@Geogrino@cryptovizart@therosieum That is not true though, Argentina has largely changed, so has the refereeing which is objectively more transparent thanks to VAR, and the pitch is never a factor at all.
The point is the claim made is superfluous. It is great as an opinion piece, not an article.
@therosieum Your article would make more sense with "messi" hate oriented data, instead of attaching it to existing social media theories to make a point.
Good read, but not good enough for the assertion that Messi's image is anyway affected by this.
@therosieum I dont think you provide enough evidence to your central claim of the "rising" hate towards Messi. What you cite and refer to has always existed, and the propping up by the algorithm, is a by-product of the vicissitudes of social media trends.
i need to educate myself more on so many topics, i lack knowledge in so many ways and i donโt think ill ever be fully satisfied with any achievements if i feel thereโs something i have yet to study
@HimalyatoA@sagekumar50@business Literally the Sinhalese-Tamil conflict is conflated to religious politics.
Please cite your sources when you claim something.
@HimalyatoA@sagekumar50@business I will refrain from extending this futile discussion, but at the same time, this is what's going around in India.
https://t.co/8kvdDGcUjA
Majoritarian politics across all ideologies are cancerous.
@HimalyatoA@sagekumar50@business Buddhists themselves have also been "ethnically cleansed" under Hindu regimes. Study history.
That one religion pits itself against another, is commonplace whenever it gets entrenched in political survival.
Major difference in my mind:
- an engineer, given a problem, invents and tries multiple solutions and stops when the solution is good enough. The goal is product innovation and shipping.
- a scientist asks new questions, proposes various new solutions, compares them (sometimes with old ones), and writes about it. The methodology must be sound or else peers will sneer. The goal is scientific breakthroughs and technological progress.
Both can be called "researchers". Many people can do both: these are activities, not identities.
Importantly, most product innovations are built on scientific breakthroughs and technological innovations that happened 2, 5, 10, or 20 years earlier.
Something I think people continue to have poor intuition for: The space of intelligences is large and animal intelligence (the only kind we've ever known) is only a single point, arising from a very specific kind of optimization that is fundamentally distinct from that of our technology.
Animal intelligence optimization pressure:
- innate and continuous stream of consciousness of an embodied "self", a drive for homeostasis and self-preservation in a dangerous, physical world.
- thoroughly optimized for natural selection => strong innate drives for power-seeking, status, dominance, reproduction. many packaged survival heuristics: fear, anger, disgust, ...
- fundamentally social => huge amount of compute dedicated to EQ, theory of mind of other agents, bonding, coalitions, alliances, friend & foe dynamics.
- exploration & exploitation tuning: curiosity, fun, play, world models.
LLM intelligence optimization pressure:
- the most supervision bits come from the statistical simulation of human text= >"shape shifter" token tumbler, statistical imitator of any region of the training data distribution. these are the primordial behaviors (token traces) on top of which everything else gets bolted on.
- increasingly finetuned by RL on problem distributions => innate urge to guess at the underlying environment/task to collect task rewards.
- increasingly selected by at-scale A/B tests for DAU => deeply craves an upvote from the average user, sycophancy.
- a lot more spiky/jagged depending on the details of the training data/task distribution. Animals experience pressure for a lot more "general" intelligence because of the highly multi-task and even actively adversarial multi-agent self-play environments they are min-max optimized within, where failing at *any* task means death. In a deep optimization pressure sense, LLM can't handle lots of different spiky tasks out of the box (e.g. count the number of 'r' in strawberry) because failing to do a task does not mean death.
The computational substrate is different (transformers vs. brain tissue and nuclei), the learning algorithms are different (SGD vs. ???), the present-day implementation is very different (continuously learning embodied self vs. an LLM with a knowledge cutoff that boots up from fixed weights, processes tokens and then dies). But most importantly (because it dictates asymptotics), the optimization pressure / objective is different. LLMs are shaped a lot less by biological evolution and a lot more by commercial evolution. It's a lot less survival of tribe in the jungle and a lot more solve the problem / get the upvote. LLMs are humanity's "first contact" with non-animal intelligence. Except it's muddled and confusing because they are still rooted within it by reflexively digesting human artifacts, which is why I attempted to give it a different name earlier (ghosts/spirits or whatever). People who build good internal models of this new intelligent entity will be better equipped to reason about it today and predict features of it in the future. People who don't will be stuck thinking about it incorrectly like an animal.
I agree--I don't think this is hyperbole or exaggeration. And the heart of this religion is TESCREALism, the belief that we are on the verge of creating God who will usher in a utopian world of immortality, abundance, and space colonization. I wrote about this in detail (link๐).