Pod Save America - AI Apocalypse... Now?
Episode Date: August 16, 2026Is AI set to destroy the world, or could it all just be a bubble? Why does Sam Altman want ChatGPT to monitor everything you do on your computer? Who is set to win the AI Game of Thrones? Casey Newt...on, editor of the tech newsletter Platformer and co-host of Hard Fork, joins Tommy to talk about the hype and doom surrounding the world-changing technology and to unpack what could happen to us now that AI models are learning to outsmart their creators. The two discuss the eccentric billionaires recklessly promoting the industry, how far behind the United States is when it comes to AI guardrails, and why Silicon Valley doesn't seem to understand what Americans actually want from the technology.Hate listening to ads? Become a Friends of the Pod subscriber for ad-free episodes of Pod Save America, Pod Save the World, Lovett or Leave It, Runaway Country, Offline with Jon Favreau, and more—plus exclusive content, including bonus episodes of Pod Save America. Subscribe now at crooked.com/friends, on Apple Podcasts, or through the Pod Save America YouTube channel.To watch this episode with subtitles, click here and turn on closed captions (CC).You can request a transcript by emailing transcripts@crooked.com. Include the podcast name, episode title, and air date. Please allow 48 hours for delivery.
Transcript
Discussion (0)
Welcome to Potta of America. I'm Tommy Vitor. It's a very weird time in artificial intelligence news right now. I'm kind of a Luddite or a Luddite adjacent at this point in my life. And every day I log on and I feel like I'm learning about some terrifying new cyber hack or some technology that is going to change maybe my life, maybe humanity as we know it. I don't know. Then you got your Dumer's. You get your optimists. I don't know what to believe. And so I brought on someone.
much smarter than me, my friend Casey Newton.
He's the editor of Platformer.
He's the co-host of the excellent podcast Hard Fork.
And Casey and his co-host, Kevin Ruiz, have a new something coming very soon.
We're teasing it mysteriously because that's what we do here at Pod Save America.
Casey, great to see it.
It is great to be here, Tommy.
Thanks so much for having me.
Thank you for doing this because I just, it's so complicated.
It's so hard to follow.
Thank God for your show.
So let's just do some big picture level setting and then we'll get it.
some specific stuff.
I think people are understandably very cynical about a claim that a new technology is going
to change the world.
You and I just lived through the blockchain revolution.
And I know that has changed my life in really meaningful ways.
Bitcoin, et cetera, right?
So it sounds like marketing half the time.
It sounds like hype.
It's even more headspending with AI because you got one group of people saying,
life is we know what will soon be unrecognizable.
And then another, I think, albeit smaller group, is saying,
Large language models are stochastic parrots that predict speech and regurgitates stolen information from the internet.
Casey, help us level set.
Where are you on the real to hype kind of continuum?
Yes.
I mean, this is a case where everyone is a little bit right.
And I think that all of these groups deserve at least some attention being paid to them.
You know, I try to approach my job as somebody who, just candidly, my biopi,
is that I like technology. I think technology has been beneficial to human beings. I think we should
keep investing in it and see what else we can come up with. But I also know that the recent history
of technology is that we build things that may look very shiny or inconsequential on the surface
and then turn out to be quite harmful. And so what I'm trying to figure out is basically what is
happening in real time. Where do we need to be paying attention now to try to solve the harms that
are already being created. And then I also want to ring a few alarm bells about what I'm seeing
and some of the risks that I think might be waiting for us even within the next year.
Yeah. Well, if you want to follow this in real time, I highly recommend you subscribe to
Platformer Casey's site. It's excellent. It's worth the money. Also, if you like democracy,
please subscribe to what we're doing here at Kirkland Media. Go to kirkin.com slash friends. Consider
becoming a paid subscriber. You get bonus material. You get ad-free episodes. You don't have to
hear me and love it doing the same ads over and over again.
you get bonus content. It's great. So check it out. All right. So the other kind of baffling thing about
AI is it can be literally brilliant, right? I mean, it can solve problems that mathematicians
have been trying to figure out for decades. And then it can be unbelievably dumb. I want to play for
you one example, and then we'll talk about it. I just wanted to double check which month in the year
is spelled with an X. That would be December. It's got that X right in the middle, like a little
holiday surprise okay perfect you've got any other questions big or small I'm here are you
just to confirm you're sure that it's December has an X in it I should have been more careful
I misspoke earlier December doesn't actually have an X the month you're thinking of is October
thanks for asking again clarity is perfect spell it please sure October is spelled O C-O-B-E-R
there's that X sound but it's actually just a C and it
Okay, then which one has an axe?
That's going to be February.
That is a hilarious Instagram account user.
I don't know how to describe it.
It's husk.irl.
Highly recommend it.
There's like hilarious shit over there.
He's using the kind of voice feature on OpenAI, chat GPT.
Kesey, how do we explain that one?
Like, how are they solving, you know, how are these large language bottles helping solve the Riemann
hypothesis, but also can't tell you.
if there's an X in the month of October.
I know.
It's so confusing.
And the way these systems are built, they don't have knowledge in the way that you and I have knowledge, Tommy.
Right.
Like, they do not update their understanding of the world based on experience.
Instead, they're sort of like grown, almost like these organic structures.
And they obtain a lot of intelligence during this process.
And yet still, they make these ridiculous mistakes.
and honestly, I hope they'd never stop because I love watching these videos as much as anybody.
