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Replying to @PeterDiamandis
Max Planck’s famous line: “science advances one funeral at a time”. Biological clock is not a bug, it’s a feature against stagnation
🚨 ALEX KARP reveals OpenAI will NEVER IPO — their real playbook is to get NATIONALIZED
HOST: How does the liability get written into the S-1? What do the risk factors sound like?
KARP: You're assuming that there will be an S-1… The only way to deal with this kind of liability is to go to the government and say:
"Nationalize us, please!"
HOST: Do you think the Trump administration is going to get on board with that?
KARP: When you have unlimited liability, the only way to deal with it would be to go to the government and say:
"We'll give you 50% of our business."
Of course, the value of the business will collapse first when you do that… collapse another time when you have people on the board… collapse another time…
It might even collapse the whole market.
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Far too many people are worried about super HIGH intelligence destroying humanity, when we should be worried about super LOW intelligence destroying humanity.
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Here is Beth Barnes, the Effective Altruist CEO of METR, explaining how immigration controls are immoral, and that future generations will be embarrassed by the past existence of borders.
This is who Anthropic wants as the "independent" overseer of all frontier AI models.
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When ActBlue's own legal counsel Zain Ahmad tried to report this, IT deleted his messages in real time.
This one says "Please stop deleting my requests. You are violating the laws and policies of our company." Deleted 5 seconds later.
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The Wall Street Journal just confirmed that Jacob Coxon lied here. He worked with multiple "AI safety" execs ahead of his resignation.
This was such a smart question from @BretBaier tonight: "Did you work with any third parties as far as this whistleblowing and coming out?"
Jacob Coxon: "Not at all."
See below for research from @ParkerThayer of @capitalresearch questioning whether there was coordination between Jacob and donor-funded anti-AI groups.
This is something journalists should get a definitive answer on in order to determine how credible Jacob is.
Seven properties, a Mercedes G-Wagon, sneakers worn by Kobe Bryant and a Mickey Mantle rookie card worth $1.5 million. All of these things were bought with taxpayer money.
Paul Randall pleaded guilty in one of the largest Medicaid fraud schemes in the California history – diverting more than $270 million in tax dollars.
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EXCLUSIVE: TALARICO SUPER PAC CAUGHT PAYING VOTERS!
"We are paying people $25...a roundabout way of paying people for their votes."
Video obtained by Townhall catches Sky McAdams, organizing manager for Texas Majority PAC, on undercover video explaining the scheme to elect Talarico in November.
"You can't pay someone to vote for someone"
"If I was a Republican, I would be pissed."
In the video, McAdams says it’s called a “paid relational program,” which is operated by Relentless that uses software called Rally.
In a campaign finance report filed in July, Texas Majority PAC said it paid Relentless $500,000 for a “relational organizing program,” or about 20 percent of all its expenditures up to that point. At $25 per vote, that could be good for 20,000 ballots.
Details below 👇
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India - 1.5 Billion people
Africa - 1.6 Billion people
US - 340 million
UK - 69 million
France - 66 million
Spain - 49 million
Canada - 41 million
Sweden - 10 million
Ireland - 5 million
If mass immigration continues Western nations, cultures and peoples will be gone.
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NEW: A House Judiciary report just dropped screenshots of ActBlue's internal Slack messages.
They show staff knowingly waved through foreign donations—using "verification" methods you won't believe.
Thread 🧵👇
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BREAKING: Prosecutors announce new charges and arrests for alleged homeless services fraud in the L.A. area. One nonprofit leader is accused of misappropriating over $7.5 million, spending much of it on a nightclub and bingo hall. LAist story coming soon.
justice.gov/usao-cdca/pr/2-d…
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JUST IN: L.A. homeless nonprofit founder allegedly spent $50,000 in taxpayer funds on a luxury Tahiti vacation, as Los Angeles grappled with surging homelessness.
If AI is risky like fire is risky, then you want everyone to have it.
If AI is risky like a nuclear weapon is risky, then you want no one to have it.
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.
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The AI Doomers are the same people that proclaimed the end of the Internet during ‘net neutrality’ debates.
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The cover of Time magazine in 2006 and 2026. From "climate change will destroy humanity" to "AI will destroy humanity".
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I followed the money behind the “slow down AI” movement.
What I found is not a secret conspiracy.
It is more interesting than that.
It is a documented influence network connecting billionaire funders, nonprofits, creators, media, activists, frontier labs, and lawmakers.
🧵
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There is an unseen hand pushing AI safety as a political ideology.
Effective Altruists believe a tiny group of technocrats should decide how much technological progress the rest of us are allowed to have…. and how many shrimp your life is worth.
You are witnessing their attempted coup.
thefp.com/p/dangerous-ideolo…
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I have conducted an audit of Anthropic's finances.
What I have found is so shocking that I am calling for a Congressional investigation.
