You'll Lose Again If You Keep Betting On A 2026 Bubble

Risk-free rates are much lower than in 2000, supporting higher equity valuations without replicating past bubble dynamics.

ARMOUR Residential REIT Stays On Hold As Funding Costs Remain In Focus

ARMOUR Residential REIT (ARR) gets a Hold reaffirmed. See more on its revenue growth vs rising funding costs, payout ...

After judge’s ruling, HHS authorized to resume sharing some Medicaid data with deportation officers

The nation’s health department can resume sharing the personal data of certain Medicaid enrollees with deportation officials.

Data 2026 outlook: The rise of semantic spheres of influence

As for the AI bubble, it is coming up for conversation because it is now having a material effect on the economy at large.

Last year's odd economy in five charts, and what to watch for in 2026

The economy in 2025 was filled with contradictions, as growth was healthy while hiring slowed, inflation stayed elevated and ...
IEEE

Adding Data Quality to Federated Learning Performance Improvement

Abstract: Massive data generation from Internet of Things (IoT) devices increases the demand for efficient data analysis to extract relevant and actionable insights. As a result, Federated Learning ...

Designing A Healthcare Data Strategy That Actually Moves Margin

For healthcare data strategy projects, there are four essential elements to turn aspiration into a plan for recurring ...
GitHub

A simple, easy-to-hack GraphRAG implementation

😭 GraphRAG is good and powerful, but the official implementation is difficult/painful to read or hack. 😊 This project provides a smaller, faster, cleaner GraphRAG, while remaining the core ...
The Conversation

Data centers need electricity fast, but utilities need years to build power plants – who should pay?

Theodore Kury is the Director of Energy Studies at the University of Florida’s Public Utility Research Center, which is sponsored in part by the Florida electric and gas utilities, the Florida Public ...
IEEE

Counterfactual Data Augmentation With Denoising Diffusion for Graph Anomaly Detection

Abstract: A critical aspect of graph neural networks (GNNs) is to enhance the node representations by aggregating node neighborhood information. However, when detecting anomalies, the representations ...