Speaker 1: Welcome to the Sentient Code, where intelligence is engineered, autonomy
Speaker 1: is emerging, and a line between human and machine grows thinner.
Speaker 1: Each episode, we decode the algorithms, explore the robotics, and
Speaker 1: examine the ideas shaping the future of artificial minds.
Speaker 2: Transport yourself back to a very specific recent date, April seven,
Speaker 2: twenty six.
Speaker 3: Oh yeah, I remember exactly where I.
Speaker 2: Was, right. I mean, think about the atmosphere that morning.
Speaker 2: Anyone paying attention to the tech sector was essentially just
Speaker 2: you know, glued to a screen.
Speaker 3: The entire ecosystem was bracing for it. It was like
Speaker 3: a deeply familiar ritual.
Speaker 2: At that point, exactly the celebratory product launch from Anthropic.
Speaker 2: We all knew the choreography by heart.
Speaker 3: The slick presentations, the confetti on social.
Speaker 2: Media, flashy charts proving the new model just crushed every
Speaker 2: single benchmark, and you know, the inevitable rush of press
Speaker 2: releases about how this new AI would streamline your inbox
Speaker 2: or draft your legal contracts or write Python come out
Speaker 2: in like three seconds.
Speaker 3: Yeah, we were all basically standing at the threshold waiting
Speaker 3: for the key to a brand new frontier of capability.
Speaker 2: But instead of a key anthropic handed the world a
Speaker 2: stark warning. They revealed a door, and then they publicly
Speaker 2: dead bolted it.
Speaker 3: What's fascinating here is that the silence across the industry
Speaker 3: in the hours following that announcement was I mean, it
Speaker 3: was physically heavy.
Speaker 2: Because we had grown so numb to it, right, the
Speaker 2: relentless hype cycle.
Speaker 3: Exactly, every minor software update in Silicon Valley is packaged
Speaker 3: as a revolution. But this broke the pattern completely. It
Speaker 3: wasn't marketing. It was a deliberate, incredibly sober acknowledgment from
Speaker 3: the very engineers who built.
Speaker 2: The system, acknowledging that AI had crossed a red line.
Speaker 3: Right, the offensive capabilities of this specific model weren't theoretical anymore.
Speaker 3: They had officially outstripped our collective ability to defend against them.
Speaker 2: Which brings us to our mission today. We are looking
Speaker 2: squarely at Claude mythos preview, which is uh, the AI
Speaker 2: deemed literally too dangerous for public consumption.
Speaker 3: It's a heavy topic, it is.
Speaker 2: We're going to unpack the mechanics of what makes this
Speaker 2: specific entity uniquely formidable, decode the safety calculus that led
Speaker 2: its creators to lock it in a subterranean digital vault
Speaker 2: and analyze what this permanent paradigm shift means for the
Speaker 2: structural integrity of the Internet.
Speaker 3: And for your personal digital safety too.
Speaker 2: Exactly, because imagine a tool so relentlessly capable that it
Speaker 2: could simultaneously identify and exploit the invisible cracks in nearly
Speaker 2: every digital vault on Earth, your bank, your medical records,
Speaker 2: the power grid.
Speaker 3: It's terrifying to even conceptualize. Right.
Speaker 2: So to comprehend why Anthropic pulled the emergency brake, we
Speaker 2: first have to understand the sheer defiance of their decision
Speaker 2: within the current tech landscape.
Speaker 3: Defiance is the exact right word for it. Up until
Speaker 3: that morning in April, the major architectural players open up Google,
Speaker 3: Deep Mind, Meta and Well Entropic themselves. They all operated
Speaker 3: on a very rigid, predictable release cycle.
Speaker 2: You train it, you ship it.
Speaker 3: Basically, Yeah, you sink hundreds of millions of dollars into compute,
Speaker 3: You train a massive frontier model on a planetary scale
Speaker 3: data set, you deployed to the public, and then you
Speaker 3: open the API to developers so.
Speaker 2: They can build thousands of startups on top of it.
Speaker 3: Right, and then you secure those massive enterprise contracts. Yeah,
Speaker 3: that is the engine of the modern tech economy. But
Speaker 3: with Mytho's preview, Anthropic abruptly uncoupled that engine.