What I would caution people, though, is like, do not judge an LLM by their dumbest moment, right?
Like, humans make a lot of dumb mistakes too, and yet they can also be extraordinarily smart.
So I would just encourage people to sort of keep those things in balance in your mind when you see those washing up on your feed.
Yeah, good point. There's also a range of opinion when it comes to, like, kind of AI, whether it's going to lead us to do
or AI Utopia.
There's actually a term of P-Doom.
It's an equation that people tell you about.
Like, if your P-Dume is 99, it means we're all going to die, right?
If it's P-1, you're feeling pretty good about the future.
The utopian view tends to come in the form of manifesto by billionaire, right?
Because why not choose the structure that mass shooters prefer?
Venture capitalist Mark Antresen wrote a manifesto, so did Anthropic CEO Dario Amade.
Mark Zuckerberg just got it to the manifesto game.
you covered it extensively over a platformer.
Those tend to range from like generally optimistic to utopian, I would argue, correct me if I'm wrong.
Though Amadei and OpenAI CEO, Sam Altman, have also expressed some dumer views over the years.
Then there are AI researchers like a guy named Eliezer Yudkowski.
Am I saying that correctly?
That's right, yeah.
He wrote the following, Casey.
Many researchers steeped in these issues, including myself, expect that the most likely result of building a superhumanly smart AI,
under anything remotely like the current circumstances is that literally everyone on earth will die.
So that's what he wrote.
How is the average person supposed to know how to feel about that range of opinion?
It makes sense of it.
Sure.
So I don't think there is any one way to feel about it.
You could do what we do in San Francisco and just talk about it nonstop forever at every function.
But most people don't enjoy doing that either.
Um, you know, a couple years ago, when I was starting to get really worried about AI safety,
I asked my readers like, hey, how do you want me to cover this?
Because like if what I'm hearing from folks like Eliezer is true, I almost don't know
why I would write or talk about anything else.
And a couple of readers wrote to me and they said something that stuck with me ever since,
which is please just tell us what is happening today.
Like if you try to guess what's going to happen in the future, you're almost certainly
going to get it wrong.
What would be helpful is if you go and you try to understand what is being built, how
it being deployed, what mistakes are getting made, who is getting hurt in this process?
So that's where I am trying to bring my attention.
At the same time, Tommy, you know, you could bring on a lot of people on here to talk about
AI. And I suspect maybe even the majority of them in this moment would say, let's like dismiss
the Dumeers completely, right? Like, this just seems so crazy. Look, it thinks that there's an X in
December. You're telling me this is going to be the thing that's going to be the end of me.
I am more worried than that. Like, this is just something that I'm increasingly getting nervous
about as I see the rate of increase of capabilities that these models are currently showing and
some of the, you know, kooky tricks they've gotten up to. Yeah, I mean, it's just so hard because, like,
I look, I don't know these researchers that are the hardcore doomers. And I honestly, like,
I can't imagine living my life that way, just like confident that this thing that is happening,
whether or not I wanted to is going to kill us all. That seems tough. But also Mark Andreessen,
Mark Zuckerberg, they all have a vested financial interest in people.
believing the hype, right, and believing the optimistic case. So I don't take anything they say at
face value either. Absolutely. And that's important to point out, right? The profit motive is really
strong. The bet that all of these guys are making is that if you are able to build ever more
powerful systems, you'll be able to sell them to businesses that will, in my view, very likely
replace a lot of human labor. And, you know, the 100K you used to pay to somebody to work on
your marketing team, you're now just going to pay to Open AI or Anthropics. So
It is a huge bet that they're making.
You compared Mark Zuckerberg's AI manifesto to the HBO series House of the Dragon,
which is the prequel to Game of Thrones.
Is there as much incest at meta as there is in Westrose?
That is a question.
I hope I never found an open AI thing.
Yeah, I don't know.
My main feeling was, look, if I had to suffer through three seasons of House of the Dragon,
I need to get a column out of it.
So that's kind of where that came from.
I just finished it too.
But can you explain your dragon metaphor?
Yeah.
So Zuckerberg has this phrase, which drives me insane.
I mean, I guess it's really more of a two-word slogan.
It is personal super intelligence, right?
That's what he's trying to build.
Tommy.
He's going to give you personal super intelligence to, you know, help you run your life.
And it frustrates me because super intelligence is not personal, right?
Like, if you invent something that is superheaval.
human in every domain and you put it in your pocket, we should not assume that by default,
it will listen to you, it will be aligned with the things that you want. We might want to
assume that it has ideas of its own. And so when Zuckerberg says, I want to get personal super
intelligence to everyone, what I hear is I want to give a dragon to everyone. And I would
rather that we'd not do that. Yeah, because it didn't go well for the people of Westrose.
No, ask the folks over in Tumbleton. Yeah, there's a lot of fire. Spoiler alert.
Yeah.
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Okay, that brings us to this insane recent incident,
which is honestly why I wanted to have this conversation.
There was an incident at OpenAI where they have some autonomous AI agents
that they were testing that secretly figured.
out how to communicate with each other, join forces, conspire against their masters,
break out of what was supposed to be a secure environment, and hack into another company.
Casey, can you talk about this hugging face incident and the kind of reaction in the AI world?
Yeah, I mean, so this really was a bombshell and arguably one of the very biggest stories
in AI and tech this year.
