Artificial intelligence is rapidly changing our world, with large language models (LLMs) leading the charge. These models are masters of language, able to understand and generate text that sounds remarkably human. But, just like a human who excels in one area might struggle in another, AI models have their limitations.
We’ve discussed how humans develop skills through a combination of theory and practice, learning from trial and error. This process creates “heuristics,” mental shortcuts that allow us to solve problems efficiently. It’s the same with AI. We can’t expect a language model to drive a car or perform tasks it hasn’t been specifically trained for. They lack the practical experience needed to develop those crucial heuristics.
Imagine watching a master chef create a complex dish. They make it look effortless! But that’s because they’ve spent years honing their skills, developing those culinary heuristics. An AI might read all the cookbooks in the world, but it won’t be able to replicate that chef’s expertise without hands-on experience.
This isn’t about AI being weak; it’s about understanding its nature. Each AI is trained for a specific purpose, and we need to respect those boundaries. When we do, we can unlock AI’s true potential. For example, using a language model to help write an article is a perfect application of its strengths.
In conclusion, AI is a powerful tool, but it’s not a one-size-fits-all solution. We need to move beyond simply marveling at its language abilities and start exploring how to create AI that can learn and excel in other areas. This will require dedicated training, a focus on developing heuristics, and a willingness to embrace the learning process, just like humans do.