Speaker 2: They just stopped.
Speaker 3: They announced zero public access, no developer API, no enterprise rollout.
Speaker 2: Okay, let's unpack this because it is fundamentally equivalent to
Speaker 2: a massive pharmaceutical conglomerate calling a global press conference to
Speaker 2: announce they've cured a pervasive disease. But the compound is
Speaker 2: so volatile they're locking it in a tungsten vault.
Speaker 3: And refusing to manufacture.
Speaker 2: It right, like, you just can't have it. The immediate
Speaker 2: financial implications alone are staggered. Releasing these models is how
Speaker 2: you pay for the server farms.
Speaker 3: Yeah, Anthropic was effectively setting fire to a mountain of
Speaker 3: guaranteed revenue, and the shockwaves registered instantly.
Speaker 2: I remember seeing the headlines.
Speaker 3: Oh it wasn't just tech blogs. We saw immediate emergency
Speaker 3: convenence in Washington, d C, frantic coordination across global cybersecurity frameworks,
Speaker 3: and a profound existential crisis within AI safety circles.
Speaker 2: Media framing leaned heavily into sensationalism.
Speaker 3: Obviously, naturally, the AI too dangerous to release or a
Speaker 3: cybersecurity reckoning has arrived. They dominated the news cycle.
Speaker 2: But beneath that sensationalism was a very real confusion about
Speaker 2: what had actually been built. And you know that confusion
Speaker 2: breeds a very valid skepticism. I really have to push
Speaker 2: back on this narrative of the noble sacrifice. How so well,
Speaker 2: the tech industry has absolutely cried wolf before. We've seen
Speaker 2: companies strategically leak memos about their AI being too powerful
Speaker 2: as a brilliant form of humble bragging.
Speaker 3: Creating artificial scarcity.
Speaker 2: Exactly, it builds this dark, alluring mystique. How do we
Speaker 2: know this isn't just an incredible pr stunt, a way
Speaker 2: to convince enterprise buyers that Anthropic possesses the ultimate magic
Speaker 2: without actually having to prove it in the open market.
Speaker 3: Look skepticism is the only rational starting point when evaluating
Speaker 3: corporate motives, especially in an arms race with trillions of
Speaker 3: dollars at stake. But the pr stunt theory collapses under
Speaker 3: the weight of the actual economics.
Speaker 2: At play here because of the money they're turning down.
Speaker 3: Precisely, Anthropic operates in the most hyper competitive environment in
Speaker 3: human history by keeping mythos previewgated. They aren't just delaying gratification.
Speaker 3: They are actively surrendering critical market share to competitors who
Speaker 3: might operate with vastly different risk tolerances.
Speaker 2: So they're just handing the market to the other guys.
Speaker 3: Right, You do not voluntarily recap your own market dominance
Speaker 3: and forfeit billions in licensing just to manufacture mystique. The
Speaker 3: sheer scale of the financial sacrifice is the irrefutable proof
Speaker 3: of their sincerity.
Speaker 2: They did the math and got scared.
Speaker 3: They executed a mathematically driven safety calculus, looked at the
Speaker 3: raw capabilities of the model and concluded that broad release
Speaker 3: would be synonymous with scattering loaded autonomous weapons across every
Speaker 3: major digital intersection on the planet.
Speaker 2: Wow. Okay, So if the financial sacrifices the proof, the
Speaker 2: capabilities are the poison. We have to peer behind that
Speaker 2: locked door and look at the actual technical leaps we
Speaker 2: really do to ground this. Let's contrast Mythos Preview with
Speaker 2: its immediate predecessor, Opus four point six, which came out
Speaker 2: just a few months prior in twenty twenty six, and
Speaker 2: Opus four point six was not a toy, not at all.
Speaker 3: It was universally regarded as the state of the art.
Speaker 3: I mean it could parse one hundred page legal contract
Speaker 3: in seconds, spot the loopholes, and rewrite the clauses perfectly.
Speaker 2: It was a phenomenal tool for augmentative labor right.
