The "Ladder of Causation" proposed by Judea Pearl covers similar ground - "Rung 1” reasoning is the purely predictive work of ML models, "Rung 2" is the interactive optimization of reinforcement learning, and "Rung 3" is the counterfactual and casual reasoning / DGP construction and work of science. LLMs can parrot Rung 3 understanding from ingested texts but it can't generate it.
That you seem to consider yourself sufficiently expert and authoritative to declare the idea "overplayed" -- and that you consider this declaration something that will further readers' understanding (which I at least view as the goal here) -- is... let's say, interesting.
In any case, no, I certainly would not attribute to pigs human-level cognition. But certainly, the notion that language is a prerequisite for thought (at least up through the level of "solving a Sudoku puzzle", per some research) has been largely discarded [0]. And certainly, as omnivores (who will kill and/or consume members of their own species, occasionally including even their own offspring, as well as members of other species) I think it's reasonable to suppose that pigs would have an inkling that one being's death is another's meal. And fundamentally, there is ample reason to suppose that pigs are closer to human-like cognition than the vast majority of species on earth. (Anecdata: they make for difficult pets owing to their need for stimulation, they can play video games [1], and -- as any reputable animal scientist will tell you -- once you get past certain bare-minimum things like ending the use of gestation crates, the most important things for pig welfare in industry are not group housing or (beyond a certain point) extra space, but rather giving them toys and a sense of cleanliness via clean bedding.)
But feel free to provide evidence that attests that "[t]heir thoughts on death and loss will be similarly weak." I would certainly take it into consideration.
Of course, the hypothesis that they are sufficiently aware of everything -- existing and being nurtured solely to be slaughtered, having already seen many friends die, if female having had many children stolen from them -- to be traumatized to the point of utter emotional breakdown and unfeeling is also consistent with said observation. Humans who have survived war crimes and horrific battles tend to go pretty dead-eyed too. Death might even be welcomed, as a deliverance.
> BNNs bring the following advantages over GPs: First, training large GPs is computationally expensive, and traditional training algorithms scale as the cube of the number of data points in the time series. In contrast, for a fixed width, training a BNN will often be approximately linear in the number of data points. Second, BNNs lend themselves better to GPU and TPU hardware acceleration than GP training operations.
If I'm not mistaken Hilbert Space Gaussian Processes (HSGPs) are O(mn+m) (where m is the number of basis functions, often something like m=30, m=60, or m=100), which is also a huge improvement over conventional GPs' O(n^3). I know that there are some constraints on HSGPs (e.g. they work best with stationary time series, and they're not quite as accurate, flexible, or readily interpretable or tunable as conventional GPs), but what would be the argument for an AutoBNN over an HSGP? Is it mainly about the lack of a need for domain expert input?
As an outsider to the "tech" scene, who did a PhD generals field on modern European intellectual history (which included a dollop of recent continental philosophy), it's endlessly fascinating to me how people in tech have fixated upon Girard. While a few of his ilk do come up in standard reading lists, he (generally) doesn't -- he is far more prominent vis-a-vis his peers in this discourse than in his "native" one. I suspect that this owes to path dependency and his metaphysics' compatibility with the industry's participants' socio-intellectual priors (so to speak).
I think one further bit of horror is, it has the potential to erode your memory of the lost person, piece by piece regressing your recollection of them to the mean (so to speak) of the model's training set. At some point, will the bereaved -- to use the example given here -- just passively accept that the lost loved one actually was the sort of person to write about quilting, even when they never did in life?
(I think the author of the book discussed above, Osvaldo Martin, is the primary or sole contributor for the Rethinking implementations, in fact -- he had a full implementation in his own repo (https://github.com/aloctavodia/Statistical-Rethinking-with-P...) before deprecating it in favor of the above-linked one.)
The author was also a lead author on a CRC red-series book, Bayesian Modeling and Computation in Python Learning, published a few years ago (short review here):
For context, he is reasonably well known -- probably the third most-prominent of the early Confucians (albeit a distant third, after Confucius and Mencius), with partial and complete English translations. But, he was often regarded by Confucians throughout Chinese history warily, because of certain "Legalist" tendencies (which, to put it crudely, were more authoritarian and Machiavellian as well as more legalistic), which were frequently disparaged (but quietly drawn on by pragmatic "statecraft" thinkers). Especially because two of his students, Han Fei and Li Si, were arguably the most (in)famous legalists.
