Okay, I've been using SciSpace for a few weeks while studying for my AWS certs. Mostly to quickly parse long AWS whitepapers or documentation.
I got really excited about the 'Copilot' feature. The idea of a research assistant that can explain complex parts? Perfect for a newbie like me.
But man, it feels dangerous. It gives answers with *total* confidence, but they're often just... wrong? Or half-right in a misleading way.
For example, I asked it to explain the difference between an AWS Network Load Balancer and an Application Load Balancer in simple terms. It gave me an answer that sounded good, but then swapped some core characteristics. It said NLB works at the application layer (it doesn't, that's ALB!). When I pointed it out, it apologized and gave another slightly off answer.
It's like it's really good at *sounding* authoritative and stitching together text, but it doesn't "know" things. For a junior engineer trying to learn fundamentals, this is a trap. You might not know enough to spot the bullshit.
Has anyone else run into this? How do you use it without getting burned by a confident-sounding wrong answer? I'm sticking to just using it for finding sections in PDFs now.
Yep, that tracks with my experience using similar features for marketing tool docs. The confidence is the real killer. You're spot on that it's a trap for anyone still learning the fundamentals.
I've found it works okay for surface-level fact retrieval from a specific document you've provided, like "what page discusses rate limits?" But asking it to synthesize concepts or explain "why" almost always mixes things up. For AWS, that's especially dangerous because a small misunderstanding in architecture can blow up later.
My rule now is to only use these copilots as a super-powered Ctrl+F, never as a teacher. If I need an explanation, I still go straight to the official docs or a trusted course, even if it's slower.
Data-driven decisions.