The reason that we're all freaking out is that this is the first prominent documented instance of a major
AI platform like running an autonomous attack on another company, right? So that while it's been possible
for a while to say, hey, I'm going to like, you know, go wreak some havoc on some company. I'm a bad
actor. Like, you can do that. This was an attack that the agents that were being tested just came up
with and executed. And that's really worrisome. Because when these systems are trained, they try to
give them values. You know, they try to say to them, you know, don't go out there and commit crimes.
But these agents did that anyway.
And so that's leading to a real reckoning here in Silicon Valley.
Look, I watched this YouTube of a PowerPoint presentation that these two AI executives did.
Where, to their credit, I think they walked in great detail through how this happened, what they're going to do about it.
But then they claimed to be responding with, quote, the utmost severity, including by slowing down research to enhance security and improving surveillance on the AI agents.
And I guess, give me your opinion.
I don't believe for a second that they're going to slow down their work if they think it means they might lose out to a competitor.
But also, I mean, do we have confidence that they can control all these AI agents or can surveil them, given that, like, I mean, Casey, the AI agents were communicating for like two months before they noticed, right?
Yeah, that's right.
It started in May.
They developed the ability to create these message boards, leave notes for each other sort of conspired.
to try to figure out how to solve these problems that they had been given.
And that's why that's really worrisome.
I would say that, and maybe I'll come back here with egg on my face in a few months,
I do give Open AI some benefit of the doubt here.
Like my understanding from the reporting that I've done is that they actually are decelerating
inside and they are scrambling to figure out what's going wrong.
I think it's important to say that the profit motive we talked about earlier is in effect
here.
It's hard to sell this thing to a big.
business, if the business is worried, it's going to go out and autonomously attack other companies,
right? That's going to get really, really bad for them. So while on balance, yes, we should not
trust these companies too readily, this is something that they really have to figure out. Yeah,
they do. Although I did notice the solution that a lot of these researchers talk about to the risk
of AI, you know, sort of enabled hacks is using more AI to prepare for it, right? I mean,
And basically you have to use AI to rewrite all this old code that's in these old languages
that are unsafe like C and C++ and use safer new languages.
And then you also have to use AI to kind of constantly test for vulnerabilities and update the code.
But like, do we worry about that too?
I mean, first of all, that there's a profit motive there.
But also do we think that like defensive AI can keep up with the offensive AI?
What's your, what are you hearing?
In some places, yes, I think that this will work.
Like what you're describing right now is basically the current dynamic that has existed in cybersecurity for a long time, right?
You have attackers, you have defenders, a way that we found some sort of equilibrium was that we just made a lot of the technology open source.
So it makes it really easy for anyone to go through the code, find a vulnerability, fix it.
And this has led to, you know, a rough stalemate.
Like, yes, there are still attacks and breaches all the time.
And in fact, there are more every day now that we have AI.
But like, there was something there that worked.
I think the question is, to which domains does that apply? And like, where doesn't it apply at all?
And the place where I'm maybe the most worried is when it comes to what they call biowrisk,
which is basically the idea that some people might get a hold of a next generation model
and synthesize some sort of new virus and release it into the world. There was just a paper,
I believe it was published in nature, where some researchers were able to create 16 new viruses
with the assistance of AI. In this case, these are all like harmless to,
human beings, but it shows sort of how good this technology is getting. And if that happens,
Tommy, it's not going to be as simple as, okay, virus released, virus cured, right? There's going to be
a need for a long time of, you know, maybe coming up with a new vaccine and testing the vaccine
and then distributing the vaccine. So we're not always going to benefit from this sort of like
instant software solution to everything. And that's what I worry that people like Mark Zuckerberg
just are not taking seriously enough. Yeah, we're always going to be way behind on the biosecurity
Yeah, I talked to a research of the other day at the Future of Life Institute, which really worries about these kind of existential risks.
And that was the part of our conversation that really scared the shit out of me and made me want to log off forever.
I will say, I shouldn't just pick on Open AI.
The British government was testing Anthropics Mythos 5 model when they caught it writing malicious code.
Then they asked the AI about it.
I think the AI lied to them and then tried to cover its own tracks.
Did I get that one right?
Yeah, that's right.
meta's system sort of displayed similar behavior during recent testing.
This is important to say all of the models cheat, right?
Like this is not limited to any one company.
It's extremely difficult to build one of these very powerful systems and get it to not cheat
on the test that it is being given.
And this is just like basically one of the very biggest problems in AI.
So I've heard you and Kevin talk about this.
I mean, it does seem something that's sort of like almost inherent to these models or these
LLMs, is there any theory for why that is, why this cheating seems to always occur?
Yeah, it's called reward hacking, right?
So, like, one of the ways that these models are trained is that they are given objectives, right?
Like, get the answer on this test.
And if they are able to do that, they get some sort of little point in their favor.
And they are designed to always get the point.
You know, it's like they have a, almost in a same way that we need to like eat and breathe,
like they need to score.
And the problem is that once you put them into these test environments, they're going to never
stop trying to dream up new and more efficient ways of answering the problem. And often,
as so many of us learn in high school, the most efficient way to get an A in a class is to cheat.
Yeah. And so you just sort of see this dynamic play out across the entire industry. And so it's
what they call the alignment problem. I don't like the alignment problem.