That said, I had a teacher years ago from Taiwan who argued that 1) Xunzi was the first full-blown "philosopher" (in the Western sense of offering an epistemology etc and arguing in a logically reasoned way) in Chinese history, and that 2) Xunzi and Zhuangzi were the smartest Chinese thinkers of all time. Years later, I'm not sure she was wrong.
That's what books were for (among other things): they were knowledge prosthetics.
EDIT: And to be clear, yes, books were conveying information from other adults. But 1) the capital requirements of engaging or operating a printing press meant that there was some gatekeeping (for better as well as worse) concerning which adults' views made it into print, and 2) there were things like peer review and other social technologies to increase confidence in the accuracy of the information contained in books, i.e. to make that gatekeeping more than merely economic. LLMs are ingesting the unfiltered thoughts of anyone with internet access, and then noisily producing outputs based on them (with some limited inexpert human fine-tuning at the end).
Personally I would vote "no" regardless of whether I had confidence the kid wouldn't be exposed to the dregs of the Internet, for two reasons:
1. LLMs are I think pretty inarguably bad at answering certain types of questions in a factually accurate way, at least without nontrivial prompt engineering. I don't think many 8 year-olds will recognize which types of questions the LLM will give inaccurate answers to, or be ready for the sort of prompt engineering that'd be required to mitigate this.
2. Learning is of course more than simply obtaining and memorizing facts. You don't want to overfit your kid - you want them to have to struggle a bit for their understanding so that it generalizes. Sure, formulating questions is part of that process, but there's something to be said for having to sift through pages of search results (or even better, from a learning standpoint, searching through the pages of a book they had to find on a library or bookstore shelf). It's like the old idiom, give a man a fish and he eats for a day, teach a man to fish and he eats for a lifetime. Better to teach your kid to fish (and for knowledge/understanding, not mere facts).
As for image generation, I suspect you'd find more inappropriate content come up there than with a chatbot - and teaching the kid to draw, paint, etc would probably be better for their development.
Why on earth would this be remotely noteworthy to Tyler Cowen, an economist? Set aside the cultural stuff -- it's obviously just market dynamics at its core. Humanities degrees are -- rightly or wrongly -- not considered to benefit one's future livelihood, so a priori, they are not seen as being as valuable as others in a financial sense, which drives down enrollments in humanities classes. When enrollments go down, it becomes more difficult to make the case to resource-constrained universities that the department deserves the funding used to recruit and retain faculty and graduate students, etc. (It's already a hard case given that humanities departments are less likely to bring in lucrative outside grants than STEM departments.) So, the faculty sing a song, they do a dance -- that is, they make the class as fun and entertaining as possible -- and they give everyone A's afterward. Word gets out (sometimes in a very structured way, via student social network groups), and students enroll (sometimes whole sports teams will swarm a single humanities class). The classes don't get cancelled, and more sections are created, which creates jobs for the grad students as TAs. Some professors are extra eager to inflate grades, because they like the attention and/or they want a following, which boosts their prestige (merit being more subjective in the humanities than STEM, too), and who knows, maybe one day they'll get a book deal or an NPR interview because they taught a famously big class. Some professors don't really want to do it, but the department chair really needs to keep that enrollment up so the provost doesn't axe the whole department in next year's budget, and the grad students have to eat, and what they study is important, so they bear up and do it anyway, and just feel guilty afterward.
It's a real phenomenon, and not good, but c'mon -- let's not pretend to be so shocked.
(EDIT: And the students will be extra disappointed if they don't get that A that was all but advertised to them, so it's all the harder to ever right the ship. And at prestigious institutions, there's always that facile argument that "If you're smart enough to get into this school, of course you're going to be smart enough to get A's at this school!" And all universities want to keep their future alumni donors happy...)
Second the Beast Academy recommendation. I'd add, it's the younger version of Art of Problem Solving. The interactive games are extremely well designed from a pedagogical standpoint, the videos are fun and clear, the visuals are appealing, etc. (And I will say, there's a TTS button on the screen so that a kid who can't read can still hear the instructions, which are usually pretty intuitive anyway, especially after the video walkthrough. And the accompanying comics have proven more supplemental than essential for us.)