The development of Physical AI—AI systems designed to simulate, predict, and optimize real-world physics—has long been constrained by significant challenges. Building accurate models often demands ...

When it comes to AI tools, chatbots are often the first thing that comes to mind —conversation-based interfaces for users to write queries and receive responses. These dialogue interfaces are ...

In a time when global health faces persistent threats from emerging pandemics, the need for advanced biosurveillance and pathogen detection systems is increasingly evident. Traditional genomic ...

Protein docking, the process of predicting the structure of protein-protein complexes, remains a complex challenge in computational biology. While advances like AlphaFold have transformed ...

Social media platforms have revolutionized human interaction, creating dynamic environments where millions of users exchange information, form communities, and influence one another. These platforms, ...

Social media platforms have revolutionized human interaction, creating dynamic environments where millions of users exchange information, form communities, and influence one another. These platforms, ...

Protein docking, the process of predicting the structure of protein-protein complexes, remains a complex challenge in computational biology. While advances like AlphaFold have transformed ...

The semiconductor industry enables advancements in consumer electronics, automotive systems, and cutting-edge computing technologies. The production of semiconductors involves sophisticated processes ...

Artificial intelligence (AI) has made significant strides in developing language models capable of solving complex problems. However, applying these models to real-world scientific challenges remains ...

The semiconductor industry enables advancements in consumer electronics, automotive systems, and cutting-edge computing technologies. The production of semiconductors involves sophisticated processes ...

Machine unlearning is driven by the need for data autonomy, allowing individuals to request the removal of their data’s influence on machine learning models. This field complements data privacy ...

Large language models (LLMs) built using transformer architectures heavily depend on pre-training with large-scale data to predict sequential tokens. This complex and resource-intensive process ...