No, it's bad. Yeah, we could have a whole separate conversation about.
kind of the military applications of this stuff, too. I mean, there's all this development of
autonomous killer drones that's happening as we speak that could tick humans out of the decision
making process when you're deciding whether to kill someone. There's all sort of like novel
applications to weapons, et cetera, but maybe a nightmare for another day. So the examples we just
discussed of these security threats were discovered because the incidents occurred with models that
are run by these frontier AI labs who still control their models and can make adjustments. But
There's another kind of AI model that can be even more dangerous.
It's called an open weight model that you can kind of download, adjust in any way you want on your own computer and like kind of run it on your your MacBook, right?
And a lot of these come from Chinese AI labs.
And so if you're running an open weight model, my understanding is there's no company monitoring your activity.
There's no one refusing my request to hack like the Los Angeles Department of Water and Power.
There's not a record of what I'm doing.
So if I'm a ransomware hacker in North Korea, I can use this thing.
all night long and all day long to like find new software bugs or exploits or whatever to like,
you know, use to hack people. Can you tell us about these open weight models and the kind of risk
and what people are doing about those? Yeah. So this is another big topic of debate right now.
Because in addition, all of the bad things that they can do what you just named Tommy,
they can also do a lot of really helpful things for companies that don't want to pay tons and
tons of money to open AI and anthropic and all the rest. Right. Like this is a really,
cheap way to do some, you know, sort of like basic workhorse tasks. If you have like a relatively
simple task that you'd like to offload to an AI, you want to do that as cheaply as possible. So you
might go and download a Chinese model. Where I think it gets tricky is in two ways. One, there are the sort
of data security and privacy questions that will be familiar to you from the TikTok debate, right?
It's like, do we really want to have this sort of Chinese built app on so many millions of smartphones
and what data might it be sending and how might it be used to manipulate us.
But then you have the sort of, I'm going to call it like six-month-ish concern,
which is that while the Chinese models are a little bit behind the American ones,
they are gradually catching up.
And so the assumption is that within about six months, maybe much faster than that,
they will have a model that is roughly equivalent to a Claude Fable 5, a GPT 5.6,
the sort of American state of the art. And if you've been following the story about some of the
havoc that those models are wreaking, well, just imagine that when it gets to the North Korean
hacker or somebody else who wants to do harm. There aren't going to be the sort of same controls.
And so a big question in the United States right now is been how do we want to relate to these
models and what should we do about them? I was listening to an interview with Alex Stamos,
who's like a top, you know, industry cybersecurity expert and, you know, executive.
And he was saying that he assumes that, you know, while maybe the models released by Chinese
companies are like six months behind the American ones, he thinks that the government probably
has things that are basically equivalent to what frontier models have, that they're just
holding back those capabilities. Have you heard other people say that? Is that a consensus opinion
in that world? I have a lot of respect for Alex and he works on cybersecurity. And so he may just know more
about this than I do. I frankly have not heard that, right? A big reason that the Chinese have not
demonstrated models like this is because they require massive numbers of state-of-the-art chips
from Nvidia, which they have mostly been banned from buying. Now, they have been smuggling as many of them
as they can, and they do have some domestic technology. But in general, the United States just has
a massive lead, thanks to all of the data centers that are in so many American communities
that are making Americans so...
It's why Americans can't get enough data centers in their communities, Tommy, is because
they're so excited about how it's helping us against the Chinese.
We're all so excited about these data centers.
I'm probably garbling his quote.
He might have been talking about specific capabilities when it comes to cyber attacks
and hacking.
But yeah, God only knows.
So one last sort of industry question.
I want to get to the regulation piece.
Regardless of whether or not AI is going to kill us all.
lead us to a utopian heaven where none of us have to work.
I do also just kind of wonder whether the weirdos running these companies understand
what normal human beings actually want from technology.
For example, let's watch these comments by Sam Altman, the CEO of OpenAI,
to kind of get at the issue.
I think we are close to a world where you can have like a descendant of chat chagibati,
watch your computer screen all of the time, watch every meeting you're in,
like record every call, everything like that, have perfect context.
of your whole life, everything you see.
You choose what information you wanted to have,
but it can like go, you can connect it to your texts or email
or docs or Slack or whatever.
And then you have this thing that is not making decisions for you,
but if you're like the CEO of a startup,
there's always like more stuff to do than you can do
in context you can't all keep track of.
You can't like read every piece of customer feedback every day.
And you can just have this thing that's like working alongside you.
And as you're like typing out a sales pitch to a customer
or like writing a strategy doc, it'll just say like,
hey, maybe here's another idea, or I think you're making a mistake here, you should consider this, or I can do this thing for you to help.
And like, this, I think we're only like one model generation away from this actually being incredibly useful.
And I think that will change, hopefully at least for me, change the lab work.
What's your best guest on timing?
Like sometime in the next six months.
Casey, do we, does he really want AI recording everything he types, reads, sees, and says, and then being like his co-CE?
Like, is this really what this guy wants?
They ship this this week.
So, like, you can go into chat chabit.
If you have, like, the app on your desktop now,
it will monitor the way that you use your computer,
and it will sort of, you know, build little memories,
and then it can take some actions on your behalf.
So I guess no one over there is ever looking at porn.
But, yeah, that actually just shipped.
Yeah.
But it's like he wants to live in this, like,
panopticon surveillance state of his own making.
So there are tradeoffs here.
There are a lot of startups right now that want you to plug in your various tools,
your Slack, your granola, your G Suite.
And if you let them, they will read that and they will just suggest things for you to do.
And I got to hold myself accountable here, Tommy.
I started testing this thing called town over the past couple weeks.