Speaker 3: But the progression from Opus four point six to mythos preview,
Speaker 3: it breaks the linear trajectory of AI development. We aren't
Speaker 3: talking about a model that just hallucinates a little less
Speaker 3: often or writes poetry better.
Speaker 2: The nature of the intelligence shifted, and the clearest metric
Speaker 2: of this shift is the swe bench pro evaluation.
Speaker 3: Which is a brutal test.
Speaker 2: Yeah, it's not a standardized test of multiple choice questions.
Speaker 2: It's a real world gauntlet where the AI is handed
Speaker 2: actual complex issues from professional GitHub repositories and told to
Speaker 2: fix the codebase.
Speaker 3: And Opus four point six achieved a fifty three point
Speaker 3: four percent resolution rate on that, which at the time
Speaker 3: was staggering, and AI fixing more than half of human
Speaker 3: generated software bugs on its own.
Speaker 2: It was wild, but Mytho's preview completely shattered that ceiling.
Speaker 2: It hits seventy seven point eight percent for software engineering tasks,
Speaker 2: and that.
Speaker 3: Jumped from fifty three to seventy eight. It isn't just
Speaker 3: a statistical bump. It represents a phase transition in utility.
Speaker 3: How do you mean when an artificial intelligence crosses that
Speaker 3: seventy percent threshold on swue bench pro it ceases to
Speaker 3: be a sophisticated autocomplete engine. It transitions into a highly competent,
Speaker 3: fully autonomous senior software engineer.
Speaker 2: So it doesn't need a babysitter anymore.
Speaker 3: Exactly, at seventy eight percent, the model no longer requires
Speaker 3: a human operator to watch its logic, catch its syntax errors,
Speaker 3: or redirect its approach. When it hits a roadblock, it
Speaker 3: debugs its own thought process.
Speaker 2: And that absolute autonomy is validated by its near perfect
Speaker 2: scores on a gentic workflow evaluation.
Speaker 3: Which is the real key here.
Speaker 2: Let's clarify exactly what an agentic workflow is for a second,
Speaker 2: because this is where we leave the realm of chatblots entirely.
Speaker 2: We are not talking about typing a prompt and waiting
Speaker 2: for a text response.
Speaker 3: No, not at all. In a true urgentic workflow, you
Speaker 3: hand the AI a high level complex objective like.
Speaker 2: Audit this proprietary database architecture for memory leak vulnerabilities, write
Speaker 2: a patch and deploy the fix.
Speaker 3: Right, and Mythos doesn't just spit out code. It autonomously
Speaker 3: breaks that massive goal down into one hundred sequential steps.
Speaker 3: It spins up its own internal subagents to handle different
Speaker 3: parts of the task.
Speaker 2: It writes a script, executes, it, analyzes the error logs
Speaker 2: when it fails, adjusts its own logic, rewrites it, and
Speaker 2: just loops that process relentlessly until.
Speaker 3: The overarching goal is achieved. It is a self contained,
Speaker 3: self correcting execution.
Speaker 2: Loop, and it's doing this over an unprecedented volume of data.
Speaker 2: Mythos has this crazy long context reasoning capability. It can
Speaker 2: hold millions of tokens of raw code, documentation, and network architecture,
Speaker 2: and its active working memory all at once.
Speaker 3: It can ingest the entire underlying source code of an
Speaker 3: operating system and then instantly correlate a minor configuration error
Speaker 3: in one module with a seemingly unrelated memory quirk tens
Speaker 3: of thousands of lines away.
Speaker 2: Which brings us to the epicenter of the crisis. The
Speaker 2: reason Anthropic triggered the fire alarm wasn't because Mythos was
Speaker 2: too good at building websites.
Speaker 3: No, it was because its unparalleled ability to understand code
Speaker 3: translated perfectly into an unparalleled ability to break it.
Speaker 2: The internal red teaming reports the evaluations done by ethical
Speaker 2: hackers hired specifically to push the model's limits. They revealed
Speaker 2: offensive side cybersecurity prowess that reads like pure science fiction.
