ChatGPT’s Coding Conundrums: Can AI Really Answer Your Programming Questions?

Remember when the internet collectively freaked out about AI that could write poems and compose emails? That was just the tip of the iceberg, my friends. We’re talking about Large Language Models (LLMs) like ChatGPT, those digital brainiacs that seem poised to revolutionize…well, everything.

But hold on a sec. Before we hand over the keys to the coding kingdom, let’s talk about accuracy. Sure, LLMs are great at spitting out human-like text, but can they actually solve complex programming problems? A new study from Purdue University suggests we might wanna pump the brakes on the AI hype train.

This ain’t just some abstract academic debate either. We’re talking about the tools students and professionals use every day to learn, troubleshoot, and build the digital world. If these tools are spitting out bogus info, it’s kinda a big deal.

Putting ChatGPT to the Test: A Deep Dive into the Research

So, how did the brainy folks at Purdue decide to put ChatGPT through its paces? They didn’t mess around, that’s for sure. They hit up StackOverflow, the go-to website for programming Q&A, and pulled a whopping collection of programming questions.

Next, they fed these questions to two different flavors of ChatGPT: the free version, GPT-three-point-five, and its turbocharged cousin, GPT-three-point-five-turbo (because who doesn’t love a good API?). Think of it like a digital bake-off, with code instead of cookies.

The researchers weren’t just looking for right or wrong answers, though. They wanted to know how ChatGPT’s responses stacked up against those of human experts. Were they clear? Concise? Did they make sense? (Sometimes, even human programmers struggle with that last one.)

ChatGPT’s Report Card: Not Quite Passing with Flying Colors

Okay, time to spill the tea. Did ChatGPT ace the test? Not exactly. In fact, the results were a little, shall we say, concerning.

Turns out, ChatGPT (the free version) only managed to crank out correct answers a little over half the time. Yikes. That’s like trying to build a house on a foundation of sand.

And it gets even wilder. Remember how I said they were looking at clarity and conciseness? Well, ChatGPT seemed to have a bit of a verbosity problem. Its answers were often way longer and more complicated than they needed to be, kinda like that one friend who turns a simple story into a Shakespearean drama.