Artificial intelligence (AI) is getting smarter, but there are still problems. One type of AI, called neural networks, is really good at learning patterns from lots of examples, but it can sometimes make things up or be hard to understand. Another type, called symbolic AI, uses rules and logic, but it can be slow. To solve these problems, people are combining the two types into neurosymbolic AI. This combines the strengths of both types of AI to create a more reliable and explainable system. Some companies, like LG, are using neurosymbolic AI to improve their AI agents. Some experts think neurosymbolic AI is the key to achieving artificial general intelligence (AGI), which is a type of AI that can think like a human. However, there are still challenges, such as making neurosymbolic AI faster and easier to scale.