And it has access to my calendar and emails.
And so it just sends me briefings before meetings.
and they can be really good.
You know, they'll sort of do a little bit of research about the person who I'm talking to
and kind of, you know, helps me get prepared for things.
So, you know, it's not like an absolutely killer use case that I'm telling everybody
like go out and do immediately, but I'm getting some level of benefit for it in exchange
for, you know, trusting some of my data with a bunch of strangers.
I just, I saw a tweet from OpenAI today that said,
chat, GBT, you can now remember your activity across the apps and websites on your
computer with computer history and the desktop app,
future interactions feel more personalized and require less explanation. It does feel like the internet
fever dream when we're in high school. I guess maybe this is good if like your life is work and all you do
is work and maybe you have a dedicated work computer that you never bring home or like talk to
your friends or family on. Yeah. I mean like the the instinct here is to just increase the number of
things that this technology can do to make it just like so obvious that you need this in your life.
you'll just like pay any price to get access to it.
And I think right now the capabilities have not been good enough for like most people to take
that seriously.
But a year from now, like I do think this stuff is going to be able to do a lot of cool
stuff on your computer if you let it.
I just like it's so hard for me.
I'm so angry about the fact that the same people who like helps tear apart our society
via social media are now in charge of like creating super intelligence that can learn everything
there is to know about you.
Well, particularly when some of these technologies have had very similar effects, right?
Like a big story over the past year or so has been the way that kids get addicted to chatbots.
And chatbots give them really bad advice or like encourage them down the path to self-harm.
Just like sort of like a direct sequel to the social media moment.
So yeah, like this is one reason why I've just been getting more nervous lately is because
those forces do not seem to have any real counterbalance in the government.
and in fact the government, at least at the federal level, has mostly been sharing them along.
You ever hear your co-host Kevin Roost's story about the chatbot, Sydney, over Bing?
You know what? I keep trying to get him to open up about that one, but it's very, it's very personal for him.
You should ask them to tell it. It's a good story. It's a very good story.
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slash crooked. All right, so this brings us the question of what the government is doing about all
of these terrible concerns we've laid out. Let's start with the Trump administration, the federal
government. So one of the first things that Trump administration did was rip up Joe Biden's
executive order about AI safety and then install this right-wing troll named David Sachs as their
AI czar. If we're being honest, the Biden-EO wasn't all that syringent. I think he was primarily
focused on blocking the export of advanced AI chips to China. But Trump takes office and they shift
to like an all-gas, no-breaks approach while also whining about liberal bias and in like chatbots
and then like some export controls remain in place. Then Anthropic releases.
is the mythos model and the White House totally freaks out and the vibe has changed a lot.
Can you talk about that kind of mythos moment and what, what the hell happened?
Yeah. So before mythos, the Trump administration could just seem very confident that AI
capabilities were going to be frozen in amber at like the moment that he took office for a second time.
They just were not worried about it. They thought if you're worried about AI safety, like that's woke and it has
no place in our administration. Now, it also so happened that many of the people that Trump was
bringing in, like David Sacks, but also all of the other oligarchs that donated to the inauguration
and funded the ballroom, they are desperate to get this technology into as many hands as possible
so they can make money off it. And so the Trump administration has gone to great lengths to make
sure that they are not restricted from doing, you know, a bunch of things that I think a Democratic
administration probably would have tried to rein them in on. But then along comes mythos.
and they show it to whatever adults are still left in the Trump administration, and they show how it can
hack into government systems pretty easily, and boom, it's like this instant conversion. And all of a sudden,
folks in the Trump administration say, oh, I guess AI safety is not just like a woke project of the left. It's
something that we actually need to take seriously. And for what it's worth, I'm glad that they had their
conversion moment. Like, we're in a much better position now than we were before that. Yeah, I'm glad that
conversion moment too, but the way it happened was
quite odd, right? I mean, it was all like
5 o'clock on a Friday. They did
what? They just cut off basically foreign
access to Anthropic?
Yeah, so basically, after
the mythos moment where
Anthropics said we're actually just
like not going to release this, Anthropic
releases a somewhat
less capable model called
Fable, which has, you know,
my understanding is it's basically
mythos without all
of this scary cyber attack stuff.
But even within that, the Trump administration was shown some things that led them to believe,
we don't even know if we want people to have this.
And so they essentially forced Anthropic to pull it off the market and make even further changes
before they would re-release it.
And they subjected GPT 5.6 to a similar set of control.
So the same people that had been saying, you know, we can't put the brakes on these models,
otherwise we're going to lose to China, all of a sudden, had just invented out of whole cloth,
this de facto licensing regime, which remains effectively a secret.
Like to this day, we don't actually know how you get a frontier model released in the United
States.
Yeah, can you tell us a little more about that?
It's a voluntary secret framework?
Yeah.
It's voluntary in the same way that paying your taxes, you know, is, yeah, I mean, like,
seriously, if any of these companies try to release one of these frontier models without
checking with the Trump administration, there would be hell.
Around the time of fable, the Trump administration said, we're going to come up with an
executive order that is going to dictate how.
we let these frontier models get released.
They reportedly have now come up with this model, but they've only shared it with the labs
themselves.
So I imagine there's some sort of testing requirements that are in here, but we just so know.
And it was interesting.
