Artificial Intelligence may possibly be the single most misunderstood concept in contemporary data management. Most organizations are unclear about the relationship of AI to machine learning (they’re ...

As AI systems have advanced rapidly, with large language models (LLMs) at the center, every tech executive has experienced their limits—when AI systems struggle with complex problem-solving, produce ...

Neuro-symbolic AI is a unique form of artificial intelligence that combines the strengths of neural and symbolic AI architectures. This powerful AI model can model cognition, learning, and reason, ...

The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...

Ziwei Zhu, Assistant Professor, Computer Science, College of Engineering and Computing (CEC), received funding for the project: “III: Small: Harnessing Interpretable Neuro-Symbolic Learning for ...

In a breakthrough for artificial intelligence (AI) and finance, computer scientists from Texas A&M University have developed a machine learning based method called Symbolic Modeling to handle ...