AI Intelligence Archive

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the...

A tweet went around saying: "No human will ever write code better than LLMs. Accept this fact, stop...

Tokens per second per watt improved roughly 3.5x in two years. Here is what that does to API pricing, device BOMs and the economics of shipping a model instead of calling one.

Error-correction overhead fell by roughly 10x in five years. Here is what that curve does to drug discovery budgets, cryostat supply chains and the price of a quantum hour.

Why Forward Deployed Engineers Are Suddenly Hot: The Death of the Centralized AI...

Agents commit PHP that never met your formatter or PHPStan. A lefthook setup that blocks the commit, hands the agent the error, and survives new worktrees.

A tool call can pass schema validation and still select the wrong product, skip a prerequisite, or...

📌 Note: Interactive math rendering is currently being updated for this post. In the meantime, you...

Zero-width, bidi and Unicode tag characters hid instructions in AI rules files. How they work, plus a ripgrep check and a git hook that block them.

Summary: AI coding agents rarely lie. They do something worse for a one-person shop: they state...

# Build RAG in C# with ASP.NET Core and Qdrant Build RAG in C# with ASP.NET Core, Qdrant and Ollama:...

A few months ago my typical afternoon looked like this: four terminal tabs, four Claude Code...

Deep dive into how function calling actually works under the hood — JSON Schema to CFG compilation, pushdown automata, logit masking, and why the model literally cannot produce invalid structure.

Static analysis and LLMs are a good pairing. I'm not here to argue otherwise. But a lot of teams are...

The second client on the hot path: net/http, encoding/json and a bufio scanner for Server-Sent Events, in a static binary from a scratch image. What the standard library gives you, and the one thing it does not.

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine. ...

Static rules break on novel agent actions, and blind human approvals break on volume. A concept we are evaluating: AI at the meta level drafting rules, a deterministic pipeline deciding, and a human sealing.

An opinion on how IAM should treat AI agents, as a new kind of principal that starts every session with nothing and borrows exactly what the task needs, with the user's consent.

In the first article of this series we put four 2026 context-engineering principles on one map. This...

Eight checks before an unattended Claude Code run: sleep, idle compaction, usage-limit waits, turn caps, permissions, worktrees, a test gate, a ping.

This week's Hacktoberfest theme is Ghost in the Machine. Unfortunately, I don't have enough time to...

The vibe coding argument has been running for over a year and has settled nothing, because it's a...

Automated detection has become the essential safeguard against realistic synthetic media, but deploying it at scale requires training on sensitive data from multiple organizations, putting privacy and the transparency demanded by forensic …

Graph analytics generates irregular, topology-dependent memory-access streams via indirect traversals, limiting data prefetching. Accurate prediction enables timely prefetches that hide memory latency. However, ML predictors couple short h…

Somewhere between faster technology and smarter machines, we must never forget the ordinary people...

What PredictSphere taught me about orchestration, data quality, adaptive learning, and the...

AI coding agents now do long, multi-step and multi-session software work with little supervision. When a developer comes back to that work, the useful question is not what the model said but what was actually done, by whom, and whether it …

In many real-world classification tasks, datasets exhibit class imbalance, which can degrade the generalization performance of conventional learning algorithms. Data complexity has recently been recognized as a more objective indicator of …

View- and target-specific echocardiography AI models capture useful but complementary information and may not achieve sufficient predictive performance in isolation. A learned ensemble is a natural way to combine these outputs, but heterog…

I built Off the Wall, a plugin for Claude Code and Codex. It saves the corrections you give your...

Lately I've been using video diffusion models and learning more about them. As I was digging around...

We study first-order and best-of-both-worlds regret guarantees in multi-armed bandits. Pogodin and Lattimore (2019) proposed an algorithm that combines minimax-optimal worst-case regret with a first-order guarantee whose loss-dependent ter…

Deep neural networks achieve strong performance across many tasks but remain vulnerable to adversarial perturbations. Adversarial training (AT) is one of the most effective defenses, yet it suffers from high memory cost on large models and…

Planning at run time, as in robots that re-plan while they act, needs a planner that reads the PDDL its users write (durative actions, numeric resources, time windows, continuous change), answers quickly, and delivers only validated plans.…

Imitation learning has become a widely adopted approach for vision-based robot policies, owing to its conceptual simplicity, scalability, and ability to leverage large-scale datasets. As these policies have grown more capable, action chunk…

A 74B vision agent model in 22 GB on one A40: 136 tokens/s with its drafter, 70 without, about 27 GB used. What the 24 GB leaves out.

Masked diffusion models train a denoiser on masked cross-entropy and generate by unmasking many positions in parallel. Existing MDM sampling bounds assume an exact denoiser or leave its error uncontrolled while training bounds cover only t…

Softmax routing in mixture-of-experts models can concentrate probability on a subset of experts, suppressing access to the others. We study how this concentration forms, why it persists, and how suppressed probabilities recover. For fixed …

Label-free test-time reinforcement learning adapts vision--language models using rewards derived from their own predictions. However, misinterpreted visual evidence and sensitivity to textual formulation can produce a consistent but incorr…

Reliable local search is essential for LLM agents to support everyday decisions and longer plans by finding places that meet users' needs at given times and locations. Yet existing benchmarks provide limited coverage of whether search resu…