I don't think the statement reads that the 44% and the 26% should be additive. Especially given the zombie graphic where it looks like they overlap the 26 on top of the 44, where the orange bar is the 26% and the remaining yellow bar is the 44%
I'm impressed you were able to not get tangled up by the youtube/captcha/color hex/roman numeral mess! The youtube one is what screwed me over and over out of all my attempts
Google that, including the quotes, replace the minutes and seconds with your given time, then look through the results and find a URL which fits the password criteria.
Every result should be a video with that duration. If it isn't, check your useragent. I noticed some weirdness with that.
I don't think it's easy. Verification is much easier than generating correct solutions for this.
Looking at the JS, these rules use RNG such that you can have an inconsistent or impossible password. E.g. if the only youtube video URLs that work with your duration have roman numerals that multiply above 35 in it you are hard stuck. Your youtube URL can also hard stuck your atomic number summation to 200 if it happens to contain enough elements that adds above 200. Your color hex can hard stuck your 25 sum, etc. The code does not try to generate working passwords given all the rules, it simply adds checks and randomly generates the requirement per rule.
You'd have to have the RNG rules to align well in order to win i.e. youtube video with no roman numerals or numbers or elements, captcha with no numbers or roman numerals or elements, to minimize conflict.
For a given video length, there will be some youtube video urls without roman numerals, and with low digit sum, and atomic number.
I first search this on Google
"0:00 / mm:ss" site:youtube.com
Where mm:ss is the desired length. Then I used some Javascript to scrape the results, finding only youtube urls without roman numbers, and print them out sorted by digit sum and atomic number
I've done it a few times, never had a situation where there was no suitable url
As for the color hex, if it's not suitable, you can regenerate it
I wonder if something like quickcheck could be used to randomly generate characters which pass the criteria. I don't know how it would handle Paul though...
I uploaded a video quick just to pass that step since the length was hard to find. The generated video ID was a bunch of Roman numerals so I was totally fucked.
Her field has also taken the largest hit from the success of LLMs and her research topics and her department are probably no longer prioritized by research grants. Given how many articles she's written that have criticized LLMs it's not surprising she has incentives.
LLMs are in her field; they are one of her research topics and they're definitely getting funding.
We absolutely should not be ignoring research that doesn't support popular narratives; dismissing her work because it is critical of LLMs is not reasonable.
In her field doesn't mean that's what she researches, LLMs are loosely in her field but the methods are completely different. Computational linguistics != deep learning. Deep learning does not directly use concepts from linguistics, semantics, grammars or grammar engineering, which is what Emily was researcing for the past decades.
It's the same thing as saying a number theorist and a set theorist are in the same field cause they both work in the Math field.
They are what she researches though. She has published research on them.
LLMs don't directly use concepts from linguistics but they do produce and model language/grammar; it's entirely valid to use techniques from those fields to evaluate them, which is what she does. In the same vein, though a self-driving car doesn't work the same way as a human driver does, we can measure their performance on similar tasks.
Hmm I looked into it, and looked at papers/pdfs in google scholar's advanced search with her as an author that mentioned LLMs or GPT in the past 3 years. Every single one was a criticism about how they couldn't actually understand anything (e.g. "they're only trained on form" and "at best they can only understand things in a limited well scoped fashion") and that linguistic fundamentals for NLP was more important.
Current topic aside, I feel like that stochastic parrots paper aged really poorly in its criticisms of LLMs, and reading it felt like political propaganda with its exaggerated rhetoric and its anemic amount of scientific substance e.g.
> Text generated by an LM is not grounded in communicative
intent, any model of the world, or any model of the reader’s state
of mind. It can’t have been, because the training data never included sharing thoughts with a listener, nor does the machine have
the ability to do that.
I'm surprised its cited so much given how many of its claims fell flat 1.5 years later
It's extremely easy to publish in NLP right now. 20-30% acceptance rates at even the top end conferences and plenty of tricks to increase your chances. Just because someone is first author on a highly cited paper doesn't imply that they're "right"
It's trained on pre-2021 data. Looks like they tested on the most recent tests (i.e. 2022-2023) or practice exams. But yeah standardized tests are heavily weighed towards pattern matching, which is what GPT-4 is good at, as shown by its failure at the hindsight neglect inverse-scaling problem.
I believe they showed that in GPT4 reversed the trend on the hindsight neglect problem. Search for "hindsight neglect" in the website and you can see that it's accuracy on the problem shot up to 100%.
For Vietnamese, ChatGPT has been much more effective for me. You can tell it very specific things to modify as well as give it additional context which you can't really do with Google Translate. Especially with pronouns, google will just translate everyone as 'uncle' or 'aunt' or 'grandma' or 'grandpa' and it'll get genders wrong all the time, which you can correct for with ChatGPT.
