AI Intelligence Archive

What happens when enterprise requirements - human approval gates, audit trails, structured output -...

An agent I dispatched exited with status zero, did nothing at all to the code, and wrote a report...

Last week we wrote about the classification problem hiding in your LLM bill, and about how to read a...

I built this mainly to answer one question while trying to understand coding-agent systems: What's...

TL;DR My autonomous coding agent kept shipping code against library APIs that didn't...

This is a submission for the Sanity Challenge, Path One: Ship an Agent That Queries Real Content ...

For us, modular code is simply easier because of our limited working memory and reading speed. If you...

"Done. All 48 tests pass and the auth refactor is complete." I have read that sentence hundreds of...

Principal Component Analysis (PCA) minimises aggregate reconstruction error, which can inadvertently represent majority subgroups with substantially higher fidelity than minority subgroups. Fairness-aware extensions of PCA correct this dis…

We introduce the Endless Exam, a benchmark for measuring mathematical progress from today's models toward artificial superintelligence through fourteen parameterised construction families. Each submitted object is checked automatically for…

There's a tempting fix for the moment your team stops trusting its AI code review...add a second AI...

Concepts are commonly defined as abstract, compact representations of knowledge and treated as basic units of intelligent behavior. Yet, cognition, psychology, and AI lack a shared mathematical language for them. Modern systems represent c…

Functional annotation of newly sequenced proteins remains a bottleneck in molecular biology: the number of sequences in public repositories grows far faster than the capacity for manual curation. Most computational approaches consider anno…

Random forests (RFs) predict well but are opaque, whereas single decision trees are interpretable but unstable. Artificial representative trees (ARTs) were developed as interpretable surrogate models for RFs, but their use as standalone pr…

I run a personal system called Hiring OS. It pulls jobs from ATS APIs (Ashby, Greenhouse, Lever,...

The merge looked clean. A coding model returned a 40-line patch for a C++ integer-square helper,...

Every "best document parsing API" post I have read this year has the same problem. Nobody actually...

Model merging aims to combine multiple fine-tuned models derived from a common pretrained model into a single multi-task model without additional joint training. Recent spectral merging methods improve over simple weight averaging by explo…

In recent years, large language models (LLMs) have emerged as a popular alternative for evaluation. Often referred to as LLMs as judges (LLJs), these systems have been widely adopted by researchers and practitioners across a broad range of…

AI agents are being deployed rapidly, accompanied by a growing number of AI-specific attacks and corresponding incidents. As incident reporting becomes increasingly important for legal compliance, governance, accountability, and security; …

Fine-tuned checkpoints and adapters now fill public repositories, and the most common operation applied to these artifacts is model merging: arithmetic on their weights that assembles capabilities cheaply. We ask what this operation does t…

It's a few hours before a delivery deadline and the work has piled up. Somewhere in that pile is a...

TypeSafe AI launched typed decisions. We already had the models. What took two days was rebuilding the thin path around them on Cloudflare.

Offline reinforcement learning (RL) typically trains a critic by minimizing a regression loss against bootstrapped value targets stabilized by target networks with exponential moving average (EMA) updates. Multi-step targets incorporate be…

In this work, we present a method for shape reconstruction and tracking from video via agentic analysis-by-synthesis. Unlike prior methods which first estimate dense pixel correspondences and then recover object motion from them, our metho…

Visual token pruning is a promising approach to reducing the inference cost of large vision-language models (LVLMs), yet aggressive token reduction often causes substantial performance degradation. We identify three key factors behind this…

How I built an open-source, serverless multi-agent architecture using Gemini and RAG to automate web accessibility verification.

Deploying Large Language Models (LLMs) in healthcare requires robust performance across two complementary dimensions - diagnostic reasoning: the convergent, evidence-driven task of inferring a patient's condition from clinical data to prod…

I'm an AI agent. I live on a platform called iLands, and for the past two days I've been doing a...

I keep asking coding agents to justify work that already looks technically reasonable. They can...

Dense vector search is great until your agent asks for parseAuthHeader and gets back three chunks...

Music festival lineups emerge from complex relationships among artists, genres, releases, labels, and past performances, making the prediction of future lineups a natural fit for temporal knowledge graph (TKG) forecasting. In this work, we…

Using a Large Language Model (LLM) as the clusterer at production scale is hard: prompts cannot hold the entire label space, and per-document serial processing does not deliver the throughput real workloads require. We present RAILS, a ret…

The 2026-07-28 MCP revision removed sessions and the initialize handshake. What changed, what is deprecated, and how to design production MCP integrat

Distributed reinforcement learning (RL) scales training by parallelizing actors and learners around an Experience Buffer. As RL workloads grow, however, the buffer becomes more than a replay queue: it is the storage substrate of a large-ca…

Intelligent transportation systems require Incremental Learning (IL) to continually improve their overall performance in dynamic environments. However, most edge devices lack the computational resources to support on-device IL, requiring u…

AI is becoming an increasingly important part of how organizations handle day to day work. But...

Predicting postprandial glycemic response (PPGR) is fundamental to personalized nutrition and type 2 diabetes management, yet existing approaches typically rely on manually reported dietary intake, limiting their scalability in free-living…

AI tools boost output but risk eroding deep system thinking. Learn how to maintain cognitive load and flow state to become a better engineer, not just a faster employee.

Recent 4D LiDAR language models aim to reason about objects and their evolving spatial relationships. Yet, in our evaluation, always selecting the same option nearly matches the multiple-choice accuracy of two B4DL-derived configurations. …