5 ms·
It's a fundamental epistemological paradox concerning the long-term prospects of this ML technology. The model needs real human knowledge gained from subjective
by bluetomcat 3y ago
It's a fundamental epistemological paradox concerning the long-term prospects of this ML technology. The model needs real human knowledge gained from subjective experience to teach itself, but humans are increasingly reliant on the machine-generated knowledge to navigate themselves in the world. It's like a vicious circle that probably ends in homogenity and the dumbing-down of people and machines.
- somewhereoutth 3y agoIndeed - it turns out the singularity was in fact self-referential and the whole thing evaporated in a cloud of weights and biases.
- deleted 3y ago[deleted]
- woopsn 3y agoIt will merely end in diminishing returns, no?
- TeMPOraL 3y agoAs long as humans are still interacting with the real world, it might actually work out - by depending on both real-world experience and machine-generated knowledge, humans would become a conduit through which ML models could indirectly experience that real world. The feedback loop would make the models smarter, not dumber.
- JustBreath 3y agoMost of the recent gains with LLMs were from the truly vast corpus of data they were able to ingest for training. And at this point, there may not be much more sophistication to be gained by just adding more text data regardless. Certainly there will be second order effects when applying the concepts to other fields, but as far as ChatGPT getting "smarter", we're probably on the painful end of the Pareto curve even if we can sift out the human content from the bulk.
- gibolt 3y agoMore "quality" data equals more better. The argument here is the LLM generated text is now going to enter the corpus, muddying the waters and reducing the quality.
- chaxor 3y agoPerhaps Meta will release their dataset for Galactica sometime, and we will have incredibly good training data quality.
- dontupvoteme 3y agoCurrent LLM outputs already kind of reek of reddit-style responses, at least to me. Is a hivemind really any different than an AI making its own data?
- crote 3y agoThey might not even need more sophistication, but even something as simple as updating their data might become increasingly difficult. The initial data set was essentially created by undiscriminatingly crawling the internet. This worked reasonably well because up until now most of the internet was - in one way or another - created by humans. This is no longer the case, as LLMs are incredibly attractive when you want to create spam. Anyone who wants to get any general dataset past 2022 will have to deal with the reality that a significant amount of crawled content will have been written by a LLM and is therefore essentially unusable for training. Facts are useless when they have been hallucinated!
- JustBreath 3y ago> updating their data might become increasingly difficult. Very true, I suspect part of the changes at Reddit are being driven by them wanting to hoard their data from AI's et. al or at least make them pay for it.
- bugglebeetle 3y agoThis will not solve any of Reddit’s problems or preserve their data value. While more complicated than an API, it’s trivial to run accounts flooding Reddit with AI generated content through browser automation. Even if they switch to app only access, this is still not meaningfully challenging and app-only would also destroy the service.
- jerf 3y ago"It's like a vicious circle that probably ends in homogenity and the dumbing-down of people and machines." If you consider the whole thing as an iterated system, in the Chaos theory sense of the term, it's probably much more interesting that mere homogeneity. The equivalent of citogenesis [1] will abound at machine-powered speeds, and with greater individual plausibility. In a few select places, entire fictional concepts will be called into existence, possibly replacing real ones. It's likely most places will look normal, too. It won't be a simple situation that can be characterized easily with everything being wrong or dumbed down or anything like that, it'll be a fractal blast of everything, everywhere. [1]: https://en.wikipedia.org/wiki/Wikipedia:List_of_citogenesis_incidents https://en.wikipedia.org/wiki/Wikipedia:List_of_citogenesis_...
- JustBreath 3y agoIn layman's terms: https://xkcd.com/978/ https://xkcd.com/978/
- moffkalast 3y agoIn slightly longer layman's terms: https://www.youtube.com/watch?v=OjlKIjLWq-Y https://www.youtube.com/watch?v=OjlKIjLWq-Y Snopes did recently confirm that this video is in fact accurate.
- AbrahamParangi 3y agoI don’t know if it really is a fundamental problem though. Human knowledge was able to bootstrap itself. Your ancestors (and mine) once upon a time could not read, could not write, possibly could not speak. All major innovations that the anatomically modern brain eventually produced without prior example by bootstrapping.
- ars 3y agoThat's because humans don't say things without understanding them. A LLM will parrot what it learned without any understanding, which is unlike a human.
- AbrahamParangi 3y agoHumans absolutely say things without understanding them. They do that all the time. What is religion but a discussion of the ineffable? Does the concept of "understanding" even meaningfully apply there?
- ars 3y agoYah, I knew someone would reply something like that. Just because someone sometimes says something without understand does not in slightest mean that that is the common occurrence.
- AbrahamParangi 3y agoLook, if you're going to make a claim about LLMs and Human minds being intrinsically different, you're going to have to lay out a testable hypothesis. Saying "LLMs will never be able to solve programming problems with variable renaming" would be a testable hypothesis. "LLMs cannot reason about recursion" would be a testable hypothesis. Something like "LLMs can act as if they understand but they don't truly understand" is NOT a testable hypothesis. Neither is "LLMs are different because we possess qualia and they don't". In order for these to be actually saying something, you would need to bring them to conclusions. "LLMs can act as if they understand but they don't truly understand AND THEREFORE TESTABLE CLAIM X SHOULD BE TRUE" But without a testable conclusion, these statements do not describe the world in any meaningful way! They are what you accuse LLMs of producing - words strung together that seem like they have meaning!
- chaxor 3y agoPerhaps someone will start listening to Chomsky and figure out better inductive biases for the models such that we get tiny local LLMs that are more based in universal grammar rather than initialized randomly or by Xavier.
- kelseyfrog 3y agoIt's a fundamental epistemic paradox even without ML. ML might exacerbate, accelerate, or perturb it, but at it's core it's variation on the Münchhausen trilemma that's invariant with respect to subjectivity or embodiment. Make no mistake, even science isn't immune. We've hoisted ourselves into a conceptual maxima, but we have no idea if it's a dead end or not. 1. https://en.m.wikipedia.org/wiki/M%C3%BCnchhausen_trilemma https://en.m.wikipedia.org/wiki/M%C3%BCnchhausen_trilemma