AI Intelligence Archive

YOU got it right. We migrated 70,000 tests (reads: 70 thousand) from Jest to Vitest. The logical...

200 real URLs, one vanilla agent, zero challenge solving — 82.5% readable, 72 hosts blocking every AI crawler, zero x402 yet, and one site running a declared paywall with the gate up.

15 subagents, one producer, and the rules I had to write after things went wrong.

Originally published at cchinchilla.dev. Part 6 of From code to weights, a 12-part series on ML...

The EU AI Act will introduce new transparency duties for businesses that provide or deploy certain AI...

(and the bug that froze our masks — a regression story about wiring performance switches to product...

In December 2025 I shipped a small CLI called Context Bank. The idea was simple and, I still think,...

If you think AI cybersecurity is currently being handled by smart people with everything under...

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass ...

Day 8 of 30 Days of Search. A company can report strong growth and still disclose risks that...

Building SortSense: A Local AI File Organizer Built in a Single Hack Day hacktoberfest...

Memory-augmented mobile GUI agents store successful execution trajectories and reuse them in later tasks, but a stored trajectory rarely matches a new task exactly. The new task may use different parameters, share only some of its steps wi…

Self-blended images are widely used to train face-swap detectors, but primarily capture blending artifacts. We investigate whether adding illumination inconsistencies improves detection. Temporal Self-Blended Images (T-SBI) transfer lighti…

Complete orthogonal predictive coordinates do not by themselves bind a latent direction to a named intervention. We present a mathematical and synthetic audit motivated by vascular device-vessel suitcordance. Capacity-matched least-squares…

Unsupervised learning is one of the main branches of machine learning. Here I argue that unlike the other branches of machine learning (supervised and reinforcement learning), unsupervised learning is a rather heterogenous field that can s…

Puzzles are widely used to evaluate the reasoning capabilities of artificial intelligence (AI) systems for sequential decision making, yet approaches originating from different paradigms are rarely compared under unified conditions. To add…

This study addresses the problem of structured sentiment analysis, whose goal is to obtain a fine-grained sentiment graph where the nodes represent spans of sentiment holders, targets, and expressions, while the arcs define the relationshi…

Existing reaction models primarily learn molecular transformations, whereas enzy- matic reactions depend jointly on molecular structure and catalytic function. We formulate this problem as learning an enzymatic reaction space linking react…

Foundation models supply reinforcement learning (RL) with priors that mitigate its longstanding weaknesses in sample efficiency and transfer, but their token-by-token generation makes queries sequential and costly. Jev, a recently released…

In the graph model for conflict resolution (GMCR), a decision maker (DM) either moves the conflict to another state or does nothing. The basic definitions leave inaction implicit, so every action that leaves the state unchanged is treated …

Image-to-3D generation has become increasingly capable of producing objects that closely resemble the input image, and an outstanding challenge is to reproduce the depicted object itself, including the specific geometry that defines it. In…

I built an MCP server that lets you click a layer on your running web page or Android app, drag it, and hand the exact element to Claude Code, Cursor or Codex.

Fusing a learned camera-noise fingerprint with an RGB appearance backbone is an appealing route to generator-independent deepfake detection, because the noise residual is grounded in image-formation physics rather than in the texture stati…

Verifier scores now serve as both benchmark metrics and training rewards for large language model (LLM) agents, and a change in score is routinely read as a change in capability. It may instead reflect a change in the evaluation. We introd…

Diffusion models generalize early in training and later reproduce individual training samples. Standard tests detect memorization only once one-shot generation produces near-copies, leaving a released model unaudited until its outputs fail…

A coding-agent score is evidence only when the dataset, the metric, and the control surface are...

Reliable predictive uncertainty in Laplace approximations depends critically on the prior precision, yet selecting it requires a posterior sweep that is prohibitively expensive for neural networks with billions of parameters. Under the Max…

Online platforms contain growing numbers of bots, deceptive reviewers, and scam accounts that imitate legitimate users. Such camouflage blurs graph neighborhoods and behavioral attributes, making it difficult for graph neural networks (GNN…

Deep reinforcement learning agents reach strong performance in real-time strategy games but can be brittle against opponents outside their training distribution. Separating strategic command selection from learned unit control allows diffe…

Autonomous driving capabilities depend strongly on the distribution of scenarios encountered during training. Existing methods commonly construct or dynamically adapt training scenario distributions using surrogate criteria such as realism…

On-policy distillation (OPD) supervises student-generated trajectories with token-level teacher signals. Its sampled-token variant avoids the cost of full-vocabulary probabilities. Yet we find that training on fewer tokens can outperform f…

Originally published on metalbear.com. In January we published How Our Engineering Team Uses AI. The...

Improving a long-horizon LLM agent means evolving the harness around a frozen model or training its weights. We let a self-evolving harness make the system stronger first, then cross seed and evolved harnesses with base and trained weights…

Automated interviewers and conversational agents are increasingly used in research, recruitment, customer service, and education. However, many existing systems rely on fixed question sequences and provide limited context-based personaliza…

What we built Prompt Heist is a browser game about prompt injection. You are the Cipher...

We, Team Latent, built TrialBridge during the Hacktoberfest Hack Day Coimbatore x (INIT Club &...

Every week, perfectly fixable things end up in the bin. A kettle with a tripped fuse. A lamp with a...

I built Prompt Heist for the Hacktoberfest Hack Day (Coimbatore x Init Club and Idea Club). It is a...

OpenAI published hundreds of AI-produced math results before fully formalizing them. Two days later, three are gone — and that is the system working, not failing.

My comment to yesterdays Dev.to post: Web components failed. We can fix them became a full post: ...