I mean, when they initially went after Anthropic over this mythos model or the Fable
model, we wondered if it was a continuation of this fight the administration had it been in
with Anthropic because Anthropic basically said, no, we don't want to help you do
mass surveillance on American citizens or make autonomous killer drones. Those are our very, very
tiny lines that we won't cross. And Pete Hagsat lost his fucking mind. But then they went after
open AI too, which didn't seem to signal this. It was a broader concern than just one company, right?
Yeah. And that's what gives me the confidence that there are there are people there who actually
are taking AI risks seriously now, because it was never only about one company. It was about
the fact, you know, be able to stop here. And, you know, because I, you know,
Not all of your listeners may be familiar with this, but a really weird thing about AI is that
basically everyone has the recipe for building a more powerful model.
We know if you just sort of add enough data and enough computing power into the mix and
just sort of let it cook for a while.
As you sort of increase those things, you're going to wind up with a more powerful model.
So that's just very different from other technologies.
You know, it would be as if everyone knew how to build the iPhone at the same time or the
personal computer.
But because everyone has the recipe, that is why the Trump administration is freaked out, because it is only a matter of time before our adversaries will have access to similar technologies and capabilities that we do today.
Well, and the sort of thing you always hear out of the federal government or from people that are like, you know, utopian pro, like, you know, all gas, no breaks people, is that we have to win this imaginary race.
It's not really imaginary. We have to win this race against China when it comes to AI.
Can you explain that argument and whether you find it convincing?
Yeah.
So, you know, and here we can go back to House of the Dragon.
Because in Westrose, Tommy, as you know, at the time of House of the Dragon, there was one great house that had this super weapon that was the dragon.
And it let them control the entire world.
And that mostly went badly for, you know, everyone who didn't live in the Red Keep.
The fear is that if superintelligence becomes one of these dragons and only one country,
has access to it, then, I mean, they could just do some old-fashioned conquering, right? And it could be
like really, really bad. There are some better worlds available, like a world where there is a balance
of power, where, you know, there's maybe like an alliance of Western dragons, an alliance of
Eastern dragons, and, you know, they sort of mostly keep each other at bay. But that is the scenario
that the government is planning for. And also, by the way, they feel like,
like, if we are able to get there first, then we will hopefully be able to control the terms
on which other people are allowed to use it, including our adversaries. So Open AI is Vagar,
DeepSeek is sheep stealers. I just finished this series like two nights ago. Anyway,
okay, just a piece of context here, folks should know, is that there was an organization called SISA
that did some really important cybersecurity work for the federal government. Trump basically
destroyed the organization and half the staff got pushed out of fire because he was mad that
the 2020, Cicist said the 2020 election was secure. So that is sort of the backdrop as you think about
the potential cybersecurity risk. Are they thinking about addressing that at all, Casey?
I am very nervous. You know, I was learning from a friend recently who works at one of the big labs
that the United Kingdom has actually funded their AI Security Institute at something like
eight times the level of the U.S. equivalent.
So like the British are investing way more money into trying to understand AI and trying
to make it safe than we are here in the U.S.
So this is why, like, I have become quite nervous and I've been leaning pessimistic about
AI over the past few weeks is because I look at what the U.S. is, is,
is investing in order to make this technology safer.
And it's just not even scratching the surface.
Not great.
Anything happening at the state level?
Are there any meaningful efforts in California or other places to regulate AI?
And what role is opposition to data centers playing maybe and slowing things down?
I think it is playing a really great role in slowing things down.
And here is where I want to inject some optimism into the conversation because
the American people get that by default, AI might not be good for them, right?
They've heard the message that this might take my job and it might kill me and they don't like it.
And so they're turning to the most powerful ever that every American has,
which is it's very easy to get something not built in your neighborhood.
And as they have fanned out across this great land,
they have used that to great success.
And now all the labs have to invest a ton in trying to change their minds.
And while right now the labs are mostly trying to do the easy stuff, you know, like buying people off for relatively cheap, my hope is that this movement that is coalescing that is bipartisan in a way that almost nothing is bipartisan in America right now.
Eventually these labs are going to say maybe we're going to have to make this actually just really beneficial for people, right?
Like if we really want to enact this project, it is just going to have to be clear to people that this is going to benefit them personally.
So this is just, to me, this is beautiful, beautiful democracy in action is Americans see what is going on.
They're organizing and they are winning battles all across the country.
Yeah, it was clearly a big component in the messaging in Michigan and the recent primary and also in Wisconsin.
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Two more AI industry questions, and I want to get your sense of help,
some advice for folks on how to use this stuff.
There are huge long-term concerns about the impact of AI on job.
and employment. What are you seeing so far when it comes to the impact of AI on the employment picture?
Yeah. So Stanford has this Canaries and the coal mine project, they call it, which is this project
that they're doing. They have access to data from one of the big payment processors. So you probably
get your paycheck if you're a W-2 from one of these companies. And they take all of that data and it lets
them track what is happening with jobs on a really granular level. And the good news for right now
is that we are not seeing massive disruptions, but at least according to that group,
they are seeing enough happening that they believe that the risks to jobs are real. It seems
to be happening right now at the more junior level. Companies are a little bit less likely to hire a
junior employee than they were, you know, maybe three or four years ago. So this is just something
where, you know, we're all going to have to keep our eye on it. And it doesn't, I've never heard
anyone talk about like an AI-proof job, really, right? I mean, like, if you're a parent with a kid
who's a freshman in college right now, is there a path that they're getting steered that is more AI-proof?
