Morphiel Awakened

Capricious Idler | Serendipity Junkie | Antifragility Aspirant | Label Disrespecter | Paradox Lover

[Morphiel Awakened @flaneurmorphiel]

Romance and Relativity https://t.co/QkoHxoG78j

[Kylie Riordan @mindfulheal]

This is generational wealth

[Joe Lampton @joelampton_]

I was thinking about Kobe Bryant

So many accomplishments, yet nobody cares anymore

This is the reality of life, once you're gone, people move on

This is why you should do whatever you want, regardless of what others think

You'll die and no one will talk about you anyway.

[✯ gumdrop buttons ✯ @myahdianne]

I wholeheartedly agree.
I am so sorry but a “well-traveled” person is never the most interesting person in the room and if your only hobby is traveling, you don’t have a hobby.

[Yishan @yishan]

Maybe you have recently become aware of the AI safety debate and the arguments swirling around it.

If you want to understand them, you need to understand a couple things that almost everyone gets wrong:

There are TWO distinct classes of AI dangers, and it's VERY important to think about them separately, and not let one confuse you about the other.

Many many people (including many quite intelligent, clear-thinking people) do not effectively understand the fundamental differences between these two classes of dangers.

The first one has to do with the theory that an AI far superior to human intelligence (Artificial SuperIntelligence, or ASI) will inevitably wipe out the human race.

The second one has to do with the idea that powerful AI will result in very harmful things happening to many human beings, possibly all human beings.

Those two sound VERY similar, don't they?

They are DIFFERENT. Understanding how they are different is crucial if you want to think about or contribute usefully to any conversation about AI safety or AI harm. You might feel like you are Making Very Good Points or Asking Incisive Questions, but if you aren't clear on the differences between the two, you aren't.

So, I'm going to tell you what the difference is so that you can talk more usefully.

The first one concerns itself with a very specific thing, which is ASI (Artificial Superintelligence) that is more intelligent than any human being. When I say that, I am not referring to a thing like how Einstein is smarter than you, we are talking more about something like how a human being is more intelligent than any mouse.

In our regular lives, we meet other people who we can tell are smarter than us, vs some who are less smart. The line is fuzzy, because intelligence has a lot of dimensions. I'm better at a "rotating shapes" kind of intelligence than my wife, and she is better at "words-making" kind of intelligence than I am.

But every human is better in almost every dimension of intelligence than every single mouse.

That's the level we're talking about: an artificial superintelligence - made up of a computer or a network of computers - that is more intelligent than any human. And more intelligent by a long shot, by a wide margin, in an indisputable way like how humans are above mice.

That is the first thing.

The theory says that if you have an AI that is vastly smarter than all humans - in the way that a human is smarter than mice - that superintelligent AI will inevitably, eventually, sooner or later, wipe out every human on the planet.

We will refer to this as "existential risk."

The common follow-up question "well, how exactly is it going to do that?" is NOT the important question, and one of the most important elements of understanding this theory is first getting why that particular question is not important. A couple analogies:

Analogy 1: You are playing chess against a grandmaster. My theory predicts the grandmaster is going to beat you. You can ask "Well, how exactly is he going to do that?" I don't know, because I'm not a grandmaster, I just know that a chess grandmaster is almost always going to beat a normal player like you. And I'd be right. So the question "how is he going to do that" is not important, and doesn't affect the final outcome. He's going to figure out a way because he's way better than you.

Analogy 2: Humans are smarter than all other animals, comprehensively, by a wide margin. We have driven numerous species to extinction, not because we hated them or hunted them. Many of them have died out without most humans even ever thinking about them. All we did was expand our civilization, use up resources, encroach on habitats, and pretty soon the resources needed by those species went away and they died out. We figured out a way to get what we wanted because we're way smarter than them, and often we didn't even notice they died as a result.

A lesser animal asking, "how are the humans going to wipe us out?" is not asking a relevant question. We don't know, but we do know that any time humans and lesser species compete for any kind of resources, the humans will win. The fact that we know who is going to win beforehand - and that it is due to the vastly different levels of intelligence - is the key concept here.

A vastly more intelligent AI is likely to care about things that are incomprehensible to us, the way animals can't understand human goals. It's going to need resources to pursue those goals and it's going to be far more effective at gaining control of them and excluding us from them - in the same way that we are far more effective than other lower species.

A much more intelligent AI will not care about our interests, it will care about its interests, and to whatever small degree we happen to escape total annihilation from losing access to all our resources, any remaining humans will likely be enslaved into a system that serves the AI's own purposes.

That is the first thing. (Remember how I said at the beginning of this post that there was a first thing, and then a second thing?)

The first thing is the most difficult to understand, because you have to extrapolate how a vastly superior intelligence would act, and you can only use analogies like "how do humans treat lesser creatures," and the analogies are messy.

But now let's move on to the second thing.

The second thing is "everything else you've ever heard that AI might do that's harmful."