Speaker 3: The system card that Anthropic published outlines a machine that
Speaker 3: can autonomously scan massive, intricate code bases. We're talking about
Speaker 3: the bedrock architecture of our digital infrastructure.
Speaker 2: OS kernels, the rendering engines of major web browsers.
Speaker 3: Right, Mythos digest these architectures natively.
Speaker 2: And as it maps them out, it actively hunts for
Speaker 2: high severity zero day vulnerabilities. These are the flaws that
Speaker 2: human experts have missed for decades.
Speaker 3: They're called zero days because the vendor has had zero
Speaker 3: days to write a patch. Historically, finding a true exploitable
Speaker 3: zero day in a hardened system like Linux or Chrome
Speaker 3: it's a monumental task.
Speaker 2: It takes human researchers months, maybe years, to reverse engineer
Speaker 2: a single binary to find one critical.
Speaker 3: Flaw, but Mythos finds them routinely, almost casually.
Speaker 2: The discovery phase is alarming enough, but the exploitation phase
Speaker 2: is what really forced the lockdown.
Speaker 3: Right, oh, absolutely. Identifying vulnerability is essentially just pointing at
Speaker 3: a weeklock on a bank vault. Mythos doesn't just point.
Speaker 3: It autonomously engineers the exploit.
Speaker 2: It actually writes the attack.
Speaker 3: It strings together the incredibly sophisticated attack chains. A real
Speaker 3: cyber attack isn't a single action, It's a ballet of
Speaker 3: mathematical manipulation. Mythos seamlessly chains together memory corruption techniques, privileged
Speaker 3: escalation paths, sandbox escapes, and persistence mechanisms.
Speaker 2: Into a single cohesive payload.
Speaker 3: Yeah, all without human handholding. You just give it a
Speaker 3: vague goal like find exploitable flaws in this Linux kernel version.
Speaker 2: So to put this in perspective for you, it's not
Speaker 2: just giving you the blueprint to a bank vault. It's
Speaker 2: building the drill bypassing the alarm, cracking the safe, and
Speaker 2: handing you the cash, all while you just sit back
Speaker 2: and watch.
Speaker 3: That is the perfect analogy, because the human element is
Speaker 3: completely removed from the actual execution.
Speaker 2: And the targets that compromise in testing were terrifyingly broad Windows, macOS, Linux, Chrome, Firefox, Afari,
Speaker 2: Cloud infrastructure, financial tech.
Speaker 3: In every single controlled test, Mythos beat the top human
Speaker 3: red teams. It was faster, and it was significantly more reliable.
Speaker 2: We have to stop and ask how this happened? I mean,
Speaker 2: how did the technology evolve so rapidly to achieve this?
Speaker 2: A few years ago, AI was hallucinating historical dates and
Speaker 2: struggling with basic math.
Speaker 3: Now it's dismantling operating systems.
Speaker 2: Right, what are the mechanics here? How did it get
Speaker 2: so smart?
Speaker 3: The evolution is the compounding result of specific architectural breakthroughs.
Speaker 3: The first big one is its vastly improved chain of
Speaker 3: thought reasoning applied at an unprecedented.
Speaker 2: Scale, which means what practically well.
Speaker 3: Earlier models operated more intuitively. They'd recognize a pattern and
Speaker 3: a prompt and immediately try to probabilistically guess the final output.
Speaker 3: That's fine for poetry, but it fails catastrophically in complex coding.
Speaker 2: Right, code has to be precise exactly.
Speaker 3: Mythos is trained to relentlessly break massive problems into microscopic
Speaker 3: logical steps. It reasoned through those steps, sequentially, verifying its
Speaker 3: own logic at each juncture.
Speaker 2: But the most counterintuitive part of its hacking ability is
Speaker 2: actually rooted in its safety training. Isn't it The deep
Speaker 2: integration of reinforcement learning from human feedback or URLHF and
Speaker 2: constitutional AI principles.
Speaker 3: It's the grand paradox of AI alignment. Normally, we think
Speaker 3: of URLHF as the seat belt. You use human feedback
Speaker 3: to penalize the AI when it generates harmful content, rewarding
Speaker 3: it when it adheres to strict ethical principles.
