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by shybear9 hours ago |
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upvoteby esjeon7 hours ago|
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Exactly. Much of the intellectual work is, in fact, intellectual labor. It’s mostly about combining various information in one place — the exact task that LLM far outperforms human. People traditionally misclassified this class of work as “creative”. It’s not really.
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upvoteby Jtarii5 hours ago|
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Having a new insight that leads to the combination of two distinct ideas is definitionally creative.

You can say this problem needed a low amount of total creativity, but saying it's void of all creativity seems wrong.

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upvoteby Ekaros1 hours ago|
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Creative bit is figuring out two or more bits that might work together for something new. Labour part is combining that especially if it is actually laborious.

Which get to other possibility of having list of distinct things and then iterating over all pairs or combinations. Which I probably would not qualify as "creative" work.

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upvoteby versteegen5 hours ago|
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I agree except: this is creative work. Creativity can be and is being mechanised. True originality is extremely rare. Most novelty is the repurposing of one idea or concept elsewhere in a way we call find surprising, but the choice to apply A to B could have been made for any reason including mechanical: very many inventions are accidents. In-depth knowledge / conceptual understanding of something is built on abstraction, and abstractions are portable.

If you had a list of N concepts and M ways to apply them you could try all N*M combinations, and get some very interesting results. For a real example, see the theory of inventive problem solving (TRIZ)'s amusing "40 principles of invention" by Soviet inventor Genrich Altshuller. https://en.wikipedia.org/wiki/TRIZ

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upvoteby _Microft6 hours ago|
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What is your idea of "creative"/"creativity" then?
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upvoteby moffkalast5 hours ago|
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Coming up with said novel techniques in the first place. Arguably something that most humans can't really do reliably or at all.
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upvoteby jvln2 hours ago|
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I always thought that way about genius level.
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upvoteby adampunk1 hours ago|
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Novelty is overrated in mathematics by those outside mathematics. We desperately need lots of less novel things in math right now.
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upvoteby wonger_1 hours ago|
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Yeah, I've been grappling with the definition of creativity too. There's a gamedev talk [0] on creativity that gave me useful perspective. Here's what I wrote elsewhere:

---

i've been thinking about raph's definition of creativity [0]: permuting one set of ideas with another set of ideas

(or trying an idea in new contexts)

this is a systematic process, doable even by machine once enough pattern libraries have been catalogued.

on a small scale, there's sprint.cards [1] or oblique strats [2]. on a large scale, there's llms...

it's freeing to approach creativity as a deliberate practice rather than waiting on some fickle muse. yet it's a bit disappointing to see idea generation so mechanical and dehumanized.

i am comforted by the value of mushy human abilities surrounding the creative process:

mostly 1) taste, the ability to recognize pleasing output,

...

[0] https://www.youtube.com/watch?v=zyVTxGpEO30

[1] https://sprint.cards/

[2] https://stoney.sb.org/eno/oblique.html

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upvoteby dorgo6 hours ago|
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Maybe all intellectual work is intellectual labor?
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upvoteby raincole5 hours ago|
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This is exactly what creativity is.
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upvoteby locknitpicker6 hours ago|
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> Much of the intellectual work is, in fact, intellectual labor.

That's a great point. It's in line with research being carried on the backs of graduate students, whose work is to hyperfocus on areas.

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upvoteby gardenhedge7 hours ago|
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Isn't that science too?
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upvoteby hansmayer5 hours ago|
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> Much of the intellectual work is, in fact, intellectual labor.

Not surprisimg, because the two words you used are synonyms. Who did ever classify mathematical work as creative? Kids in third grade math class?

> that LLM far outperforms human.

LLMs only outperform humans in creating loads of bullshit. 6 years in and they remain shiny toys for easily impressionable idiots.

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upvoteby squidbeak2 hours ago|
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As I understand it, models form connections (weak or strong) between everything in their training sets, even the smallest details. They've already made other breakthroughs directly because of this ability and this line of research is likely to be incredibly fruitful.
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upvoteby freakynit9 hours ago|
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This is what I personally consider as "reasoning" ... knowledge generalization and application across domains.
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upvoteby jdub8 hours ago|
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Less reasoning than a dimension of brute force unfamiliar to human brains.
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upvoteby squidbeak3 hours ago|
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Trying to diminish this as brute force (something by the way that is categorically not 'unfamiliar to human brains' - as anyone who has every worked on complex slippery problems will tell you) is foolish, when the models hypothesize along the way to their solutions. That's reasoning.
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upvoteby worldsavior7 hours ago|
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Familiar but isn't effective enough for surviving.
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upvoteby renticulous1 hours ago|
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> someone applying technique X from one field to problem Y in another

Witten is the canonical example of someone taking mathematics techniques and applying them to physics problems, but what made him legendary was the opposite direction: he used physical intuition and string theory to solve open problems in pure mathematics.

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upvoteby bojo9 hours ago|
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This is what I have been doing. I don't think I've made any amazing breakthroughs, but at the same time I can't help but feel like I've come across some white paper-worthy realizations. Being able to correlate across a lot of domains I feel like I intuitively understand but have no depth of knowledge has been a fun exercise in LLM experimentation.
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upvoteby some_furry8 hours ago|
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> It seems like alot of scientific advancements occurred by someone applying technique X from one field to problem Y in another.

Yeah, you should look into the Langlands project sometime

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upvoteby pfdietz3 hours ago|
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I'm thinking once we have much of the math literature formalized it's going to be possible to mine commonalities like that. Think of it as automated refactoring, applied to math.
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upvoteby trhway7 hours ago|
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As a civilization we went the left-brained/sequential/language based way of thinking (with computers and AI being the crown achievement of it). Personally i for example remember like around 3rd grade i switched from the whole-page-at-once reading mode into the word by word line by line mode and that mode stuck with me since then (at some point while at the University i had for some period of time, probably it was the peak of my abilities, some more deep/wide/non-linear perception into at least my area of math specialization, though not sure whether it was a mastery by the left brain or the right brain got plugged in too) LLMs will definitely beat us in that sequential way of thinking. That makes me wonder whether we will have to push into our whatever is still left there right-brainness, and whether AI will get there faster too. May be we'll abandon the left-brain completely leaving it to AI.
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upvoteby kbrkbr6 hours ago|
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If that is your hope you are probably in for a rude awakening. Left brained/right brained is a wooden exaggeration according to more recent research [1].

[1] e.g. https://www.sciencenewstoday.org/left-brain-vs-right-brain-t...

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upvoteby chrisweekly2 hours ago|
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Well, maybe. The poster you replied to wasn't discussing literal neuroanatomy, they were using "left/right-brained" in the colloquial, metaphorical sense.
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upvoteby pelasaco4 hours ago|
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accuracy and creativity are often quite difficult to achieve at the same time. Looks like LLM can do it, even though one can question how creative it really is...
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upvoteby squidbeak3 hours ago|
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Can one? It's surpassed the creativity of humans in this one problem at least.
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upvoteby pelasaco15 minutes ago|
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i agree with you, but apparently some people do it
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upvoteby aaron6952 hours ago|
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[dead]
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