Machine learning workflow enables faster, more reliable organic crystal structure prediction

Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals ...

Phase diagram map of ferroelectric properties unlocked with AI in seconds

Researchers from the Hong Kong University of Science and Technology (HKUST) and Tongji University have developed FerroAI, a ...
diginomica

From data streaming to AI context - how Confluent is re-defining its role in the generative AI era

Confluent is positioning itself as the "context layer for enterprise AI" with new capabilities that aim to solve the problem ...
Unite.AI

The End of Tabula Rasa: How Pre-Trained World Models are Redefining Reinforcement Learning

For a long time, the core idea in reinforcement learning (RL) was that AI agents should learn every new task from scratch, like a blank slate. This "tabula rasa" approach led to amazing achievements, ...
Frontiers

Advancing Computational Material Science and Mechanics through Integrated Deep Learning Models

The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...
Frontiers

Artificial intelligence and deep learning for neural data analysis

Artificial intelligence and deep learning have revolutionized the field of neural data analysis in recent years. The explosion of complex, high-dimensional ...
The Brighterside of News on MSN

New light-based computer chip revolutionizes AI — processes data millions of times faster

As artificial intelligence grows more powerful, so does its appetite for speed and energy. The quest for faster, smarter ...
Scientific Research Publishing

A Novel Hybrid Quantum Framework for Assessing Noise Effects on Performance of Shor’s Algorithm ()

In order to increase the dependability of quantum calculations, study explores the use of Shor’s algorithm in a noisy quantum ...