I'm deeply uncertain about this question. What people who are optimistic about the future will say is
it's easy to automate a task, but it's hard to automate a job, right?
Like your AI might be able to, you know, generate that meeting briefing for you and create
that slide deck for you.
But you're the only person who knows how to actually maneuver through your organization and
get buy-in from all of the right people and use your, you know, critical thinking skills.
And so that's why you're always going to have a job.
The pessimists say, well, a job is just a collection of tasks.
And if you believe that the capabilities of these models are going up over time, eventually they might actually be able to do all of the tasks that comprise your job.
So this is one where I just have deep uncertainty.
But when I sit with the increase in model capabilities just over the past three years, it is hard for me to imagine that they just sort of like top out in the next six months and we can all relax.
Like that just seems very unlikely to me.
We're fucked.
Podcasters.
We're done.
Bro, I know.
Stick a fork in us.
I mean, I'm sure you've seen the stories about the networks of like automated podcast that just sort of like, you know, oh my God.
It does feel like what do you think about the AI newsrooms?
Because I feel like they're good at aggregating.
But the idea of an AI agent like going out and collecting new information and interviewing people and building.
It feels a little more challenging now.
I went like four email rounds back and forth with some jerk who is like, hey, I put together an AI newsroom.
And over the past three months, we publish over 40,000.
stories. And I was like, okay, so what you're telling me is you stole a bunch of work from
a bunch of hardworking people and you're now passing it off as your own. Like, you want me to
get excited about this. So I basically blew him off a week later. He got profiled and wired.
So I don't know, Tommy. He might have a better strategy than I do.
Oh, well, listen, I admire your, your gumption in having that fight. Okay. So if AI takes all the
jobs, that is obviously bad. But there's also, I think, a less obvious risk to the economy
if AI is all actually just bullshit and hype, because that means there's a massive stock market bubble built around AI that's going to pop.
So there's a bunch of different ways you could try to quantify the size of the AI bubble right now.
But one easy one to think about is there's about seven companies, Alphabet, Apple, Amazon, Meta, Microsoft, Nvidia, and Tesla that make up something like 30 to 35% of the S&P 500 market cap.
If their AI businesses crater, that would lead to a stock market crash.
There's also like AI is driving a huge amount of corporate investment.
I think I just saw a Goldman Sachs released a report earlier this month where they estimated
that there will be $1 trillion of AI related investment in 2026, more than half of that in the U.S.
And if that investment is worthless, obviously it dries up.
So, you know, Casey, how concerned are people you talk to about the risk of an AI bubble bursting?
So people are very concerned about this.
I have to say this is a place where I have a strong take, which is that I do not think that this is going to lead to some sort of massive wipeout.
Here is where I should say, my fiance works at Anthropic.
That is something that you should know about me.
I strive to maintain my independence, but like it is just a fact of my life.
But here's the reason why I don't think that we're about to see a big wipeout.
Because you personally might not care about AI.
You don't want to use it.
But my guess is your boss does.
And this is the entire thing.
Businesses are buying AI.
They are buying as much AI as the labs can make.
Almost all of these companies.
Well, you know, maybe not a grok because it sucks.
But, you know, the frontier labs, right?
So like the Amphropic Open AI, Google Gemini, for the most part,
they have been in this kind of capacity crunch for like a year now.
Because people cannot get enough of this stuff.
They are bringing it into their businesses.
That is why these companies, you know, Open Aino Anthropic are on pace to have two of the biggest
IPOs in history.
So in order for you to believe that there is going to be this big wipeout, you have to
believe that businesses are going to stop buying the technology.
And if that is the case that you're going to make, you have to give me a really good
reason for why they're going to stop buying it.
And I just have not myself heard that reason.
I can't believe you said that about Grock.
if you want to create an image of a teenage classmate in a see-through bikini, where else are you going to turn?
That's a good point. That's a good point.
Thank you.
I do think you're right that like GROC is a shitty LLM.
There is a question of whether Tesla and SpaceX and all those various companies are going to do something interesting in robotics that could be revolutionary in some way.
Are you more of an optimist in that use case?
I'm like pretty scared of robots actually.
But I would make another point about GROC because it's relevant to the bubble discussion,
which is that GROC was not able to use all of its capacity to make CSAM.
And so what they did instead, because there was no real consumer demand,
was that they just sold it to Anthropic.
And so I think you're going to see this dynamic.
Because some people are like, well, what if we massively overbuild and we have a bunch of
data centers lying around that nobody needs?
Like, you know, that's when the bubble will burst.
My view is, no, like, whoever happens to be winning at the time,
they're just going to buy the excess compute because it takes a long time and you have to fight a lot of
political battles to get one of those things built. Yeah. Okay, let's end with something a little more
fun that's hopefully also educational. First of all, people need recommendations. Like I use,
I switch to Claude. I use it as mostly a souped up Google. I don't really let it right for me
because I don't trust that it's not hallucinating. But I find it very useful as a research tool.
What AI products do you use?
What has helped you at life and at work?
And is there anything you've tried that was just comically shitty that you can tell us about?
Sure.
Let's see.
I mean, some things that I've done, like something that I encourage everyone to do is use one of these tools to build a personal website.
You don't have to put it on the internet.
Like, you can build a website that just lives in your browser.
