The ability to reason and draw inferences from natural language is a crucial component of intelligence. According to recent research findings, large language models (LLMs) struggle with complex reasoning tasks (Six Brave Apple Researchers Demonstrate that LLMs don’t Reason) particularly multi-hop reasoning. This involves synthesizing information from multiple sources to arrive at an answer, as well as generating explanations for those answers — a critical aspect of explainability.

Artificial Intelligence (AI) is transforming every facet of our world, from how we communicate to how we work, create, and solve complex problems. While Generative AI (GenAI) – machines that can create text, images, or even music –, has captured much of the recent attention, AI is much more than that. It’s a vast, evolving field filled with both foundational and cutting– edge innovations that are shaping industries, enhancing decision– making, and solving global challenges.

Artificial Intelligence (AI) is not new, and yet is much older than we think.
Humanity has been busy building machines that help us automate work, to do things faster and better, more effortlessly, for millennia.

Former Google researcher Geoffrey Hinton and alongside U.S. scientist John Hopfield received the Physics Prize for their foundational work in Machine Learning. Demis Hassabis – co-founder of Google’s AI unit DeepMind – and colleague John Jumper won the Chemistry Prize for their AlphaFold project, which revolutionized protein structure prediction.