High-performance computing has become crucial for various businesses, including scientific research and Artificial Intelligence (AI), in today’s data-driven society. By providing strong, scalable, and ...

Artificial intelligence has transformed code generation, with large language models (LLMs) for code now integral to software engineering. These models support code synthesis, debugging, and ...

In today’s world, building robotic policies is difficult. It often requires collecting specific data for each robot, task, and environment, and the learned policies do not generalize beyond these ...

The quantum tunneling (QT) effect discovered in the 1920s was a major achievement in the field of quantum mechanics. Since there is a major fundamental difference between artificial and biological ...

The quest to strengthen national security has faced several challenges over the years, especially as the pace of technological advancement has far outstripped the speed of legislative and bureaucratic ...

Understanding the different forms and future directions of Artificial Intelligence (AI) is becoming increasingly important as it evolves. Artificial Narrow Intelligence (ANI), Artificial General ...

Video generation has rapidly become a focal point in artificial intelligence research, especially in generating temporally consistent, high-fidelity videos. This area involves creating video sequences ...

In the rapidly evolving field of artificial intelligence, the focus often lies on large, complex models requiring immense computational resources. However, many practical use cases call for smaller, ...

A fundamental challenge in studying EEG-to-Text models is ensuring that the models learn from EEG inputs and not just memorize text patterns. In many reports in the literature where great results have ...

In the world of information retrieval, one of the most challenging tasks is to create a system that can seamlessly understand and retrieve relevant content across different formats, such as text and ...

Automatic differentiation has transformed the development of machine learning models by eliminating complex, application-dependent gradient derivations. This transformation helps to calculate Jacobian ...

Tracking dense 3D motion from monocular videos remains challenging, particularly when aiming for pixel-level precision over long sequences. Existing methods face challenges in achieving detailed 3D ...