February 2026

arXiv:2602.17667v1 Announce Type: new Abstract: In video search systems, user historical behaviors provide rich context for identifying search intent and resolving ambiguity. However, traditional methods utilizing implicit history features often suffer from signal dilution and delayed feedback. To address these challenges, we propose WeWrite, a novel Personalized Demand-aware Query Rewriting framework. Specifically, WeWrite tackles three key challenges: (1) When to Write: An automated posterior-based mining strategy extracts high-quality samples from user logs, identifying scenarios where personalization is strictly […]

Ver mais

We present Federated Learning Playground, an interactive browser-based platform inspired by and extends TensorFlow Playground that teaches core Federated Learning (FL) concepts. Users can experiment with heterogeneous client data distributions, model hyperparameters, and aggregation algorithms directly in the browser without coding or system setup, and observe their effects on client and global models through real-time visualizations, gaining intuition for challenges such as non-IID data, local overfitting, and scalability. The playground serves as an easy to use educational tool, […]

Ver mais

Physics-informed neural networks (PINNs) have emerged as a promising mesh-free paradigm for solving partial differential equations, yet adoption in science and engineering is limited by slow training and modest accuracy relative to modern numerical solvers. We introduce the Sequential Correction Algorithm for Learning Efficient PINN (Scale-PINN), a learning strategy that bridges modern physics-informed learning with numerical algorithms. Scale-PINN incorporates the iterative residual-correction principle, a cornerstone of numerical solvers, directly into the loss formulation, marking a paradigm shift in […]

Ver mais

… and I’d love to talk to people about it. I don’t want to just spam links, but I have them if anyone is interested. I’ve done three cool things that I would like to share and get opinions on. – a dense integer only neural network. It fits in l1 cache in most uses and so I have NPCs with little brains that learn. – a demo I’ve been sharing of an NPC solving logic puzzles through […]

Ver mais

The rapid growth of medical imaging data has intensified the need for advanced computational tools to support clinical decision-making. However, centralized approaches to artificial intelligence development raise significant challenges related to privacy, regulation, and generalizability. This paper introduces FedIHRAS (Federated Intelligent Humanized Radiology Analysis System), a privacy-preserving federated learning framework that enables multi-institutional collaboration for chest X-ray analysis. FedIHRAS integrates pathology classification, visual explainability, anatomical segmentation, and automated clinical report generation into a unified system that incorporates adaptive […]

Ver mais

In the Symfony ecosystem, Doctrine is the de facto standard for database interaction. However, developers often hit a crossroads: should I use Doctrine’s object-oriented Query Language (DQL) or drop down to raw, Native SQL This article explores both approaches using Symfony 7.4 and PHP 8.4+. We will build real-world examples to demonstrate performance, maintainability and developer experience. Prerequisites & Environment To follow this guide, you need a standard Symfony 7.4 environment. We will use the official ORM pack. Installation: […]

Ver mais

The intersection of AI agents, blockchain, and everyday finance is no longer a distant vision—it’s happening now, and fast. From agentic commerce that hides complex rails behind simple conversations, to trust stacks built on permission, proof, and verifiable receipts, the industry is shifting toward AI as the true interface for financial decisions. Users want outcomes in plain language (“pay this,” “save that,” “grow my assets safely”), not chains or wallets to manage. Fresh off insights from Consensus Hong […]

Ver mais

The era of cloud-tethered computing is officially coming to an end. For the last three years, developers have been held hostage by API rate limits, exorbitant subscription costs, and the looming threat of closed-source data harvesting. Big Tech told us that local AI was a pipe dream. They claimed that running frontier models required server farms the size of small cities. They wanted us dependent on their infrastructure, paying rent for every token generated. Then came the lobster. […]

Ver mais

There was no outage. No alerts. n No failed pipelines. Everything “worked.” But our BI environment was slowing down, getting expensive, impossible to budget for. Not because the warehouse was failing. Because the design was wrong. AI will expose that at scale. The Architecture That Punished Curiosity. For years, the default in modern BI orgs was “DirectQuery”. Users → Reports → Semantic Model → Warehouse → Execution → Results. Every click triggered compute. It felt good. It felt […]

Ver mais

I’m trying to understand the exact logic behind this key step in dynamic programming. We know that V* satisfies the Bellman optimality equation: V*(s) = max_a [ r(s,a) + γ Σ_{s’} P(s’|s,a) V*(s’) ] Now define the greedy policy with respect to V*: a*(s) = argmax_a [ r(s,a) + γ Σ_{s’} P(s’|s,a) V*(s’) ] and define the deterministic policy: π*(a|s) = 1 if a = a*(s) 0 otherwise Step 1: Plug greedy action into Bellman optimality Because π* […]

Ver mais