This illustrates a widespread problem affecting large language models (LLMs): even when an English-language version passes a safety test, it can still hallucinate dangerous misinformation in other ...

I test-drove both. Here’s what I learned. In early March, OpenAI unleashed a one-two punch, dropping two major frontier models just days apart.

Choosing an AI model is no longer about “best model wins.” Instead, the right choice is the one that meets accuracy targets, fits latency and cost budgets, respects compliance boundaries and ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

mcp-agent's vision is that MCP is all you need to build agents, and that simple patterns are more robust than complex architectures for shipping high-quality agents.

Utilizing fake data (simulated based on mechanism models or generated through data-driven models) for data enhancement is a popular approach to solve the problem of fault diagnosis with small samples.

This paper describes the evolution of synthetic data, common data models, and federated learning supported by strong cross-sector collaboration to support digital health research. Lessons learned are ...

Abstract: Creating aesthetically pleasing data visualizations remains challenging for users without design expertise or familiarity with visualization tools. To address this gap, we present DataWink, ...