An international team led by Einstein Professor Cecilia Clementi in the Department of Physics at Freie Universität Berlin has ...

A new study led by Freie Universität Berlin physicist and recently published in Nature Chemistry opens up, among other things ...

Who needs rewrites? This metadata-powered architecture fuses AI and ETL so smoothly, it turns pipelines into self-evolving ...

Complex model architectures, demanding runtime computations, and transformer-specific operations introduce unique challenges.

Just as people from different countries speak different languages, AI models also create various internal "languages"—a ...

The artificial intelligence community has long struggled with a fundamental challenge of making AI systems transparent and ...

Equipped with tools such as Python, NumPy, TensorFlow, PyTorch, spaCy and Hugging Face, learners engage in guided tutorials ...

Scikit-learn, PyTorch, and TensorFlow remain core tools for structured data and deep learning tasks.New libraries like JAX, ...

The widespread adoption of Transformers in deep learning, serving as the core framework for numerous large-scale language models, has sparked significant interest in understanding their underlying ...

This work adopts a CsPbI 3 and Ge-doped system as the research object, combines density functional theory with nonadiabatic molecular dynamics (NAMD), uses Hammes-Schiffer–Tully (HST) and ...

Deep reinforcement learning (RL) typically requires a tremendous number of training samples, which are not practical in many applications. State abstraction and world models are two promising ...