AI Intelligence Archive

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: ...

GroundedDocs answers questions over a document set with exact citations and refuses when the evidence...

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

This is a submission for the Kaggle Benchmarking Challenge What I Benchmarked I've been a...

I use coding agents across real repositories every day. I run a small security firm, and between...

Here's a line from YouTube's auto-captions on a lecture about attention in neural...

I build Soba, an iPhone app that looks at a photo of a meal and estimates the carbs in it. People...

🌿 Trailnote — An AI Trail Companion That Tells You to Put Your Phone Away My submission...

Store reviews, users who couldn't reach the store, payments and analytics. What building a solo AI side-panel extension actually took.

Most AI chat tools are terrible language tutors. Ask a generic chatbot to practice Chinese with you...

The biggest enterprise integration risk in 2026 is not AI. It is operational neglect. This week,...

A published coding-agent score describes one frozen task slice, and it does not describe an entire...

Um benchmark reprodutível de pequenos modelos de decisão e de embeddings para classificar o objetivo do cliente em português do Brasil, e o que uma tradução paralela para o inglês revela sobre o custo do idioma.

A reproducible benchmark of small choice deciders and embeddings for customer-goal classification in Brazilian Portuguese, plus what a parallel English translation reveals about the cost of language.

After ten years in asset management, I started a full-stack developer path in 2024 and spent my time...

A native app on both stores, in five languages, built by one person with an AI as the developer. This...

I ran 65 questions against our own knowledge base and checked which ones the retrieved text actually...

"Design on your screen. Step outside with your tape measure. Touch the soil. Grow together." This...

Job searching started feeling like a second job. I was jumping between different job sites and ATS...

This is a submission for the Kaggle Benchmarking Challenge Those who read my articles know that a...

Every AI rollout comes with a dashboard. PRs merged per week, time from ticket to prototype, model...

Written for: dev.to readers and the Kaggle Benchmarking Challenge judges. I kept your format and...

Most multi-agent demos fail the moment you put them in front of real production traffic. They work...

Training an on-device YOLO26n food detection model from scratch across multi-source datasets I set...

Beyond 30-second TikTok demos: A transparent cost and fatigue breakdown of rendering long-form...