272. Is Anthropic holding businesses to ransom?

Summary

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The Rest Is Money: Episode 272 — Is Anthropic Holding Businesses to Ransom?

Date: April 22, 2026
Hosts: Robert Peston, Steph McGovern
Guest: Sebastian Mallaby (author of "The Infinity Machine")
Topic: The AI race, the economics and risks of frontier AI firms (DeepMind, OpenAI, Anthropic), and reflections on the people driving transformative technology.

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Episode Overview

This episode features an insightful deep-dive into the current state of artificial intelligence—the technology, the money, and most importantly, the extraordinary people behind its rapid development. Robert Peston and guest expert Sebastian Mallaby explore existential risks, the stark economics of leading AI labs, the UK’s missed tech opportunities, and the rise of Anthropic—a firm whose cybersecurity model is shaking the business world. At the heart of it all is Demis Hassabis, DeepMind’s enigmatic founder, subject of Mallaby's latest book. The conversation is as thrilling as it is substantive, filled with character studies, industry gossip, and high-stakes questions about our AI future.

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Key Discussion Points & Insights

Existential Risks and "P Doom": Are We Racing to Danger?

• The Prospect of AI Extinction
  • Peston opens with the industry's own "P doom," the risk that artificial general intelligence could exterminate humanity.
  • Mallaby recalls his earlier skepticism—machines lacked a survival drive. But Geoffrey Hinton convinced him otherwise:
    • [03:22] Sebastian Mallaby:
      “Imagine you have a good AI. Imagine that there are rival AIs controlled by your enemies... you're going to have to tell your own AI to defend itself. And the moment you tell it to defend itself, it's got a survival instinct... don't tell me, Sebastian, that these machines won't have a survival instinct. Cause they're going to.”
• Machine Recursion and Evolution
  • AI is now writing and improving its own code, blurring the line between static programming and biological evolution—raising concerns about unpredictable "survival" behaviors.
  • [06:46] Robert Peston:
    “We’re almost at that point… basically we’ve got machines that know how to improve themselves. And that would feel to me like evolution.”

Demis Hassabis: Genius, Paradox, and Motivation

• Background: Relentless Curiosity & Competitiveness

  • Born to a musically artistic family with few means, Hassabis was a chess prodigy, eventually the world’s #2 youth player.
  • Driven from a young age by a thirst to “understand everything”—a potentially megalomaniacal but deeply intellectual drive.
  • [12:14] Demis Hassabis (as described by Mallaby):
    “You have to understand this because this is how I see myself… the sacrifice of this child who gives up everything to be excellent at space battles. And I'm doing the same with AI and that's my mission…”

• Paradox of Empathy & Ambition

  • Despite his grand ambitions, Hassabis maintains an ethos of empathy—shaped by his upbringing and faith.
  • [13:20] Sebastian Mallaby:
    "[His mother] made him do church-based philanthropy… And he’s very empathetic.”

• Competitiveness Manifested

  • Won the “Mind Sports Olympiad” five times, self-professed best at table football—his drive pervades everything.

The Birth and Trajectory of the Modern AI Race

• Deep Learning & Reinforcement Learning (2008–2012)

  • Geoffrey Hinton’s deep learning and David Silver’s reinforcement learning sparked the AI boom:
    • 2012: DeepMind’s successes in games like Pong and image recognition (the "CATS paper") marked breakthroughs.

• DeepMind’s UK Origins and Acquisition

  • 2014: Google, Meta, and Tesla all tried to acquire DeepMind—Google succeeded.

  • UK could not finance such ambitions; acquisition funneled $1 billion/year into London R&D.

    • [21:37] Mallaby:
      “We could regard this as a victory for Britain… persuaded this American group… to just rain down research funding onto Britain.”

  • Still, Peston bemoans lost long-term profits and tax returns to the UK.

Economics of AI Startups — Losing Billions for Monopoly Power

• OpenAI’s Bleak Business Model

  • OpenAI is burning through cash at an unsustainable rate ($660 billion projected loss before profit).

    • [23:52] Mallaby:
      “660 billion with a B. I mean this is insanely… negative cash flow because their revenues are paltry.”

  • Mallaby predicts OpenAI will “go bust”—potentially to be acquired by Microsoft or Amazon for its assets and staff.

• Venture Capital & UK Tech

  • Today, global VC is more open to British startups, but serious scaling almost always requires US capital.
  • The key is where profits, control, and “brains” remain.

Anthropic and “Holding Businesses to Ransom”

• Anthropic’s Edge: Focus on Safety & B2B Products

  • Founded by OpenAI defectors (led by Dario Amodei), Anthropic is now a leader, especially in products like the Mythos cybersecurity model.
  • [30:51] Mallaby:
    “If you create something and you basically say to all of the corporations in the world, if you don't have this system… you will be hacked. Imagine how much those businesses will pay you for access…”

• Restricted Proprietary Models: A New Frontier

  • Anthropic’s Mythos is neither fully open-source nor entirely closed, but selectively licensed—a potentially "ransom-like" hold over business clients.
  • Raises questions about fairness, market power, and leak risks.
    • [32:54] Mallaby:
      “…Anthropic has just invented… restricted proprietary, where they retain it, but they restrict. They have a kind of special invitation list of other companies that are allowed to get their hands on it.”