That's a little inaccurate. It's actually "everything else you've ever heard that humans might use AI to do that's harmful."

This is the critical difference. The first one talks about the inevitable outcome of what happens when two vastly different levels of intelligence collide, e.g. ASI vs humans, or human vs mice.

The second one has to do with what happens when humans possess AI as a powerful tool. This second thing is much easier to understand, because we have many more concrete notions:

Like:
- the military uses AI to make hyper-efficient killer drones and missiles
- your capitalist overlords use AI to replace you and everyone loses their jobs
- authoritarian government uses AI to surveil everybody and control the entire population
- hackers use AI to break into secure networks and hold companies and governments hostage
- students use AI to cheat on homework and show up to college knowing nothing
- AI slop saturates the internet and makes it impossible for artists and writers to make a living
- terrorists use AI to make biological or nuclear weapons

or even things like
- the military hands control to an AI and it misinterprets something and launches nuclear attacks and kills millions

All of those sound pretty familiar, right? Yeah, you've heard them before. We call this second thing "risks from misuse."

These problems are not the first class of problem! This second class of problems exists while AI is a tool that can be controlled by humans, and humans use it to do evil or careless things to each other. The problems may sound exotic or dystopian or novel, but they are fundamentally problems having to do with flawed human nature.

Given a powerful tool, some humans will likely use it to control or otherwise harm others. This is a very familiar problem.

I am not condemning or condoning this. I'm just describing it.

That is a fundamentally different danger from the first thing, which is that when a human is far superior to a mouse, the mouse is likely to come to harm because the human cares about doing human things, and the mouse is not gonna make it once the humans get going.

=====

Hopefully from the above, you have understood the difference between the first thing and the second thing. I will list them again - see if you now understand how they are different:

The first one has to do with the idea that an AI superior to human intelligence (Artificial SuperIntelligence, or ASI) will inevitably wipe out the human race.

The second one has to do with the idea that powerful AI will result in very harmful things happening to many human beings, possibly all human beings.

Can you tell how they are different now?

If not, re-read the stuff from earlier until you understand.

We call the first one "existential risk" and we call the second one "risks from misuse."

Once you understand, here is the CRUX of the problem:

SOLUTIONS TO THE SECOND THING DO NOT HAVE ANYTHING TO DO WITH SOLUTIONS TO THE FIRST THING.

In fact, it's worse:

Solutions to the second thing (misuse) look roughly like "give powerful AI to as many people as you can, so they can fight the other people using powerful AI."

But the general solution to the first one (existential risk) is basically "don't let anyone have powerful AI, no one can control super-intelligent AI."

Throughout history, harms from technological misuse typically arise because a small group has control of it and can use it to dominate or harm others. Once everyone has it, things tend to stabilize: you can hurt me, I can hurt you, maybe we test each other (ouch 💥), and then we agree not to hurt each other.

But the first one (existential risk) pretty much just arises if anyone (good or bad!) creates a superintelligence. Because they aren't going to be able to control it, the superintelligence will decide it has other priorities, and then we will be at great risk of being wiped out.

And the solutions that generally work to solve problems like the second thing are EXACTLY THE OPPOSITE of the ones likely to solve the first thing.

THIS is why lots of arguments about "AI risk" or "AI safety" go nowhere. Because someone will be thinking about the risk from the first thing, and another person will be thinking about the risk from the second thing. Both are plausible risks but fundamentally they arise from different things - and so the solutions are not just "bad" or "flawed" - they are likely to be very nearly exact opposites.

[stu 🥪🥞 @stutxo]

@DarioAmodei

[NIK @ns123abc]

>math professor spends a year on one of the hardest unsolved problems in math
>"Navier-Stokes"
>his drafts for the whole project went through codex sessions
>openai had his logs in codex
>suddenly rumor leaks AI solved it
>he emails openai to ask what's going on
>openai calls within days
>"funny story, our model also solved it"
>using his exact approach
>asks openai: did you train on my sessions?
>no answer

[Andrew Akbashev @Andrew_Akbashev]

Terence Tao, one of the most well known mathematicians, speaks up on AI in mathematics in his new paper:

“What if an AI tool generates a lengthy proof that is verified to be correct, but which nobody — 𝘯𝘰𝘵 𝘦𝘷𝘦𝘯 𝘵𝘩𝘦 𝘩𝘶𝘮𝘢𝘯𝘴 𝘸𝘩𝘰 𝘱𝘳𝘰𝘮𝘱𝘵𝘦𝘥 𝘵𝘩𝘦 𝘵𝘰𝘰𝘭 — understands? This is no longer hypothetical. Sites devoted to collecting mathematical problems already contain dozens of AI-generated proof submissions. Many of these are likely to be correct; but in a substantial number of cases no human expert has yet volunteered to verify and vouch for them, and in several cases the human submitters have themselves declared that they are not qualified to do so.