Speaker 2: But when anthropic engineers spent years aggressively training Mythos to
Speaker 2: perfectly avoid violating its safety rules, they inadvertently trained it
Speaker 2: to perfectly map the absolute microscopic boundaries.
Speaker 3: Of those rules, which is literally the definition of vulnerability research.
Speaker 3: It's the science of finding the boundary of a system's
Speaker 3: logic and stepping exactly one pixel over it without triggering
Speaker 3: an alert.
Speaker 2: They sharpen the blade while trying to build the sheath exactly.
Speaker 3: And then you add the models enhanced multimodal understanding. MYTHOS
Speaker 3: natively read raw binaries, the ones and zero's, the CPU
Speaker 3: actually executes it parses live complex network traffic.
Speaker 2: But the breakthrough that really unnerved the researchers was something
Speaker 2: they called emergent strategic planning.
Speaker 3: Emergent strategic planning, Yes, this was not explicitly programmed. It
Speaker 3: evolved this capability spontaneously.
Speaker 2: Here's where it gets really interesting. Emergent means nobody wrote
Speaker 2: code saying teach the model to strategize, But in a
Speaker 2: cybertack context, it's simulating the defender's mindset dozens of steps ahead.
Speaker 3: Hypothesisis right. It thinks if I exploit this port, the
Speaker 3: detection software will isolate my IP. So I will first
Speaker 3: deploy a subtle script to generate a distraction on a
Speaker 3: secondary server, forcing security to look left while I quietly
Speaker 3: steal the data on the right.
Speaker 2: Previous models could write basic exploits, but they were like
Speaker 2: eager interns needing constant supervision. If they hit a wall,
Speaker 2: they stopped.
Speaker 3: Mythos is a fully autonomous, tireless mastermind. It has no ego,
Speaker 3: It doesn't need sleep. It anticipates defensive countermeasures before they
Speaker 3: even happen.
Speaker 2: Think about the devices you use every day, your phone,
Speaker 2: your laptop, the servers holding your bank data. Mythos can
Speaker 2: see the invisible cracks in all of them, all at once.
Speaker 3: Which forces us to look at the people who built it.
Speaker 3: When you manifest an entity with these apocalyptic capabilities, how
Speaker 3: do you weigh the pros and cons.
Speaker 2: Why lock it up? The answer is tied to Anthropics
Speaker 2: DNA as a safety first company. It was founded by
Speaker 2: former Open AI executives like CEO Dario Mday and President DANIELA. Amiday.
Speaker 3: They've been shouting from the rooftops about the dual use
Speaker 3: nature of advanced AI for years.
Speaker 2: Dual use meaning it can cure cancer or build a bioweapon,
Speaker 2: secure a network, or destroy it. So they had an
Speaker 2: internal risk assessment that led to the lockdown based on
Speaker 2: three pillars of risk.
Speaker 3: The first pillar is lowering the barrier. Releasing Mythos would
Speaker 3: allow hostile nation states, ransomware gangs, or even just an
Speaker 3: angry teenager to launch advanced cyber operations effortlessly.
Speaker 2: The second pillar is the arms race of defensive capabilities
Speaker 2: would drastically outpace defensive.
Speaker 3: Ones right because defense requires absolute perfection. You have to
Speaker 3: secure ten thousand digital windows. An attacker using Mythos only
Speaker 3: needs to find one window that was left unlatched.
Speaker 2: And the third pillar is proliferation, the risk of model distillation,
Speaker 2: weight leaks, or adversarial fine tune and creating uncontrolled variants.
Speaker 3: This raises an important question if the defense cannot keep
Speaker 3: up with the automated offense, does the Internet fundamentally break?
Speaker 3: That's what model distillation threatens to do.
Speaker 2: Explain distillation because it's a huge concept.
Speaker 3: Think of Mythos as a master chef with thirty years
Speaker 3: of innate intuition. Distillation is like having that master chef
Speaker 3: cook ten thousand perfect meals while a novice just record
Speaker 3: the exact measurements and timings.
Speaker 2: The novice doesn't have the intuition, but they have the
Speaker 2: recipes exactly.
Speaker 3: Malicious actors wouldn't need to steal the massive Mythos model.
