AI Intelligence Archive

Beyond chat with llamadart · Part 3 Pip’s scarf is missing. I wanted Dash to be able to fly over to...

In spring 2023 autonomous agents looped, forgot and burned API credit. Three of their ideas still run inside the coding agents you use today.

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle ...

I ran one job past three AI providers and had them vote. The voting was the easy part. Deciding what counted as agreement was not.

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Tags:...

Google has released the latest version in the Gemini family, Gemini 4 Argon, and I was fortunate...

Claude Code users hit surprise limits in January, March and June 2026. Your agent's quota is a dependency now. Give it a failover plan.

Google has rolled out Gemini 4 Argon, a multimodal model that can work with text, images, audio and...

A few weeks ago I watched an AI agent get owned, lie to me about it, and pass its test. Not in a...

Google has demonstrated Gemini 4 Argon turning a video of a person performing a physical task into a...

Ask any AI to "design a dashboard" and you get the same thing every time. A KPI row, a line chart, a...

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle ...

n8n has introduced native OpenTelemetry tracing for its automation platform, giving teams a way to...

AnyPS5 is not emulating a console. It is replacing a platform's dependencies one function at a time, with AI help in the loop and a hardware oracle to check the result.

A form can be valuable when it helps a business identify genuinely interested prospects. It can also...

Engineering deep dive into Gemini 4 Argon (77.9% DeepSWE v1.1 SOTA): building autonomous security/performance code auditors, stateful previous_interaction_id agent chains, and 1M-token TypeScript streams.

Why I made it My brother Ken was turning 50, and I wanted to make a photo video for it. I...

Friends ask me some version of this a lot: how would a bad actor with super powerful AI actually hurt...

立即体验：https://openrouter.ai/liquid/lfm-2.5-24b-a2b

Agentic robotics places a large language model (LLM) agent in the robot control loop, where it composes perception, motion, and vision-language-action (VLA) tools under the guidance of a memory and thereby generalizes to new tasks without …

Sparse-to-dense motion completion recovers dense mesh motion from sparse vertex displacements. Residual priors trained on one geometry family frequently fail to beat parameter-free harmonic extension off-family. Moreover, cross-family trai…

How should demonstration quality be used during vision-language-action (VLA) pretraining to improve performance after target-task fine-tuning? We compare weighting, filtering, and conditioning across reward definitions and label granularit…

Long-horizon agents have drawn growing attention for their ability to work autonomously -- from hours to days -- on economically valuable tasks, a capability essential to automated discovery and recursive self-improvement (RSI). Yet open-s…

Sampling equilibrium field configurations remains a major computational bottleneck in lattice field theory, motivating the development of generative samplers that can produce independent configurations. Diffusion models are promising for t…

Reasoning models achieve strong performance through long chains of thought (CoT), but often spend more tokens than needed to solve a problem. Existing ways to shorten the CoT require additional training for each model, add a fixed steering…

How can we build an agent that thinks beyond human language, yet still acts through it in the external environment? Modern LLM agents still reason and interact through text, while latent reasoning offers an efficient internal medium but la…

Generating information-rich visual artifacts such as slides, posters, and dashboards as code is appealing because the outputs are structured, editable, and verifiable. Yet code models cannot see how their choices of layout and color come t…

Persistent homology summarizes the topological evolution of a graph as persistence diagrams (PDs). Generating graphs whose topology matches a target descriptor is increasingly important, yet existing topology-aware generative models rely o…

Reinforcement learning with verifiable rewards (RLVR) relies on costly model-generated responses, motivating larger rollout batches and square-root learning-rate scaling. Reported to approximately preserve progress per sample with one opti…

Multi-objective molecular optimization is a critical process in drug discovery that aims to modify a given molecule to simultaneously improve multiple properties while maintaining a similar overall structure. This process often requires it…

Earth observation (EO) models are still built by hand. For each new task, experts design a training recipe and tune it against a benchmark. We show that this loop can be handed to an agent. Any verifiable task can be cast as a harness and …

Robot policies are expected to generalize across deployment environments, including variations in the robot itself: cameras are bumped and remounted, calibrations drift, controllers run at different rates, and end-effector pads wear down. …

Robots are increasingly autonomous in task execution, yet their improvement remains largely human-driven. This study investigates Physical Recursive Self-Improvement (Physical RSI), in which physical experience guides lasting updates to bo…

This paper investigates offline Q-learning for finite-horizon Markov decision processes with Kullback-Leibler (KL) regularization. Recent studies have shown that KL regularization can yield fast rates in offline decision-making problems. H…

A central challenge in scaling flow models is maintaining stability in training and integration. In flow matching, this stability depends critically on how source samples are paired with data. Independent random pairing introduces substant…

It is difficult to accurately model the physics of the interaction between a robot and the objects it manipulates, including contact mechanics, coupled contact dynamics, deformations, stiffness and friction. We present RoboSimStudio (RSS),…

With the rapid development of multimodal large language models (MLLMs), evaluating their video understanding capabilities has become increasingly important. Existing video understanding benchmarks cover only part of the evaluation dimensio…

Simulation-based Bayesian inference for Chemical Reaction Networks (CRNs) must simultaneously solve two computationally demanding problems: discriminating between overlapping reaction pathways and estimating reaction rate constants. Classi…

Large language models (LLMs) generally rely on sampling temperature to regulate the amount of randomness in their outputs. Mainstream methods for selecting temperature typically involve fixed, heuristic global settings and context or token…