An image-only artificial intelligence (AI) model for predicting the five-year risk of breast cancer provided stronger and more precise risk stratification than breast density assessment, according to ...

The ongoing government shutdown delayed the release of the Commerce Department's initial estimate of the third-quarter gross domestic product (GDP), as other data sources suggest solid economic growth ...

The Reserve Bank of Australia’s model of the neutral cash rate implies a “significant downward revision” to its estimates while the job market is seen as tighter than previously thought, according to ...

When I connect MCP to Semantic Kernel, MCP has a feature called 'progress' which can be used to show the progress of tool execution. Does Semantic Kernel (particularly the Python implementation) ...

They look, move and even smell like the kind of furry Everglades marsh rabbit a Burmese python would love to eat. But these bunnies are robots meant to lure the giant invasive snakes out of their ...

Semantic Kernel automatically passes a max_tokens parameter to Azure OpenAI's o3 model, but this parameter has been replaced with max_completion_tokens, causing API calls to fail with Unsupported ...

Electric vehicle giant Tesla Inc (NASDAQ:TSLA) reported second-quarter financial results after market close Wednesday. What Happened: Tesla reported second-quarter revenue of $22.5 billion, down 12% ...

This study presents a novel and efficient approach to accurately assess post-sowing rice plant density by leveraging unmanned aerial vehicles (UAVs) equipped with high-resolution RGB cameras. In ...

NVIDIA introduces cuda.cccl, bridging the gap for Python developers by providing essential building blocks for CUDA kernel fusion, enhancing performance across GPU architectures. NVIDIA has unveiled a ...

Purpose: This study introduces two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel tool for visualising Training Intensity Distribution (TID) in biathlon. The goal was to assess how ...

Abstract: Spectral unmixing is an important technique in remote sensing for analyzing hyperspectral images to identify endmembers and estimate fractional abundance maps. Over the past few decades, ...