Speaker 3: They would use a smart AI to generate millions of
Speaker 3: examples of perfect cyber attacks, and then use the data
Speaker 3: set to train a vastly smaller, cheaper, open source AI
Speaker 3: to do the same bad things.
Speaker 2: A model small enough to run on a laptop.
Speaker 3: And once that's out there, you have uncontrolled, unpatchable variants
Speaker 3: proliferating endlessly.
Speaker 2: But wait, if the good guys don't have access to
Speaker 2: this to defend themselves, aren't we just sitting ducks for
Speaker 2: when a malicious actor eventually builds their own version of Mythos.
Speaker 3: It's the central dilemma, but nthropic solution wasn't to delete
Speaker 3: the model, they just refuse to deploy it publicly. And
Speaker 3: that compromise is Project glass.
Speaker 2: Wing, Project Glasswing, the gated garden.
Speaker 3: They created a highly restricted, defensive cybersecurity coalition, a digital
Speaker 3: fortress with Mythos at.
Speaker 2: The center, and the roster of who gets access is insane.
Speaker 2: Over forty major organizations Apple, Aws, Microsoft, Google, Nvidia, Cisco, CrowdStrike,
Speaker 2: Palo Alto Networks, JP, Morgan Chase, and the Linux.
Speaker 3: Foundation the Titans of the Internet, right.
Speaker 2: But even they have strict rules. The model can strictly
Speaker 2: and exclusively be utilized for vulnerability discovery and remediation within
Speaker 2: their own proprietary systems or open source infrastructure.
Speaker 3: Strictly monitored access. They are barred from using it to
Speaker 3: develop offensive capabilities.
Speaker 2: And the cost guarantees it's a tool for titans, not hobbyists.
Speaker 2: It's premium pricing roughly twenty five dollars per million input
Speaker 2: tokens and a staggering one hundred and twenty five dollars
Speaker 2: per million output tokens.
Speaker 3: A comprehensive security audit of a major codebase could burn
Speaker 3: tens of thousands of dollars in a few hours. Add
Speaker 3: in the strict contracts, the audit logging, the technical controls,
Speaker 3: blocking offensive use. It's an environment of immense friction.
Speaker 2: Yet despite that friction, project glass Wing has had massive
Speaker 2: early victories. Dozens of critical zero day patches have already
Speaker 2: been quietly pushed to major open source projects.
Speaker 3: National cybersecurity agencies are actively coordinating with Anthropic now. One
Speaker 3: cloud provider executive even called it the most effective vulnerability
Speaker 3: hunter they've ever used.
Speaker 2: But naturally, a decision this massive doesn't happen without starting
Speaker 2: a war of words in the tech community. The backlash
Speaker 2: and the praise were instantaneous.
Speaker 3: The AI governance researchers were applauding it. For them, it
Speaker 3: was a profound moment of maturity, prioritizing societal safety over
Speaker 3: market dominance.
Speaker 2: But the open source advocates were furious. Gary Marcus, for instance,
Speaker 2: argued that withholding this tech just empowers a cartel of
Speaker 2: big tech incumbents.
Speaker 3: His tweet was widely circulated. History shows the secrets like
Speaker 3: this don't stay secret forever. We're better off democratizing the
Speaker 3: technology with strong safeguards.
Speaker 2: And then you have the National Security angle, US and
Speaker 2: allied security voices quietly loving this. They see Project Last
Speaker 2: Wing as a way to maintain a strategic edge over
Speaker 2: adversaries like China and Russia.
Speaker 3: So what does this all mean? Is anthropic accidentally creating
Speaker 3: a cybersecurity oligarchy where only the richest banks and tech
Speaker 3: giants get the ultimate shield while everyone else is left vulnerable.
Speaker 2: That's the Gary Marcus argument, right, small businesses and municipal
Speaker 2: governments are left totally exposed.
Speaker 3: It's a valid fear, but you have to balance it
Speaker 3: in partial The open source advocates are historically right that
Speaker 3: transparency makes software more secure. Many eyes make all bugs shallow.
Speaker 2: Sure, that works for Linux, right.