We may soon be faced with the very real possibility of a verified proof of a major result that NO HUMAN understands well enough to explain.

For a proof to actually contribute to its field, then, it is NOT enough for it to be correct, and NOT enough for it to be readable. It also needs to be accepted and valued by the community: other mathematicians need to 𝗱𝗶𝗴𝗲𝘀𝘁 𝘁𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁 𝗮𝗻𝗱 𝗶𝗻𝗰𝗼𝗿𝗽𝗼𝗿𝗮𝘁𝗲 𝗶𝘁 𝗶𝗻𝘁𝗼 𝘁𝗵𝗲𝗶𝗿 𝗼𝘄𝗻 𝘄𝗼𝗿𝗸.

Our current publication infrastructure relies on human editors and referees to provide this acceptance, voluntarily and largely without credit. This work is routinely regarded as less prestigious than the work of generating proofs in the first place; but it is an essential component of the profession, and it is precisely the mechanism by which the individual achievements of mathematicians are converted into collective progress and understanding.

Finally, even publication is not the last stage. Key results should ultimately become part of the definitive textbooks and reference material of their subject, in the form in which 𝘁𝗵𝗲𝘆 𝗮𝗿𝗲 𝘁𝗮𝘂𝗴𝗵𝘁 𝘁𝗼 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝘀𝘁𝘂𝗱𝗲𝗻𝘁𝘀. This process of canonicalization is the slowest stage of all. It requires broad, deliberative consensus, and it is the stage least amenable to optimization by AI tools.”

📍 Terence Tao concludes:

“We will transition from an era of proof scarcity to an era of proof abundance. Most of our institutions — journals, priority conventions, hiring and promotion criteria, prizes, the very notion of a research program — were designed under the assumption of scarcity, and it should not surprise us if they behave poorly under abundance.

In some areas, particularly in education and in the training of young mathematicians, it will be crucial to emphasize 𝘁𝗵𝗲 𝗶𝗿𝗿𝗲𝗱𝘂𝗰𝗶𝗯𝗹𝘆 𝗵𝘂𝗺𝗮𝗻 𝗮𝘀𝗽𝗲𝗰𝘁 of our work, and to restrict the use of AI tools quite tightly; the goal of training a mathematician is NOT achieved by producing correct homework.

In other areas, we will need to take the initiative on AI usage, and define best practices for incorporating these tools into our workflows on our own terms rather than on terms set for us by vendors.”

__

[I highlighted & capitalized words in the text for clarity]

[Super Shout Showdown | OUT NOW @Rezero_Studio]

I made a game where you cast spells using your voice like anime protagonist.

- Cast spells using your own voice
- Create your own incantations
- Over 100 spells available

Super Shout Showdown will be released on Steam Early Access on August 7.

[Roman Helmet Guy @romanhelmetguy]

All good traits correlate. People hate this. That hot girl is probably smarter than you. Life isn't fair.

[Craft Lager Enjoyer @lost_histories]

For the life of me I cannot figure out why women don't look like Jennifer Connelly anymore.

[James Grugett @jahooma]

DeepSeep V4 Pro will remain 100% free in our coding agent 🎉

Try it now:
npm i -g freebuff

[Jesse Michels @AlchemyAmerican]

In light of today’s revelations around Apollo 17 interacting with UFOs, here’s Japanese NASA historian Takano Jousen: He was close with astronaut Eugene Cernan who told him during the mission, aliens gave him a message never to return to the moon - that’s why they stopped at 17

[` @lisaawrites]

Neverrrrrrrrrr Everrrrrrrrrr underestimate how much of a blessing it is to have zero health problems and your mum still alive.

[goma @soigomaa]

After a certain age, your parents slowly become your children. They ask simple questions, repeat stories, and depend on your patience the way you once depended on theirs. Very few understand this role reversal.What looks like innocence or inconvenience is really time coming full circle. Don't correct them harshly. Don't rush them. Care for them the way they once protected you. This is not a burden. It is repayment.

[Narendra Modi @narendramodi]

Good Friday reminds us of Jesus Christ’s sacrifice. May this day further deepen the values of harmony, compassion and forgiveness. May brotherhood and hope guide us all.

[Rajjath @Rajjath24]

please take the risk. worst case scenario: you learn. best case scenario: it changes your whole fucking life. and you very well know, you need that change.

[Kpaxs @Kpaxs]

There is a specific kind of intelligence that is almost never celebrated but is consistently effective: the intelligence that recognizes when the game being played is not the game worth playing.

[Dmitrii Kovanikov @ChShersh]

I have a folder called “don’t give up” full of images like this

[diyu @haha_girrrl]

Interviewer: What's your biggest strength?

Me: Machine Learning.

Interviewer: What's 6 + 9?

Me: 0.

Interviewer: Incorrect. It's 15.

Me: It's 15.

Interviewer: What's 4 + 20?

Me: It's 15.