- Nils@lemmy.caEnglish20 hours
People, please open the article before spouting non-sense. There are some cool images and videos that would make your life a lot easier.
They did not ask chatgpt to convert files like the news a few scrolls up about converting pdf to slideshow.
They are using statistical models to figure out ink from fibre on ancient burned scrolls, from x-ray and CT scan data. Then other techniques to unroll them, so scientists can read and compare with other works.
Pretty much going from this
To this
- Mesophar@pawb.socialEnglish14 hours
This is the sort of stuff I was excited about AI for in the 2010s when development started showing results. Before tech(bro) companies ruined the term.
- mushroommunk@lemmy.todayEnglish23 hours
Getting real tired of everyone calling everything AI these days. Machine learning doesn’t mean AI
23 hoursAs someone in the know i agree, but for the “common folk” out there with a very limited tech background, it’s probably the easiest way to get the point what was used across.
- mushroommunk@lemmy.todayEnglish22 hours
No it’s just straight up lazy and leading people to believe ChatGPT is out there solving archeological problems and is actually valuable. Just call it machine learning and go. Most non tech people won’t care, and they won’t keep having that association reinforced.
You’ve got a point there, i did not take into account that this reinforces the perception of LLMs as something close to AGI (which was pushed heavily by Altman and Amodei).
The other problem is the “um actually the field of ML is a subset of AI” people because, technically machine learning is a subset of the field of artificial intelligence mathematics.
But them acting like that isn’t doing the devil’s dirty work to “um actually” at everyone is absurd.
- phutatorius@lemmy.zipEnglish15 hours
Without over-disclosing: I work in a highly technical field. We’ve done considerable assessment of LLMs and our conclusion so far is that they’re largely useless to us. But since long before the LLM craze, we’ve also been exploring ML applications, and some of those have been yielding interesting results.
Both are flavors of AI. It’s just that one is in a massive hype cycle right now, so correcting unreasonable expectations is a necessity.
- Repple (she/her)@lemmy.worldEnglish15 hours
Language needs to change because it’s completely undecipherable to lay people. I use all sorts of models to great effect in my work. Random forests, LSTMs, SVMs, etc all have tons of great uses. I am pretty anti “AI” as lay people understand it (though the technology is super cool on a technical level)
On the plus side, I can much more easily convince people to use any sort of machine learning models than I used to be able to by calling it AI.
- Womble@piefed.worldEnglish20 hours
I don’t see how using terms correctly is doing “the devils work” if anything its a useful corrective to “chat bots do all the things” to explain to people that AI is an umbrella term that includes many things.
- NeilNuggetstrong@lemmy.worldEnglish16 hours
That’s extremely disrespectful to the researchers who have built and trained the machine learning model. And the process of extracting useful data from a charred scroll. That’s a tremendous undertaking. AI is not just ChatGPT and LLMs.
Why can’t we discuss the Roman Empire in this thread?? Imagine the cool shit hidden in those scrolls
- 23 hours
Not all AI works like LLMs. It doesn’t go into much detail, but similar use of AI in the past has been for converting handwritten samples into a more legible form or separating superimposed letters.
Manually filling in “G__d mor_ing” is doable, but I can see how AI can make that process better. It’s technically just guessing, but so is a person in that scenario and the person will have less data to use to guess from.
- phutatorius@lemmy.zipEnglish15 hours
One cool ML application was examining medieval manuscripts and being able to tell which passages were written by different scribes. That in turn yielded information about how scriptoria were organized, and also showed that some texts (books of hours, religious texts) were assigned to single highly skilled scribes, while other texts (usually more mercantile) were more cheaply done using multiple less-skilled scribes.
There’s also been some interesting work on guessing how to fill in lacunae (gaps in a manuscript due to damage or compounded transcription errors).
It’s technically just guessing, but so is a person in that scenario and the person will have less data to use to guess from.
There are other contextual clues that aid the guessing: in particular, the size of the space where the characters are missing, and sometimes grammatical inflections in surrounding words that imply what kind of word is missing (say, a verb or an adjective). That’s where experienced human experts can often perform well.
