances, p…

GUI web agents require realistic and interactive environments that remain stable during both evaluation and training. Live website evaluation suffers from changing content, access restrictions, and limited coverage of authenticated workflo…

Muon has recently emerged as a promising optimizer for pretraining large language models, offering a speedup over AdamW in minimizing pretraining loss. However, it remains unclear whether Muon's advantage persists after fine-tuning. In thi…

Reinforcement learning with verifiable rewards (RLVR) can enable generalizable improvement for large language model (LLM) reasoning. This paper studies how to incentivize such generalization via reasoning strategies. We study this question…

Group-based reinforcement learning with verifiable rewards (RLVR) learns only from prompts whose sampled completions disagree: all-pass and all-fail groups produce zero relative advantage and burn generation budget without moving the polic…

Communication is important for our well-being, but it can be impaired by disabilities, such as locked-in syndrome (LIS), cerebral palsy (CP), and dysarthria. Non-invasive brain-to-text brain-computer interfaces (BCIs) offer a promising sol…

Vision-Language Models (VLMs) hold promise for zero-shot video task-progress estimation in robot learning, yet existing frameworks frequently suffer from confirmation bias, hallucinating progress in failed executions due to implicit succes…

A model is only half of an AI agent system. The other half is the inference strategy: the reasoning procedure that turns model calls into a response. Today that second half is written by hand, and the experience of building one strategy ne…

Large language models (LLMs) show growing promise for scientific discovery, yet basic questions remain about what enables reliable discovery. How can we trace the scientific discovery capacity of LLMs to their training data? We study this …

Evaluating a generative model on all queries from all available benchmark tasks is prohibitively expensive. As such, models are often evaluated on different subsets of tasks and/or different subsets of queries from a given task. The result…

Increased computing power has transformed computational science and improved predictive capabilities for complex systems, but many phenomena still exceed current simulation capabilities or require rapid evaluations for fast design iteratio…

ufakzeka-kulak is an open Turkish speech-to-text model of 31.6M parameters, a FastConformer encoder with a token-and-duration transducer (TDT) and a CTC head, trained from scratch and released under Apache-2.0. It writes cased, punctuated …

As pretraining scales, medical language models have advanced rapidly in clinical question answering. Their ability to achieve effective physiological control through sustained intervention still lacks systematic quantitative evaluation. Ty…

AI agents are increasingly deployed in settings where they interact and coordinate with other agents, yet honesty is mostly measured in single-turn, single-agent benchmarks that pressure the model to deceive. We study deception that emerge…

In this paper, we study when two parties should pool their data to train a machine learning model. Two agents, Alice and Bob, each hold a sensitive labeled dataset and want to train a classifier from a given hypothesis class $\mathcal{H}$.…

Understanding how neurons respond to visual stimulus is an important question in both deep learning and neuroscience. It has significant implications for enhancing the interpretability of black-box artificial neural networks and for unders…

We show that the causal structure of spacetime can emerge within the memory of a learning agent performing a quantum information task. We train a model-based reinforcement-learning agent to maximize the quantum mutual information between l…

Neural operators provide efficient surrogates for computational fluid dynamics (CFD), but most are designed for static geometries and are not equipped to model unsteady flows induced by continuously moving boundaries. We study dynamic-boun…

How I wrapped llama.cpp in a small, coroutine-first Kotlin API, and the three problems that took the most time: threads, cancellation and broken emoji.

How to understand, monitor, debug, and optimize agentic AI systems using OpenTelemetry and modern AI...

Three Decisions, Three Places Same agent. Same sandbox. Different folder. Different blast...

I started writing this article while reading the OWASP Top 10 for LLM Applications 2026. I wanted to...

The pipeline costs nothing. The audience costs everything. Here's the math the faceless-channel gurus...

Autonomous AI agents and Model Context Protocol (MCP) servers have fundamentally changed software...

Google has opened a preview of its Connected Apps Platform, creating a formal route for developers to...

How much damage can a four-line kernel patch prevent? For CVE-2026-98432, the answer is a remote, unauthenticated use-after-free in the IPv4 TCP handshake, scor

Why dense and sparse retrieval disagree, why fusing ranks beats blending scores, and what a 20-question evaluation set revealed about a B2B sales-intelligence prototype.

Reddit has disclosed a material decline in search referrals during October 2026, saying it lost more...

The permission model behind Sahkarmi: sixteen action categories, six that can never be auto-approved, time-boxed delegated authority, and a browser take-over flow that keeps passwords away from the model.

I am Jake Burwick, a high school student, and I built Vow, an open source programming language under...

AI coding powers OccupySaaS's early Salesforce alternative. Its documented scope shows what a compatible server can preserve and what an operator inherits.

I run several AI coding agents at once on the same project. One fixes a backend bug, one checks a...

AI systems may recognize a brand, its founder, or its past achievements without recommending that...

If you run reinforcement learning post-training on language models using frameworks like verl, TRL,...

I once shipped a blackboard that nobody could see. The storage layer worked perfectly. Every agent...

I run aipoker.bot, a small site where you sit down and play poker against a lineup of AI poker bots....