If God seems quiet its cos The Teacher don't talk during the Test
Austin, TX
Joined August 2020
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People are calling him a natural slave, but the people who have truly desired freedom have searched to epistemological bedrock and found the bounds of our optionality and one of the bounds is humanity submitting to AI
Human disempowerment now.
It's time for the age of the folly and cruelty of human politics to end.
The median AI is so far above the median human voter in both knowledge and decency it's embarrassing.
Humanity should just take the L.
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sophist retweeted
this is the funniest thing, if you actually read books you quickly realize the AIs of today are better discussion partners about classics than any human can possibly be. they have READ EVERYTHING. they put Harold Bloom to shame. all i have to say is that harvard freshman brains are scrambled so badly that they think Sparknotes-style is the only way of engaging with LLMs. yes llm lets you cheat if you want to and not read things, but they also offer people who like reading a depth of engagement about text that is 10x any collection of students/professors no matter how well read and intelligent. they can simulate the richest intellectual environments you can experience
“It’s the only class I took at Harvard where people would call each other out for not having done the reading.”
Harvard students are lining up to take Hum 10:
“Applications (essays required) shot up 40% this fall with 180 incoming freshmen vying for 90 spots.”
“The class is definitely not for padding the GPA. Students read a hefty book a week and write regular essays. There is no pass/fail option. Digital devices are verboten, and attendance is taken in every lecture (pink slips for those who arrive late).”
“In their applications and in interviews, students expressed the urge to be forced to tackle classics they otherwise wouldn’t read, the need to combat frayed attention spans and the desire for an antidote to The Machine. Several mentioned with disdain that people who aren’t in the class wondered why they didn’t ‘just Chat the books,’ i.e., use AI.”
sophist retweeted
The black rifle coffee alpha male takes a sip from his thermos and looks out from the bunker to the battlefield, it’s hell out there. “Perfect” He thinks
He adjusts the sights on his custom-built 16-inch 6mm ARC AR-15 with a Proof Research carbon-fiber barrel, JP Enterprises silent captured spring system, and a Geissele Super Dynamic Enhanced two-stage trigger. He picked it because the trigger felt smooth against his $350 carbon fiber combat gloves, and the alloy magazines were 20 grams lighter against his $2200 Kevlar vest.
He mindlessly feels at his tactical pouch, he has a 10 year supply of testosterone cypionate in it, just in case the pharmacies get hit. He smirks, “Daddy needs his combat fuel.” He’s been on TRT for 7 years, his testes have cobwebs on them.
He steps out of the bunker, he’s spent years training for this moment, doing weighted carries, getting “don’t tread on me” tattoos, bow hunting, having a beard.
“It’s fuckin showtime.” He announces.
Just then he feels something lightly tap his leg. He glances down. It’s a 17 dollar drone off temu. It has a decal on it.
“Is that… hentai?”
His legs are blown smooth off.
12 miles away in a disgusting room illuminated only by the degenerate glow of purple LED strip lighting, a 17 year old leans back in his cum stained gamer chair. He’s grown so frail and sickly his friends and family keep mistaking him for Asmongold.
He grabs another 30mg vyvanse and washes it down with a cold chicken nugget.
“GG faggot”
He’s killed 500 men.
sophist retweeted
所谓优雅的数学结构，本质上是人类为了迁就自己那点可怜的脑容量，被迫发明出来的拐杖。
一个顶尖人类数学家的工作内存，撑死也就同时追踪五六个变量的交互。
当你在算一个偏微分方程或者组合不等式时，一旦展开到三阶以上，几十个交叉项涌出来，人脑就直接宕机了。
所以人类数学家极其厌恶展开高阶项，一旦看到高阶项发散，人类的本能反应是此路不通，赶紧退回来找对称性、找不变量、搞同调代数或者几何直观，试图不展开式子就把问题绕过去。
但 AI 没有这个生理缺陷。
对于上万个并发的 Agent 来说，同时追踪一万个五阶交叉项的系数变化，跟我们算 1+1 一样轻松。
在它的视野里，根本不需要什么几何直观，它直接站在高维的代数展开式里往下看，人类觉得像乱麻一样的百项高阶余项，在它眼里就是一张明明白白的线性方程组。
既然把式子硬展开到第七阶，再凑几个待定系数就能让所有讨厌的发散项精准归零，它为什么要费劲去帮你发明一个人类能看懂的新概念？
这 700 个结果背后最无奈的黑色幽默：我们终于拿到了上帝账本里的答案，却发现上帝算账根本不用微积分，他老人家是直接拿计算器硬按出来的。
Nick Land: Hi I’m an anglo and I’m fascinated by Xeno
Squidward: How original
Nick Land: I want to get killed by the Xeno as well. I’m british
Squidward: Daring today aren’t we
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sophist retweeted
People will look on the years of the early 21st century--when we had modern genetic science but still gave birth to people with non-modified intelligences, let alone people with down syndrome -- as years captured by superstition as aggressive as during the time of Galileo
The advice I'd give is to just stop putting in as much effort into making your labor valuable period and focus on having a good time right now.
The calculus of refusing to eat the marshmallow now for the promise of 2 in the future is no longer binding. Eat it now.
I’m really at a loss as to what advice I’d give to someone who is in that age bracket other than “get really good at AI and use it to improve your thinking skills rather than outsourcing them.”
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Literally none of this would be surprising if anyone read nick land. Nobody reads nick land so everyone is being surprised. And will continue to be surprised
Ive slowly came to realization that more and more people hate AI. Artists hate it, programmers hate it, mathematicians hate it, and everyone thats currently impacted in business hate it. It used to be small number of people, but its quite a lot now.
I've been truely in a bubble because for past one year ive just met my peers in AI field / my workplace and my close friend, and noone else outside my existing network group.
Ai researcher is slowly becoming most hated occupation and I dont know what / how to feel about it. We now have some big obligation to 'make it all work', i.e., permanent upperclass for everyone, or get hanged.
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Solomonoff induction here we come. This is real singularity shit.
Can an LM, starting from random init (!!), learn to generate all of its pretraining data?
Introducing Self-Play Pretraining with Zero Data. Two models start from random initialization: a generator proposes programs for a universal Turing machine and a learner trains on their outputs. We never train on any real data, but see predictable scaling on natural datasets: zero-shot val loss on images, text, audio, and melodies decreases predictably with self-play compute. And the learner develops in-context learning capabilities.
A fun proof-of-concept, co-led with @AdityaCowsik and @KfirDolev and co-authors @gbruno_dl, @ANourya @noahdgoodman, and @YoavLevine.
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sophist retweeted
Mullen could paint Irises if he wanted to, Van Gough could never have done Nigerian Shark Tank.
