📉 Bot traffic from Yandex’s network has dropped to almost zero after an attack on a data center in Vladimir. This is the third attack on Yandex’s data centers since October 8.
Bot traffic is automatic requests to websites from programs — search crawlers, services, parsers.
@gummibear737 T->P: "Y're in trouble! UA blowing all your stuff, u have no diesel for army, u loosing ground in frontlines".
P->T: "no way. All is ok. We winning and have plenty of diesel. All Z's lies. Prove it to u: will sell you diesel!"
T->P: "Knew it! I believed on u. Friends? $ deals?"
@MikeGea25676924@Jennabeangood@jk_rowling@PlanetFitness You don't have to wait 100 years. The minute after a "trans" dies, and the "trans" cannot answer what gender/sex they are, anyone (medic, scientist or whatever) using whatever determination methods can only conclude the reality. And as "gender is fluid" (?) past is irrelevant.
Brilliant and urgent essay by Mustafa Suleyman @mustafasuleyman on the depravity of ‘model welfare’ - training AI to reason and act as if it were an entity with sentience (and hence with interests and rights that compete with our own). It's alarmingly implied by Anthropic's "Constitution," Suleyman suggests, and should stop. https://t.co/9FZpW49ggT
@__aperture_x_ R you retarded? I asked for evidence of a plan to attack CH, which you claimed exists. Do you know what evidence is? Do you know what attacking is?
@gummibear737 It is already a problem. It reinforces bias and incorrect information when used to train LLMs. This also has the effect of diluting the weights used by the LLMs significantly increasing hallucinations.
Brilliant and urgent essay by Mustafa Suleyman @mustafasuleyman on the depravity of ‘model welfare’ - training AI to reason and act as if it were an entity with sentience (and hence with interests and rights that compete with our own). It's alarmingly implied by Anthropic's "Constitution," Suleyman suggests, and should stop. https://t.co/9FZpW49ggT
@lyndall19414@Kasparov63 Naivety is your enemy. And that reply is outside the guidelines, so you will forfeit the payment... To be paid you must post it in the following format: "I am Australian and Russia is NOT my enemy!". And it MUST include the exclamation mark.
Yann LeCun: We’re not going to reach human-level intelligence or AGI simply by scaling LLMs.
“There’s absolutely no way in hell.”
“The idea that we’re going to have a data center full of geniuses is complete BS.”
“It might feel like you have a PhD sitting right beside you.”
“But that’s not what it is.”
“It’s a system with enormous memory and retrieval capabilities not a system that can genuinely come up with solutions to problems it has never seen before.”
Yann LeCun, Executive Chairman of AMI Labs, explains why LLMs are mostly retrieving human knowledge rather than thinking for themselves:
LeCun starts with why so many people misread what these systems are doing:
"I think there's a lot of confusion, really, because we tend to anthropomorphize systems that can reproduce certain human functions."
When an AI writes fluent answers, we assume there's a mind behind them. LeCun's view is that most of what we're seeing is something more familiar:
"LLMs, to some extent, except for a few domains, are mostly information retrieval systems. They can compress a lot of factual knowledge that has been previously produced by humans and can give easy access to it."
The key words are "previously produced by humans."
The knowledge in an LLM came from people. What the system adds is compression and easy access.
That puts LLMs in a long historical line:
"In a way, it's kind of a natural evolution of the printing press, the libraries, the Internet, and search engines. Right. It's just a more efficient way to access information."
@ylecun is clear about their value:
"LLMs are incredibly useful, there's no question about that. And they do amplify human intelligence, like computer technology going back to the 1940s."
He also allows that in a few areas, such as generating code and some types of mathematics, the capabilities seem to go beyond retrieval. But he notes what those areas share:
"It's still, to a large extent, domains where reasoning has to do with manipulating symbols."
That's where the retrieval framing shows its limits. If these systems were truly thinking for themselves, you'd expect that ability to carry over into the physical world. It hasn't:
"The problem is that why do we have systems that can pass the bar exam and win mathematics Olympiads, but we don't have domestic robots, we don't even have self driving cars."
Then comes his sharpest comparison:
"And we certainly do not have self driving cars that can teach themselves to drive in 20 hours of practice like any 17 year old. So we're missing something big still."
@Osint613 Ha, Ha. Ha! Look at how easy it is to identify the bots replying to this thread. As LLMs are not able to identify sarcasm, they just reply as if the offer was not a stunt 🤣
@gummibear737@gummibear737, this type of research is from where real AI will emerge. Not LLMs. Understanding the world by sensory input and experimentation and learning from success/failure. As human and animals do. Still some years to go. https://t.co/GSbQevk1vc