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, ...

Forbes contributors publish independent expert analyses and insights. I write on the intersection of artificial intelligence, international law and finance. May 31, 2024, 07:15am EDT May 31, 2024, ...

Education is on the cusp of transformative era, driven by the integration of artificial intelligence (AI) and, in particular, large language models (LLMs). These powerful tools hold immense potential ...

Neuro-symbolic AI — combining data-driven learning with rule-based reasoning — could accelerate safe, transparent use of autonomous equipment on complex jobsites.

The 2026 Machine Learning Revolution: From Generative Chatbots to Autonomous Reasoning Agents The first quarter of 2026 has marked a ...

Inductive logic programming (ILP) and machine learning together represent a powerful synthesis of symbolic reasoning and statistical inference. ILP focuses on deriving interpretable logic rules from ...

In law school, grades are often viewed as predictors of future success: A students become law professors, B students become judges and C students become millionaires. But the adage may need updating.

Franz Inc. expands graph, vector, and Neuro-Symbolic capabilities for enterprise-scale AI systems LAFAYETTE, CA, UNITED ...

Power usage by AI and data center systems in the U.S. is extraordinary by any measure. The International Energy Agency ...

Soft Computing (SC) is an Artificial Intelligence (AI) approach that is more effective at solving real-life problems than traditional computing models. Soft Computing models are tolerant of partial ...