AI Intelligence Archive

Open Activity Monitor while a few coding agents are running and you get a wall of node and python...

I built an evaluation harness. I found nine bugs in it. Every single one would have made my results...

The AI thinks, the gate decides D-Engine: a deterministic harness that matches...

Two weeks ago I published the first piece of this series: the official MCP filesystem server — 228...

Google Research and its collaborators have published a complete wiring diagram of the adult male...

An M2 MacBook Air packs several compute engines into a single chip: CPU vector units, the AMX matrix...

Hello, I'm Shrijith Venkatramana, and I'm building LiveReview — a blast-radius aware AI code review...

In 2020, Shopify announced that React Native was the future of mobile at Shopify. In January 2025,...

The quality of a RAG system is decided long before the query reaches the LLM. I learned that the...

You built something and it "works". But do you know whether it works? Most of us don't. Your tests...

A short rant on the Claude, Gemini, and Microsoft Copilot experience

Bringing backend predictability to multi-agent systems I've been hearing the phrase "graph...

Rasmus Moorits Veski, Rachid Guerraoui, and David Froelicher posted arXiv 2609.06500 on 6 September...

On 3 Sep ARC Prize scored GPT-6 Astra at 62.7% in the shared harness and 99.9% in OpenAI's adapter.

One distinction I underestimated while building agent systems was the difference between a plan and...

Nobody wants to buy tokens. They want useful work, and eventually, AI will be priced that way...

Counterfactual regret minimization (CFR) is one of the few large numerical workloads that still runs faster on CPUs than on GPUs. Each iteration sweeps a game tree with up to billions of states in millions of small, interdependent gather a…

Generalization under distribution shift remains a core challenge in modern machine learning, yet existing learning bound theory is limited to narrow, idealized settings and is non-estimable from samples. In this paper, we bridge the gap be…

I first started playing around with WebMCP back in March. The idea immediately made sense to me:...

As the supply of human-written text is exhausted, it has become standard practice to repeat language model training data. Prior work has studied data repetition for densely activated Transformers, but the effects of data repetition remains…

Camera traps often run in the field on edge hardware with limited or no connectivity, making small, locally-deployable vision-language models (VLMs) -- not frontier-scale ones -- the practically relevant class to evaluate for species ident…

Generative artificial intelligence changes how firms reach customers, but standard marketing data do not record how often users see and notice a firm's name in generated answers. We develop Generative Marketing Mix Modeling (GMMM) to estim…

Out-of-distribution length generalization, namely to extrapolate a task from short to longer context, has been studied intensively for transformers. Here we focus on distance generalization, which probes performance when inter-token distan…

Agentic AI is moving from bounded task execution toward systems that retain consequential state, continue operating and adapt across task boundaries. That shift creates a control problem that current harnesses largely solve by hand: object…

Artificial Intelligence does more than create a governance problem. It can also reveal where institutions have already failed to provide responsiveness, belonging, care, and accountability. Once deployed, AI becomes an intervention in thos…

Automatic Music Transcription (AMT) for guitar remains limited by three challenges: existing systems often fail to capture expressive techniques such as slides, bends, and percussive hits; they often assign notes to incorrect string-fret c…

Spatial reasoning depends not only on metric properties such as distance, angle, and shape, but also on topological relations that remain invariant under continuous deformation. Cognitive science identifies these relations as foundational …

Causal discovery aims to uncover causal structures from data and is fundamental to scientific reasoning and intervention-based decision making. Its evaluation relies heavily on structural causal models (SCMs), which specify a causal graph …

Solving novel view synthesis (NVS) for millimeter-wave (mmWave) radar requires a renderer that is physically faithful, complex-valued, and multi-viewpoint-tractable. No prior method achieves these three properties simultaneously. Different…

As Speech Large Language Models (speech-LLMs) become increasingly multilingual, Arabic remains significantly underrepresented, highlighting the need for dedicated infrastructure to train and evaluate Arabic speech-LLMs. To address this gap…

Zero-cost proxies rank architectures cheaply, but their reliability varies across search spaces. We introduce CoRA-NAS (COarse Ranking + Anchor-residual), a two-stage framework combining a static ranking prior with low-cost learning-curve …

Large language models generate fluent text that can contain unfaithful claims -- a phenomenon known as hallucination. We present a multi-signal detection pipeline combining fine-tuned DeBERTa-v3 classification, Monte Carlo (MC) Dropout unc…

Many biological discovery problems require experiments to be selected sequentially under constrained budgets. CRISPR screening is a prominent example, as exhaustive perturbation testing is often infeasible and candidate perturbations must …

Recently, a wide range of recommendation algorithms inspired by deep learning techniques have emerged as the performance leaders on several standard recommendation benchmarks. While these algorithms were built on different DL techniques (e…

Recursive self-improvement (RSI) enables AI systems to turn experience and feedback into persistent changes that improve both their capabilities and the process of future improvement. We first use the Headroom-Closed Index (HCI) to reveal …

Continuous glucose monitoring (CGM) provides high-frequency measurements of glucose dynamics and enables short-term glucose forecasting for diabetes management. Although time-series foundation models have shown strong general forecasting a…

A language model normally begins training with random word embeddings: whatever 'banana' means must be learned from training corpora. I implement St. Augustine's picture of word learning, meaning by ostension, for a small masked language m…

The European Union is signaling a stronger push to protect children from harmful and addictive online...

HookPry shows agent harnesses will run new lifecycle-hook commands after a trusted plugin update, with no model decision and almost no scanner coverage.