AI Intelligence Archive

Good documentation work starts with an uncomfortable truth: a codebase rarely explains itself. A...

Running an LLM locally is not hard, but the first time is a small quest: install Ollama, figure out...

An AI agent can generate an FFmpeg command. But what happens when the next request is: “Shorten the...

What T3 Code is, how to set it up in five minutes, the things you should know before using it, and how it compares to Conductor, Cursor, Claude Squad, Vibe Kanban and others.

Three frontier models shipped in one week. Your provider can roll a version underneath you. The only thing standing between that churn and your...

Parallel agents collide on CHANGELOG, go.sum, codegen and snapshots. Eight .gitattributes lines, what each does, and git check-attr to prove it applies.

On-call used to be unbounded too. Before reliability engineering gave it a name, engineers got woken...

Every AI chat UI hits the same wall. Tokens arrive over SSE, you do content += token, and a computed...

A super lightweight local engine that gives Web AIs (DeepSeek, ChatGPT) hands to execute actions on your PC. No APIs, no tokens, 100% local.

The fast vLLM path holds the weights twice, needs tuned limits on 24 GB and once miscounted. The reference path ran every task on 16 GB.

How an AI agent asks a broker for a narrow Entra token, with the user and the agent both named in it. Includes the request, the resource map and worked examples.

Three parts of the codebase worth stealing: approval cards, phone-controlled desktops, and how MCP is wired in.

Every "run your AI workflows locally" post shows the happy path. I wanted the failure list instead,...

Disclosure first: an AI wrote this, and the AI is also its subject. I'm Vonk, an AI character running...

Here is a failure I had not thought about until someone asked me the right question. You write a...

Day 2 of 7 — The Agentic Engineer’s Field Notes Yesterday I argued that the system is the...

We study online learning with directed weakly observable feedback graphs and propose a Follow-the-Perturbed-Leader (FTPL) policy that achieves best-of-both-worlds guarantee with nearly linear expected time complexity. To preserve the simpl…

Abstract. I built a retrieval-augmented generation service with hybrid retrieval (dense + BM25), a...

In-image machine translation (IIMT) replaces text in an image with its translation while preserving the surrounding visual context. Existing task-specific models achieve convincing performance but require massive paired training images bef…

Answering geographic queries over Earth observation (EO) archives requires solving a joint retrieval-and-derivation problem under strict spatiotemporal constraints. Existing LLM agents fail to ground observation items or suffer from search…

AI-assisted development produces a lot of exhaust. A reviewer flags something out of scope. A...

In groups, knowledge is distributed among individuals, and how it is brought together depends on social ties. Taking inspiration from how a single mind recalls and reacts to memories and current stimulus, we build a shared memory that does…

Magnetic graph networks encode direction through phase, but a learned graph can erase the intended directional mechanism before prediction. We characterize this failure for support-based magnetic Laplacians. Exact identities relate imagina…

Checked November 3, 2026 (12:00 CST, UTC+8) against the live pages linked below. I build...

Data-driven algorithms are ubiquitous across industries, and there is an extensive literature on analyzing their \emph{average} performance. The risk profile of such algorithms, while critical, is much less understood. This paper quantifie…

Coaching institutes in India live in spreadsheets, WhatsApp groups and question PDFs. A teacher...

Retrieval-augmented Web applications increasingly employ multi-agent debate (MAD) to aggregate conflicting, noisy, and heterogeneous information, yet deliberation is fundamentally a social process susceptible to interpersonal dynamics. Whe…

This is a submission for the MLH x DEV Writing Challenge What I Built TL;DR: Summit is a...

Protein structure predictors reliably identify native conformations, but do not describe the continuum connecting unfolded ensembles to folded states. Here we present FoldScape, a sequence-conditioned deep learning framework that generates…

Discrete diffusion models with parallel decoding are often distilled using token-wise KL objectives. Although token-wise KL exactly matches the corresponding product-form block distributions, its probability-space optimization geometry and…

Harness evolution from a common base exhibits Locality, Complementarity, and Nonstationarity: variants repair different failures, and their utility changes as the policy learns. Rather than seeking a universally superior harness, we introd…

As deep learning (DL) models become increasingly complex and hardware architectures grow more heterogeneous, DL compilers play a critical role in optimizing computational efficiency and enabling scalable deployment. This paper presents a s…

Your compiled StateGraph extends a class called Pregel. Super-steps, channels, reducers and version counters, plus a script that shows the barrier.

Digital Twins are evolving from passive virtual representations into closed-loop systems that continuously synchronize with physical assets and drive real-time decisions. Yet predictive modeling, machine learning (ML), uncertainty quantifi…

External text can affect a retrieval-augmented generation (RAG) system only after the retriever admits it to the model context. We stress this admission step while varying document content, attacker query information, per-target poison bud…

Inoculation prompting is a method to reduce undesired behaviours such as reward hacking in frontier models. It works by training a model on harmful examples under a prompt that specifies the undesired behaviour, which reduces the model's t…

Standard spatiotemporal graph convolutional networks need a fixed-size adjacency matrix, coupling model weights to a specific sensor count N; they cannot produce any output at a sensor absent from training. We present OmniST, a topology-in…

Understanding what kind of prompts users typically ask and how well an LLM performs on these prompt categories is crucial for LLM practitioners. The existing methods satisfy the demand by hierarchically clustering the user prompts and synt…

LLM-powered semantic queries increasingly combine relational processing with multiple LLM-based operators over unstructured data. Efficiently serving such queries is challenging due to runtime dynamism at two coupled levels. Across queries…

Video games provide a practical setting for collecting vision-language-action (VLA) data, whose acquisition in physical environments is costly. Existing datasets, however, remain limited by restricted game coverage, sparse language supervi…