Knowledge representation and reasoning in logic programming constitute a core area of artificial intelligence that formalises how information is symbolically encoded and manipulated. This field ...

What actually exists? How do computers think about reality? Where does the meaning of a word come from, and how do computers learn to understand it? Do computers really “understand” language at all?

A new perspective on the future development of artificial intelligence (AI) has been put forward by researchers Li Guo and Jinghai Li in their article titled “The Development of Artificial ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

Aravind Srinivas endorsed a post on X by a physics and AI/ML student that argued large language models (LLMs) are automating ...

OpenAI's release of GPT-4.1 for ChatGPT came quietly but represents an impressive upgrade, albeit one focused specifically on logical reasoning and coding. Its enormous context window and grasp of ...

Forbes contributors publish independent expert analyses and insights. I write about innovation, the future of work and remote work. The future of programming and AI is more nuanced than headlines ...

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 ...

Researchers at Stanford and Caltech have found some critical reasoning failures in advanced AI models. LLMs are great at recognizing patterns, but they have trouble with basic logic, social reasoning, ...