technocracy

arXiv:2604.13100v1 Announce Type: new Abstract: The shift toward intent-driven software engineering (often termed “Vibe Coding”) exposes a critical Context-Fidelity Trade-off: vague user intents overwhelm linear reasoning chains, leading to architectural collapse in complex repo-level generation. We propose Contract-Coding, a structured symbolic paradigm that bridges unstructured intent and executable code via Autonomous Symbolic Grounding. By projecting ambiguous intents into a formal Language Contract, our framework serves as a Single Source of Truth (SSOT) that enforces topological independence, effectively isolating […]

Ver mais

Key Highlights: On January 1, 2026, Saudi Arabia officially laid the foundation stone for the Hexagon Data Centre in Riyadh. While it’s easy to get lost in the massive numbers, a 480-megawatt capacity, a 30-million-square-foot site, and a Tier IV global rating, the real story isn’t about the architecture. It’s about the death of the waiting room. In practical terms, that means fewer forms, fewer applications and fewer moments where citizens are required to prove information the state […]

Ver mais

arXiv:2602.18588v1 Announce Type: new Abstract: Managing the data and metadata during the active development phase of an experimental project presents a significant challenge, particularly in collaborative research. This phase is frequently overlooked in Data Management Plans included in project proposals, despite its important role in ensuring reproducibility and preventing the need for retroactive reconstruction at the time of publication. Here we present Altar, a lightweight, domain-agnostic framework for structuring experimental data from the onset of a project without […]

Ver mais

I am training AI players for a chess-like game which has 3 distinct factions (i.e. different piece sets) and is played on a 9×9 board. The three factions are called Axiom (A), Blades (B), and Clockwork (C). With help from ChatGPT, I have managed to create 6 different AI models, one for each match up (AvA, AvB, AvC, BvB, BvC and CvC), under an Alpha Zero style approach. The structure used (which I broadly understand but largely relied […]

Ver mais

The life of a prescription at Amazon Pharmacy From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money. Conversational AI Alexandre Alves Anita Vila September 30, 01:32 PM October 02, 11:42 AM Pharmacies play a vital role in ensuring patients health, but the process of dispensing medications is far more complex than it may appear. At Amazon Pharmacy, we are using artificial […]

Ver mais

arXiv:2601.20916v1 Announce Type: new Abstract: Objective: Accurate noninvasive estimation of intracranial pressure (ICP) remains a major challenge in critical care. We developed a bespoke machine learning algorithm that integrates system identification and ranking-constrained optimization to estimate mean ICP from noninvasive signals. Methods: A machine learning framework was proposed to obtain accurate mean ICP values using arbitrary noninvasive signals. The subspace system identification algorithm is employed to identify cerebral hemodynamics models for ICP simulation using arterial blood pressure (ABP), […]

Ver mais

arXiv:2601.09040v1 Announce Type: new Abstract: End-to-end backpropagation couples all layers through a global error signal, enabling coordinated learning but requiring long-range credit assignment. Motivated by recent progress in blockwise self-supervised learning (BWSSL), we ask whether masked video transformers can be trained without end-to-end backpropagation. Applying BWSSL to masked video modeling remains relatively underexplored and must handle spatiotemporal context and long-range temporal structure. More broadly, analyses that compare BWSSL and end-to-end training in terms of learning dynamics and depth-wise […]

Ver mais

Decentralized Federated Learning (DFL) enables clients with local data to collaborate in a peer-to-peer manner to train a generalized model. In this paper, we unify two branches of work that have separately solved important challenges in DFL: (i) gradient tracking techniques for mitigating data heterogeneity and (ii) accounting for diverse availability of resources across clients. We propose $textit{Sporadic Gradient Tracking}$ ($texttt{Spod-GT}$), the first DFL algorithm that incorporates these factors over general directed graphs by allowing (i) client-specific gradient […]

Ver mais

Introduction In a fintech or wealthtech product, people constantly need quick market context. Why did this stock move. What changed recently. What should we watch next. Right now, this usually turns into manual work. Someone pulls recent returns, checks a couple fundamentals, scans headlines, then writes a short Slack or Notion note. It works, but it doesn’t scale, and every person formats it differently Dashboards help when the question is predefined. Pure LLM answers are flexible, but they’re […]

Ver mais