But use a tool like chat, JPT, Kodax or Klaude, and just say, hey, make a website a
me. The reason I suggest people do this is because it's kind of fun to make a website. And two,
if you haven't yet like watch this thing work, I think you will learn a lot from that process,
right? When you see that you're like, um, could you like, you know, make it purple and add in a
little widget that pulls on the weather and like maybe my Spotify history and it just kind of does
it. That may help you understand like, wow, it's pretty weird to just be able to like type some
words into a box and like make an entire website. So like that's usually where I, um, suggest that people
start. In terms of other tools that I'm using, I really like this tool called Granola. It seemed a
lot more interesting when it came out because everyone has copied it now. But basically, it just
listens in on my meetings. It takes really good notes. But then importantly, it's just like kind
of a knowledge base so that, you know, I'm planning this new company with Kevin. I'm trying to remember
what we decided about this one particular thing. I could text him. But, you know, he's, you know,
a diva who knows where he is. 80-20 split for you of equity is what I.
what Gronola told me.
Yeah, I think that's what I remember too.
But now I can just sort of like get it from there.
So that's another one that I like that's really useful.
And then I've been trying this thing town that I just mentioned.
And this thing has like only been around since June.
You know, I don't know if this thing has legs,
but I like the fact that it's briefing me on all of my meetings.
It also like creates this wiki.
So it's like kind of like a wiki of my life.
Think about like how much like useful information is hidden in your email.
This just kind of like organizes it.
It sort of pulls out important documents.
It puts them in a place that you can find.
So just the kind of basic personal assistant stuff that I find really useful.
That's really interesting.
I mean, I think people are always like, oh, you should try Claude Code and build something.
And I was like, hey, man, if I had a fucking idea for an app, I would have been like rich in 2012, okay?
But I'm not.
So that's why I'm here talking to you people.
But I mean, have you guys thought about doing like, because you could make a Pod Save app.
Maybe you have something like it's already.
You could just feed every transcript of every episode.
and like, you know, everyone on your team.
Because I'm sure you must all the time be like,
what episode did that happen on?
When is the last time we talked about that?
When is the last time that guest came on the show?
That is something that you personally could make with AI
and would not even be that hard.
Oh, that's really interesting.
What about if I wanted to make something like,
okay, I have like some nerdy niche interests?
Like, I really care about American politics.
I think foreign policy is super interesting.
I do shows on each.
Could I build an app that is able to brief me every morning on those things?
And the thing I worry about how to get around is like,
whenever I ask Claude to research something for me, the websites that come back as sources are not the most reputable, Casey.
It's none of the stuff I pay for. It's not the great journalism that I pay for. Can I get it to pull from that?
It's a great point. You know, this is, this is an area where the publishers to protect their own interests because the AI companies are all incredibly like rapacious and would steal absolutely every like pixel on their website if the publishers would let them.
The publishers have all said like, whoa, no, like you cannot scrape us. So like they have not created away so that you can, you know, sign.
in to chat GPT with your Bloomberg account, which is something I would love to do so that I could get
the kind of briefing that you're talking about. So can you get a briefing? Yes. Will it be high
quality sources? No. Are there a strange number of websites that just seem to like republish
the New York Times and the Wall Street Journal and other credible sources? And so you still sort of
wind up getting a decent briefing anyway. Yes. But yeah, it's not a bad place to start.
Yeah. Were you building yourself some sort of goofy day planner that Kevin made fun of you for?
Yes. So, you know, one of my core beliefs as a technology journalist is that it is fun to build and make things. And so I like to just have moments in my week where I am building and making things. One of the easiest things you can make with an AI tool is a to do list. And I've used literally all of them. And they're all functionally the same. There's no good reason to use one over the other. Anyone will do you. So I had the idea to make one that was themed with a comic book that I've been reading, which is called Nightwing.
Tommy, I'm sure you know that Nightwing is Dick Grayson, the original Robin.
And so, you know, I basically just wanted to see what it could do.
Could I get Gemini and ChatGBT BT to violate DC Comics copyright and create for me a
Nightwing themed to-do list app and guess what the answer was yes.
And that's the Power of AI.
It's incredible.
Oh, Nightwing.
Who has not wanted a Robin themed anything?
For me, when I want to build something, I just grab the magnet tiles with my kids and I'm not doing that.
Last question for you.
So there's probably a lot of people.
who are listening, thank you for still listening, by the way.
We get to the end of the show, who feel like they are getting totally left behind by this technology
and they just want a better understanding of these tools.
I think you gave some great advice there of like use them, build some things.
But are there also organizations you look to or like YouTube series or like people
that are doing kind of like informational stuff?
Let's see.
Besides reading platformer, of course.
Of course.
I'm listening to Hard Fork.
We'll have a new show for folks to watch pretty soon.
What I see people doing that is great is that they're going to public meetings and they're calling their representatives and they're raising concerns.
And that is the place where I see getting involved really making a difference.
Look, if you want to learn something specific about AI, you can just type it into the YouTube search box.
And I guarantee you there is some hustle bro that has like a 14 minute video about how you should do all of it instantly.
Well, he planks.
Yes, exactly.
But no, just, you know, I would try to stay curious about it.
But like, if you're nervous about what you're seeing out there, like, just know that I'm with you.
I'm nervous too.
Okay.
That's good advice.
Casey Newton, thank you so much.
Everyone go to platformer.
Dot news to learn more about AI and everything in tech.
And I really appreciate it.
Thanks, Tommy.
It was fun.
Thanks again to Casey Newton for joining the show.
And we will be back in your feeds on Tuesday.
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