11–20 of 119 posts
Lots of people care. From a coding perspective, proper technical systems already have checks and balances (e.g. test cases) to catch bad code, and is something that's important to have regardless of generative AI usage. From a creative/informational perspective, there are stories every day of hallucinations and the tech companies are correctly dunked on because of it. That's more product management error than AI erro…
Lots of people care. From a coding perspective, proper technical systems already have checks and balances (e.g. test cases) to catch bad code, and is something that's important to have regardless of generative AI usage. From a creative/informational perspective, there are stories every day of hallucinations and the tech companies are correctly dunked on because of it. That's more product management error than AI erro…
Lots of people care. From a coding perspective, proper technical systems already have checks and balances (e.g. test cases) to catch bad code, and is something that's important to have regardless of generative AI usage. From a creative/informational perspective, there are stories every day of hallucinations and the tech companies are correctly dunked on because of it. That's more product management error than AI erro…
The fact that every AI-based company gets dunked-on for hallucination somewhat suggests that hallucination is a showstopper issue and in fact cannot be worked around.
The tide is only turning recently on whether that's a good business tradeoff.
Earlier quoted context omitted.
The fact that every AI-based company gets dunked-on for hallucination somewhat suggests that hallucination is a showstopper issue and in fact cannot be worked around.
A "showstopper" issue is a QA term-of-art indicating an issue that the project cannot be pushed to production as long as it exists. The AI project managers made the calculation that the proportion of hallucination issues (and their consequences) is within acceptable bounds. The tide is only turning recently on whether that's a good business tradeoff.
AI is like that right now. It's only right sometimes. You need to use judgement. Still useful though.
What gets difficult is evaluating the response, but let's not pretend that's any easier to do when interacting with a human. Experts give wrong answers all the time. It's generally other experts who point out wrong answers provided by one of their peers.
My solution? Query multiple LLMs. I'd like to have three so I can establish a quorum on an answer, but I only have two. If they agree then I'm reasonably confident the answer is correct. If they don't agree - well, that's where some digging is required.
To your point, nobody is expecting these systems to be infallible because I think we intuitively understand that nothing knows everything. Wouldn't be surprised if someone wrote a paper on this very topic.
Tolerable Pizza delivery is ruined. The Internet is a walled wasteland now. Far too much "content" that doesn't need to exist. Everything is an ad.
None of our lives have been improved by software.