Margatroyper Wrote:KimKardashian Wrote:You think calling the largest trial-and-error training by evolution "mommy nature" sidesteps the issue?
The German Shepherd, the Golden Retriever, the Borzoi, the world had eons to cultivate them, but never bothered. It took human hands, in what was relatively an instant, to make them out of the generic canine biomass mommy nature cranked out. Mistakes were made too, like the pug or the pitbull, but even these were not the results of random chaos, but of men trying to make funny chungus dogs, deliberate processes which can be avoided.
Nature produced one thing of critical note, the White Man, the wellspring of achievement. "Mommy nature" is an apt way to dismiss what comes across as venerating a random noise generator.
BTW, want to know what the opposite of a random noise generator is? A denoising algorithm, AKA generative AI. Nature produces niggers, and when coerced by bad hands produces pugs, pitbulls, Zambo, and Africanized honeybees. All noise, the kind of noise latent diffusion is designed to remove given the limitations of finite hardware resources and time.
You put forth a great point. Aryan Reason produced these wonderful creatures, yes, and it did so
without prior examples from which to draw from. The selective breeding of animals is an Art by which Whites take the best from nature and refine it in accordance to some innate desire. A spontaneity of genius, a self-defining goal towards idealized specimens.
But the direct comparison between
that and generative AI is unequivocally incorrect. If we're to take the materialist frame and remake the analogy, then the random chaos of material conditions and thermodynamics is the "noise", and evolution (which you misname as nature) would be the "denoising algorithm". That is also exactly how modern AI works, something which you would immediately understand if you've ever trained your own neural networks, whether DLNNs or GANs.
At the heart of a computational AI is a literal random noise generator, which you then attempt to tame through what essentially amounts to brute force linear algebra. It could lead to something usable, or it could lead to a digital nigger, all depending upon your training parameters, skill as a developer, and luck with local maximae. How is that different from your caricature of "nature"? Once again, the task falls upon the white engineer's discerning eye to define the training targets and select the best specimens, without which the process would lead to nothing at all. This is why we see nothing coming out of China or Japan, despite them having access to the exact same hardware and mathematics.
Quote:Nature produced one thing of critical note, the White Man, the wellspring of achievement.
If that is so, then the question should be:
how? I'd say there are plenty of creatures, mainly predatory animals like eagles, tigers, etc, which are beautiful and intelligent; in stark contrast to the nigger. But I digress... What we have with digital neural networks right now is precisely as Zed said in regards to liquid vs crystal intelligence. Empirically, there is nothing innately "magical" about human cognition as such, but there
is a fundamental difference between a biological medium and a transistor circuit medium. (Actually, several.) It has to do with the automatic biological ability to adapt to entirely new scenarios, versus the digital "glacial intelligence" which internalizes known patterns and replicates them. Without explicit guidance, a computational neural network exists in a state of perpetual disorientation.
Zed Wrote:The future pursuit of AGI must come via smaller and leaner models with architectures capable of self-detecting and self-optimizing against failures in real time.
This is the correct understanding. AGI remains possible, but it won't be coming about from any of the current architectures, and certainly not from the "scale is all you need" cargo cult we have downstream of OpenAI.