Speaker 3: But democratizing access to an email drafting tool is a
Speaker 3: clear societal good. Democratizing a button that can shut down
Speaker 3: a power grid is a fundamentally different conversation. You don't
Speaker 3: open source the schematics for a weapon of mass destruction.
Speaker 2: To make sense of where this is heading, we have
Speaker 2: to look at how humanity has handled dangerous knowledge in
Speaker 2: the past. We have historical.
Speaker 3: Parallels if we connect this to the bigger picture. The
Speaker 3: most immediate comparison is the dawn of the nuclear age.
Speaker 2: The same physics that power a city can vaporize it exactly.
Speaker 3: We had to invent unprecedented governance structures and classification protocols
Speaker 3: to manage it.
Speaker 2: We also have the crypto wars of the nineteen nineties.
Speaker 2: The US government realized strong encryption algorithms could hide criminal communication,
Speaker 2: so they literally classified lines of cutout as munitions. They
Speaker 2: tried to ban the export of cryptographic mans and.
Speaker 3: We see it in gain a function virology research too.
Speaker 2: But AI is vastly harder to control than uranium or
Speaker 2: a virus, much.
Speaker 3: Harder to build a nuke. You need rare physical materials,
Speaker 3: massive centrifuge is huge facilities. The barrier to entry is physical.
Speaker 3: Artificial intelligence is ethereal. It has a near zero marginal
Speaker 3: cost of.
Speaker 2: Replication, It iterates at lightning speed.
Speaker 3: And it is nearly impossible to air gap once the
Speaker 3: underlying math and methods leak. If the model weights leak,
Speaker 3: it's duplicated millions of times globally. In seconds, you cannot
Speaker 3: recall the code.
Speaker 2: And think about the geopolitical timing. With state sponsored cyber
Speaker 2: operations on the rise, probing our water facilities and energy
Speaker 2: grids and thropics, move could actually serve as a blueprint
Speaker 2: for international export controls and AI safety treaties.
Speaker 3: Monitoring GPUs and model access with the same rigor we
Speaker 3: reserve for nuclear.
Speaker 2: Material exactly so synthesizing this whole journey, the era of
Speaker 2: treating every AI release as a cause for blood celebration
Speaker 2: is a officially dead power.
Speaker 3: Responsibility and risk are now the defining metrics of the
Speaker 3: AI industry.
Speaker 2: And Thropic has promised future updates and metrics on the
Speaker 2: vulnerabilities they patch through glass wing. This cautious, gated approach
Speaker 2: might really becomes a new normal.
Speaker 3: It has to, otherwise the Internet becomes fundamentally untrustworthy.
Speaker 2: And I want to remind you, the listener, about what
Speaker 2: this means for your daily life. It's easy to feel
Speaker 2: disconnected from these Silicon Valley boardrooms. But while Mythos is
Speaker 2: locked away, the reality it created is already out there shaping.
Speaker 3: The invisible digital walls.
Speaker 2: Right It's protecting your bank accounts, your medical records, your
Speaker 2: private communications. You are living inside a high stakes, invisible
Speaker 2: war between automated offense and automated defense.
Speaker 3: And that leaves us with a lingering, unsettling question to
Speaker 3: mull over. What's that Anthropic locked Mythos away? Because it's
Speaker 3: brilliant at breaking systems. It sees the flaws in human
Speaker 3: written code. But if we are entering an era where
Speaker 3: AI can autonomously find every flaw in our software, what
Speaker 3: happens when we inevitably ask the next generation of AI
Speaker 3: to write the foundational code for our society from scratch,
Speaker 3: oh wow, to make it mathematically perfect, immune to attack.
Speaker 3: Will we even be able to understand the systems we're
Speaker 3: being protected by, or will we be entirely reliant on
Speaker 3: an intelligence we can no longer comprehend.
Speaker 2: It's a profound thought. We're handing over the keys to
Speaker 2: the kingdom just to keep the kingdom safe. Thank you
Speaker 2: for joining us on this complex exploration. It's been an
Speaker 2: incredible conversation. Until next time, stay safe and keep questioning
Speaker 2: the code.