Morningstar

Xaira Therapeutics Launches X-Cell, Its First Virtual Cell Model, Trained on the Largest-Ever Genome-Wide Perturbation Dataset, X-Atlas/Pisces

State-of-the-art AI model accurately predicting unseen biological experiments X-Cell is trained on X-Atlas/Pisces, the largest and most context-diverse genome-wide perturbation dataset ever reported ...
TechCrunch

Google is using old news reports and AI to predict flash floods

Flash floods are among the deadliest weather events in the world, killing more than 5,000 people each year. They’re also among the most difficult to predict. But Google thinks it has cracked that ...
Reuters

Exclusive: China's DeepSeek trained AI model on Nvidia's best chip despite US ban, official says

WASHINGTON, Feb 23 (Reuters) - Chinese AI startup DeepSeek's latest AI model, set to be released as soon as next week, was trained on Nvidia's (NVDA.O), opens new tab most advanced AI chip, the ...
TechCrunch

Sam Altman would like to remind you that humans use a lot of energy, too

OpenAI CEO Sam Altman addressed concerns about AI’s environmental impact this week while speaking at an event hosted by The Indian Express. For one thing, Altman — who was in India for a major AI ...
The White House

Fact Sheet: President Donald J. Trump Imposes a Temporary Import Duty to Address Fundamental International Payment Problems

PROTECTING THE U.S. ECONOMY AND NATIONAL INTERESTS: Today, President Donald J. Trump signed a Proclamation imposing a temporary import duty to address fundamental international payments problems and ...
marktechpost

A Coding Implementation to Build Bulletproof Agentic Workflows with PydanticAI Using Strict Schemas, Tool Injection, and Model-Agnostic Execution

In this tutorial, we build a production-ready agentic workflow that prioritizes reliability over best-effort generation by enforcing strict, typed outputs at every step. We use PydanticAI to define ...
GitHub

Hierarchical Deep Temporal Models for Group Activity Recognition

A PyTorch implementation of "Hierarchical Deep Temporal Models for Group Activity Recognition" (CVPR 2016). This repository reproduces and extends the baselines described in the paper and provides ...
IEEE

Development of a Long Short-Term Memory (LSTM)-Based Statistical Model for Earthquake Forecasting in Central Asia

Abstract: Earthquake forecasting using traditional methods remains a complex task due to the inherent nonlinearity and stochastic nature of seismic activity. Therefore, this study examines the ...
marktechpost

A Coding Implementation to Establish Rigorous Prompt Versioning and Regression Testing Workflows for Large Language Models using MLflow

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline ...
IEEE

Proficient Breast Cancer Prediction using an Optimized CNN-LSTM Model: A Hybrid Approach for Improved Diagnostic Accuracy

Abstract: Breast cancer is still the very communal and fatal diseases that women throughout the globe suffer from. Timely and accurate finding through medical imaging especially ultrasound is crucial ...
The New York Times

This A.I. Tool Is Going Viral. Five Ways People Are Using It.

Claude Code generates computer code when people type prompts, so those with no coding experience can create their own programs and apps. By Natallie Rocha Reporting from San Francisco Claude Code, an ...