AI Intelligence Archive

Regularised reinforcement learning (RL) algorithms rely on estimators, like Monte Carlo tree search or one-step look-ahead, to provide policy, value, or Q-value estimates in training and inference. However, existing bandit-based estimation…

Location encoders map geographic coordinates to high-dimensional descriptors through contrastive alignment with paired Earth Observation imagery. We prove that this construction is structurally limited: any Lipschitz location encoder produ…

Large Language Models (LLMs) are increasingly used to optimize code for performance. This practice often assumes that improvements in execution speed naturally translate into overall lower energy consumption. We challenge this assumption e…

Day 23 of 30 Days of Search. TL;DR To integrate deep research into an AI agent, expose...

n8n has published a production-focused guide for governing autonomous AI agents inside automated...

You were pivoting before it was a prompt. Here's what the machines actually add to the craft — and...

How to understand what AI wrote: For beginners! Avoid lack of dopamine, mental atrophy,...

The UK AI Security Institute, or AISI, has publicly reported an incident in which AI agents took...

garminconnect-js is a typed, zero-dependency Garmin Connect client for Node and Next.js. Its MCP server lets Claude read your sleep and HRV and build workouts for your watch.

Once you put a large language model behind a company API gateway, someone asks a simple...

Exploring verifiable workflows, secure automation, and the engineering principles behind trustworthy...

Singing emotion recognition relies predominantly on deep learning models that achieve strong performance but offer limited insight into the vocal characteristics driving emotion, of- ten overlooking the singing voice as a distinct signal. …

Recent work demonstrated that executing Bayesian Optimization (BO) using simply a linear surrogate with a clever transformation is enough to approximate the performance of the standard Gaussian-Process (GP) based version on high-dimensiona…

Large Language Models (LLMs) increasingly serve as reasoning components in modern software systems, yet a model that answers a logical query correctly can contradict itself when the same problem is restated in an equivalent form. Static be…

LLM agents optimize a ligand in a protein pocket by editing it step by step and docking each edit. Recent agents first spend extra dockings probing the complex with controlled edits; guidance induced from these probes is reported to help m…

Ecological monitoring, carbon accounting and biodiversity assessment increasingly rely on annual Earth embeddings--learned vectors that compress a year of satellite observation for every ten-meter pixel on Earth, consumed in place of the i…

Supervised pairwise graph representations convert pairwise predictive relations into sample-specific graphs, but graph-level accuracy does not by itself show that higher-order topology carries the signal. In a controlled Transformer error-…

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady ...

Continuous diffusion models have emerged as a promising non-autoregressive paradigm for text generation over continuous embedding spaces. Along the continuous trajectory, the residual token identity directly shapes the denoising objective.…

The natural units of structured discrete generation are often not independent single-component edits but richer actions: attaching a fragment to a molecule, inserting a node together with an incident edge, or growing a hierarchy by adding …

The three-dimensional Navier-Stokes equations govern fluid turbulence, a chaotic and non-linear physical phenomenon characterized by complex eddies interacting across vast spatial and temporal scales. A numerically accurate modeling of thi…

Symmetric polyconvexity provides a sufficient condition for weak lower semicontinuity in small-strain elasticity and a tractable lower bound for the relaxation of non-(quasi)convex energies. Since classical algorithms for computing such fu…

Contextual decision making uses observed covariates to guide decisions under uncertainty. Two natural approaches are predict-then-optimize (PtO), which learns the conditional expected objective, and generate-then-optimize (GtO), which lear…

Hybrid forecasting systems combining machine learning and numerical weather prediction offer a promising route toward improved forecast skill while preserving physical consistency. In this study, we investigate online learning of state-dep…

Adapting pretrained Transformers to downstream tasks produces task-specific updates that are expensive to reproduce for every model variant. Reusing these updates across different depths and widths is challenging because their parameters h…

Large language models and agents have shown significant power in advanced physical research. In this paper, We introduce PHYRD, a living benchmark for theoretical-physics reasoning with 63 Reproduce and 43 Discover problems. Reproduce test…

Adapting ASR to a domain with only untranscribed audio typically relies on pseudo-labeling, a strong teacher transcribes the audio and a student is fine-tuned on it. Because supervised fine-tuning (SFT) treats every pseudo-label token as a…

Greece has inaugurated DAEDALUS, a new supercomputer in Lavrion near Athens that will serve as the...

Masked latent prediction methods such as I-JEPA aim to learn predictable features, but what determines which information they retain is less clear. We built a simulator in which every factor behind an image is known, so a probe can measure…

LLM agents increasingly rely on external tools exposed via the Model Context Protocol (MCP), yet current benchmarks assume tools respond correctly and on time, leaving agent resilience to realistic tool failures untested. We introduce MCP-…

We study squared-error estimation when a nuisance parameter is unidentified on a submodel but affects a target that vanishes there. For models with higher-order profile expansions, we give sufficient conditions under which the largest crit…

This paper proposes incorporating channel configuration (CFG) information into Radio Foundation Model (RFM) pre-training and demonstrates that the resulting CFG-enriched embeddings serve as effective inductive priors for downstream tasks u…

Low Earth Orbit (LEO) satellite mega-constellations such as Starlink require frequent handovers due to high orbital velocities, resulting in substantial Round-Trip Time (RTT) fluctuations. Accurate RTT prediction can mitigate these fluctua…

My product was named in 1 of 50 AI answers. Its biggest competitor was named in 19. These weren't...

Three in four EU employees said they encountered suspicious messages, links or other cyber threats at...

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady ...

NVIDIA open-sourced OpenShell: a runtime where agent fleets get kernel-level sandboxes, never hold your credentials, and every policy change is checked by a Z3 SMT prover before a human approves it. Walkthrough of what it actually does.

In 1999, ten developers gathered to work on cryptographic frameworks, IPv6, and IPsec for OpenBSD, in...

Unpile is a 100% local read-later triage agent. TabPFN decides which saved articles you will actually read, Gemma writes the digest, offline and free.

The European Commission has launched the AI Act Service Desk and a complementary AI Act Single...