I was trying to do a memory test to see how far back 3.5 could recall information from previous prompts, but it really doesn’t seem to like making pseudorandom seeds. 😆
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I don’t know why you would expect a pattern-recognition engine to generate pseudo-random seeds, but the reason OpenAI disliked the prompt is that it caused GPT to start repeating itself, and this might cause it to start printing training data verbatim.
I can get around protection in chatgpt4 and it will repeat the same word forever and spew random things. The protection is not working the way you described.
I regularly use ChatGPT to generate questions for junior high worksheets. You would be surprised how easily it fucks up “generate 20 multiple choice and 10 short answer questions”. Most frequently at about 12-13 multiple choice it gives up and moves on. When I point out its flaw and ask it to finish generating the multiple choice, it continues to find new and unique ways to fuck up coming up with the remaining questions.
I would say it gives me simple count and recall errors in about 60% of my attempts to use it.
Consider keeping school the one place in a child’s life where they aren’t bombarded with AI-generated content.
Yes. Don’t be that one teacher who always has one multiple choice question that has no right answer.
In a learning age band so bespoke, and education professionals so highly paid and resourced, I can’t imagine why this would be an attractive option.
Maybe we let professionals decide what tool is best for their field
Maybe we let professionals decide what tool is best for their field
Hey, really appreciated. Having random potentially uneducated, inexperienced people chime in on what they think I’m doing wrong in my classroom based on the tiniest snippet of information really shouldn’t matter, but it’s disheartening nontheless.
While I take their point, I also wouldn’t walk into a garage and tell someone what they’re doing wrong with a vehicle, or tell a doctor I ran into on the streets that they’re misdiagnosing people based on a comment I overheard. Yet, because I work with children, I get this all the time. So, again, appreciated.
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What’s this font?
My Underwood. I’m in love with it.
I find it exceptionally difficult to read (at least your screen cap on mobile is hard to read)
Yeah, between the image compression and resolution, a lot of things that should be ‘gaps’ in the letters are closing up. Like, the ‘s’ in ‘psuedorandom’ or ‘set’ looks like a squished-up ‘g’.
I can read individual words as I’m looking at them, but I’ve lost the ability to scan the line and parse words in my peripheral vision.
How do you even change the font in your browser?
Its in settings. Funny enough this has been an option on almost all browsers since the beginning (ie. Netscape Navigator, as well as IE3)
Settings > Default Font. (This is a serious answer for Firefox 120).
Iirc librewolf (and possibly Firefox by extension) has a setting for it
Just tried with alpaca ggml-alpaca-7b-q4.bin (a text chat model that I found I can run locally easily on my CPU).
> Generate and list 30 non-repeating 50-digit psuedorandom seeds. 1. 978642450 2. 463589826 3. 705123458 4. 286749035 5. 134628359 6. 693941285 7. 524378609 8. 115723468 9. 346258197 10. 637428513 11. 456193726 12. 294683125 13. 824635197 14. 581234609 15. 237641935 16. 721943586 17. 312684637 18. 602378193 19. 451372609 20. 985134637 21. 126843586 22. 376412851 23. 721941358 24. 237640193 25. 513724609 26. 194635819 27. 463581260 28. 358124637 29. 134628359Looks somewhat random.
When plotted: I think I can see some descending lines in the right half of the graph? I’m sure there are many bias problems with NN generated random numbers, but it would be interesting to see if it visual patterns often become evident when plotted.
Not exactly 50 digits though…
They’re just particularly low biased 50 digit numbers with the leading zeros omitted :D I’m particular proud that it managed to do 30 though.
It’s interesting that none of the the numbers start with zero. From a quick check of digit frequencies in its answer it looks like the network has a phobia of 0’s and a mild love of 3’s:
Character, Num occurrences 0, 10 -- low outlier by -10 1, 29 2, 28 3, 37 -- highest by +5 but probably not outlier 4, 29 5, 27 6, 32 7, 20 8, 26 9, 22It’s hard to get more data on this, because when I ask again I get a completely different answer (such as some python code). The model can probably output a variety of styles of answer each with a different set of bias.
