To flexibly and robustly handle diverse problems, AI systems can leverage dual-process theories of human cognition that ...

The strength of certain neural connections can predict how well someone can learn math, and mildly electrically stimulating ...

The reason for this approach is simple: to develop a robust way of algorithmic thinking. When students can think critically about a problem, decompose it, and explain how an algorithm would solve it, ...

Plastic is a product that is ubiquitous in today's society, says Sarah Morath, Wake Forest professor of law and author of the book "Our Plastic Problem and How to Solve It." ...

To make this tangible, I've developed a seven-step problem-solving process, using the word "PROBLEM" as a guide. Each letter represents a fundamental step that organizations and leaders can take ...

Hands on How much can reinforcement learning - and a bit of extra verification - improve large language models, aka LLMs? Alibaba's Qwen team aims to find out with its latest release, QwQ. Despite ...

What else to know about debt management A debt management plan can be a smart option to consider but it is not a solution for every situation — and it's essential to understand the pros and cons ...

According to New Scientist, Williams’ model represented any computation problem, and once he applied this new tree evaluation algorithm, it demonstrated a drastic reduction in required memory.

This paper addresses the following problem: Given a process model and an event log containing trace prefixes of ongoing cases of a process, map each case to its corresponding state (i.e., marking) in ...

Unlike classical algorithms, quantum algorithms can solve specific problems exponentially faster, but their development is a complex and resource-intensive process.