Anthropic is not just seeking regulatory capture.
It has built a regulatory capture machine that cannot be turned off.
Structural financial incentives make it impossible for Anthropic -- I call it the Anthropic Network -- to turn off its own AI doom cycle.
It starts with METR.
Dario Amodei proposes "third-party evaluators" to assess the risk of Anthropic's models.
He proposes METR for this purpose.
But METR is financially dependent on the Anthropic's success -- specifically, on the explosive growth of more than $7 billion dollars in Anthropic stock.
Dustin Moskovitz invested this stock into Good Ventures Foundation, where it represents the majority of that organization's portfolio.
And GVF is the overwhelming funder of the entire Anthropic Network ecosystem.
This stock was worth $500 million early last year.
It is worth more than $7.7 billion just ~16 months later.
METR -- and all of those building a career its parent organizations -- cannot afford to disrupt that growth.
Because if Anthropic goes under, many of the organizations that fund METR go under as well.
But if Anthropic succeeds, METR and its parent organizations become more richly financed to regulate AI -- something those at METR want very much.
The "third-party evaluator" is not "third-party" at all.
The evaluator is on Anthropic's payroll.
If this were the end of it, that's bad.
But that isn't all.
The same organizations that fund METR also fund the many organizations, such as the Tarbell Center, that promote AI Doom.
The Tarbell Center publishes AI Doom articles in The Verge, Science, LA Times, The Dispatch, TIME, and others.
They are selling the problem, and then selling the solution to the problem -- from the same money pile: Anthropic's.
All of these organizations are financially dependent on the same exploding $7 billion money pile.
As Anthropic grows more and more powerful, its AI Doom Machine grows better and better financed -- louder and louder.
Meanwhile, the regulatory regime seeded in METR grows larger to solve the increasingly loud -- now hysterical -- problem of AI Doom that the Anthropic Network itself created.
From this standpoint, as Anthropic becomes more powerful, AI might be getting scarier, sure -- but the positive feedback loop also becomes more deafening -- independent of objective facts.
This itself is an objective fact.
The deafening AI Doom is part of an business model, that, as it expands, so too does the AI Doom messaging -- there is simply more money to do it.
But the problem also goes in the other direction:
If Anthropic dies, the Regulatory Regime and the AI Doom Machine are crippled or die.
Neither METR nor Tarbell nor the other organizations in the Anthropic Network can allow that to happen.
Hence, neither METR or the AI Doom Machine can be trusted to provide independent assessments of Anthropic's models or AI more broadly.
They simply are not organizations independent of Anthropic.
And Anthropic cannot detach itself from METR or Tarbell or countless other safety orgs (not shown here), either, because they drive hype for the models and the possibility of eventual regulatory capture, and Anthropic will not give that up willingly.
What's more, the people at all of these organizations are all the same ecosystem, the same community. They just shuffle between organizations.
The Anthropic Network is therefore, so long as it is successful, locked into a self-amplifying feedback loop inside an ideological monoculture.
And that feedback loop is winning.
That's what Jacob Coxon is.
China is keeping messaging tight. That is why optimism for AI is so high in China.
America has Anthropic: a massive company pushing anti-AI propaganda at a state level.
Anthropic will either create hysteria until American AI slows down and China wins, or it will create fractures throughout American society with severe political consequences.
Ironically, because of the structural financial incentives underpinning the Anthropic Network, it has become the same kind of self-amplifying virus that it fantasizes AI to become in the future -- while hiding its tracks just as carefully.
It is the mirror of the same AI virus that it hypothesizes to consume America.
Anthropic's business model, models itself after the very thing it claims to fear.
Except Anthropic's ideology infects humans, not computers.
Congress must investigate.
Evidence and Github in next post.
Then some supplementary figures.
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Any pursuit of superintelligence has to be grounded in the core principle that if the AI we build is not helping humanity and under human control, it's not worth pursuing.
We also need to accelerate and spread the benefits of AI, such that they are diffused broadly across countries, communities, and companies. This requires a frontier ecosystem in which both closed and open-source models can thrive.
And for firms, it’s imperative that they retain full control over their unique and tacit knowledge. Every organization should be able to build its own continuous learning loop/hill climbing machine, without becoming dependent on any one model provider, and have the ability to embed its own knowledge into models and weights they control.
So, in this context, we welcome the research, focus, and deliberate pacing needed to get alignment right as the design goal. We also welcome ideas like "embedded evaluators" and the broader efforts to develop the mechanisms to make this more than just talk.
The key is that this cannot be controlled by a handful of entities, but must have broad representation across the ecosystem, countries, and fields, including academia.
This is the approach we are taking: broad access and choice at every layer of the AI stack; enterprise control of learning loops and models; and the “Code of Conduct” that underlies our own first party MAI models that we’ll publish tomorrow for public consultation.