Technology

37720 readers

277 users here now

A nice place to discuss rumors, happenings, innovations, and challenges in the technology sphere. We also welcome discussions on the intersections of technology and society. If it’s technological news or discussion of technology, it probably belongs here.

Remember the overriding ethos on Beehaw: Be(e) Nice. Each user you encounter here is a person, and should be treated with kindness (even if they’re wrong, or use a Linux distro you don’t like). Personal attacks will not be tolerated.

Subcommunities on Beehaw:

This community's icon was made by Aaron Schneider, under the CC-BY-NC-SA 4.0 license.

founded 2 years ago

MODERATORS

alyaza@beehaw.org

TheRtRevKaiser@beehaw.org

gyrfalcon@beehaw.org

rs5th@beehaw.org

SemioticStandard@beehaw.org

TheRtRevKaiser@kbin.social

Los@beehaw.org

coldredlight@beehaw.org

remington@beehaw.org

141

[Fortune] Over just a few months, ChatGPT went from correctly answering a simple math problem 98% of the time to just 2%, study finds (archive.ph)

submitted 1 year ago* (last edited 1 year ago) by trashhalo@beehaw.org to c/technology@beehaw.org

51 comments fedilink hide all child comments

Researchers found that ChatGPT's performance varied significantly over time, showing "wild fluctuations" in its ability to solve math problems, answer questions, generate code, and do visual reasoning between March and June 2022. In particular, ChatGPT's accuracy in solving math problems dropped drastically from over 97% in March to just 2.4% in June for one test. ChatGPT also stopped explaining its reasoning for answers and responses over time, making it less transparent. While ChatGPT became "safer" by avoiding engaging with sensitive questions, researchers note that providing less rationale limits understanding of how the AI works. The study highlights the need to continuously monitor large language models to catch performance drifts over time.

you are viewing a single comment's thread
view the rest of the comments

[–] PeepinGoodArgs@reddthat.com 1 points 1 year ago (1 children)

Oh boy. I do research on it for various things. Florida released some laws changing alimony and I researched it via Perplexity to understand what the problem was. It worked. I understood the issue.

Or carbon capture technology.

In any case, I do look directly at the sources. Perplexity.ai is useful for framing a topic, getting the gist of it, but for being sure I know wtf is going on, I personally need to look at the sources.

[–] Very_Bad_Janet@kbin.social 2 points 1 year ago* (last edited 1 year ago) (1 children)

Thanks for this reply. That's probably the best way to use LLMs - general definitions or framing / summarizing of issues. And then always check the sources to make sure it was accurate. I've played around with ChatGPT and Bard and I think my mistake has been to be a little too granular or specific in my prompts. In most cases it produced results that were inaccurate (ETA: or flat out demonstrably wrong) or only fulfilled a part of the prompt.

[–] PeepinGoodArgs@reddthat.com 1 points 1 year ago

the best way to use LLMs - general definitions or framing / summarizing of issues. And then always check the sources to make sure it was accurate.

I agree. The criticism that they're not accurate kinda misses the point of LLMs being tools. It'd be like complaining that a hammer doesn't jam the nail in all the way after the first stroke. Hit it again...and maybe try hitting it straight this time instead of at an angle. It's an iterative process that can be self-correcting when done thoughtfully.