As a developer, I’m sure you’ve been there – stuck in a sea of data, trying to collect and analyze it for your project. Writing scripts and parsers to do this can be a real pain, especially when you need to consider exceptions, errors, and folder structures. But what if I told you there’s a way to make this process easier?
Enter ‘vibe data gathering,’ where you can ask a Large Language Model (LLM) like ChatGPT to write a script for you. Imagine being able to ask it to open thousands of files, parse them for specific information, and even draw a graph for you. The possibilities are endless.
The problem is, ChatGPT needs to know the folder structure and examine the files to identify potential issues. But what if you could avoid all that hassle? Is there a way to create a generative AI shell interface that can browse and process data for you, without requiring you to roll up your sleeves?
The idea is intriguing, and it got me thinking – what if we could create a system that can understand our data gathering needs and automate the process for us? It would save us so much time and energy, and let us focus on the actual analysis and insights.
The potential applications are vast, from debugging to collecting production science data. And with the advancements in LLMs, it’s not too far-fetched to imagine a future where we can simply ask a system to gather and analyze data for us.
So, what do you think? Is ‘vibe data gathering’ the future of data analysis? Share your thoughts in the comments!