• Fear and Government Involvement

  • Major banks and government bodies have been warned that only those with Mythos can ensure some cybersecurity—others risk catastrophic hacks.
  • This model is criticized as unsustainable; many will demand access, and global competitors (notably in China) will surely catch up.

Safety Culture: Who Can We Trust?

• “White Hat” vs “Black Hat” Founders
  • Amodei of Anthropic is seen as genuinely safety-focused, attracting scientists who “don’t want to destroy the world.”
  • Hassabis works more quietly behind the scenes on safety standards; both are serious, unlike Altman at OpenAI.
    • [35:36] Mallaby:
      “…Dariama Day is a bit more out there… about it, but they share the same safety concerns. They're both PhD scientists, whereas Sam Altman dropped out of university and doesn't have a degree.”

Technical Schools of Thought within AI

• World Models vs. Deep Learning
  • David Silver champions trial-and-error “world model” learning (mirroring human experiential learning), while Ilya Sutskever is a deep learning maximalist.
  • Demis Hassabis is “eclectic,” integrating multiple approaches based on his neuroscience background.
    • [39:39] Mallaby:
      “His view has always been that with machines you're going to decompose intelligence into a bunch of different functions…”

Genius, Leadership, and Team Dynamics

• Is Hassabis a Newton or Feynman?

  • Mallaby likens Hassabis to Oppenheimer: more a genius orchestrator/team-builder than pure lone wolf.
  • [45:25] Mallaby (quoting MIT Prof. Tommaso Poggio):
    “…there’s Richard Feynman and there’s Demis Hassabis.”
    • High praise placing Hassabis in rare intellectual company.

• Credit for AlphaFold

  • Hassabis judged (rightly) to push on when others would have quit—a crucial (if managerial) intervention.
    • [44:33] Mallaby:
      “But I don’t think you assemble and juggle the Brains unless you yourself have an amazing brain.”

What’s Next? Quantum Computing, AGI Timelines, and “Abundance”

• Classical vs. Quantum Computing
  • Hassabis is a Turing “disciple”—believes classical computers will get us to AGI, though quantum has applications for specific areas (esp. encryption-breaking).
• How Far Are We from AGI?
  • Hassabis says five years plus (and keeps “moving the goalposts” out of love for research), while Amodei is more bullish (three years).
• The Culture Series and the Endgame
  • Hassabis’ utopian vision influenced by the Iain Banks’ "Culture" novels—AI brings abundance, money and corporations become obsolete, but the transition could be “brutal.”
    • [50:22] Mallaby:
      “People massively underestimate still today how transformative AI is going to be… if you have abundance, what is money, right?... all of these things he thinks melt away in some theoretical future.”
    • Near-term: governments are unprepared—“it’s hard anywhere in the world to see a government that takes these challenges seriously.” [51:17]

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Notable Quotes & Memorable Moments

• On Risks of AI Survival Instinct:
  Sebastian Mallaby, [03:22]
  “The moment you tell [an AI] to defend itself, it's got a survival instinct. It's got a sense of pain, it's got a sense of winning, defending itself.”

• On OpenAI's Bleak Finances:
  Sebastian Mallaby, [23:52]
  "660 billion with a B. I mean this is insanely... negative cash flow because their revenues are paltry.”

• On Anthropic’s “Ransom” Model:
  Sebastian Mallaby, [30:51]
  "If you create something and ... say to all corporations ... if you don't have this system ... you will be hacked. Imagine how much those businesses will pay you.”

• On Intelligence and Leadership:
  MIT Prof. Tommaso Poggio (quoted by Mallaby), [45:25]
  “There’s Richard Feynman and there’s Demis Hassabis.”

• On Utopian AI Abundance:
  Mallaby, [50:22]
  “We're going to not need corporations because if you have abundance, what is money, right?”

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Timestamps: Important Segments

• [00:01–05:19] Existential AI risks; Geoffrey Hinton’s warning; the prospect of AI survival instincts
• [06:31–14:23] Demis Hassabis’s childhood, genius, competitiveness, paradoxical humility and ambition
• [16:17–19:25] DeepMind’s origin story and the UK tech ecosystem's hurdles
• [21:34–24:33] OpenAI’s dire business prospects and possible demise
• [29:14–33:52] Rise of Anthropic, the Mythos AI model, and the “restricted proprietary” approach
• [34:37–36:37] AI safety culture: who is trustworthy in the AI leadership landscape?
• [36:58–41:39] Contrasting learning approaches in AI: Silver vs. Sutskever vs. Hassabis
• [41:39–45:32] What makes a scientific genius? Comparative genius in tech leadership
• [45:34–49:34] Quantum computing debate, AGI timelines, how far away are we?
• [49:34–51:17] Techno-utopian “abundance,” policy preparedness, and concluding thoughts

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Conclusion

This episode deftly balances technical detail, real-world business implications, and the vibrant personalities animating the AI world. From existential threats to economic realpolitik, from case studies in genius to “AI holding businesses to ransom,” Peston and Mallaby deliver a conversation that is both accessible and profound. For anyone interested in the realities—and the mythology—of artificial intelligence, this episode is essential listening.

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Transcript

[Robert Peston]

The prospect that AI could exterminate us, you take that very seriously, don't you?

[Sebastian Mallaby]

People over the millennia have understood technology as both exciting and frightening. Look at OpenAI. People knew he was a pathological liar. This was sort of fairly common line of analysis in Silicon Valley. OpenAI is losing money hand over fist. Hundreds of billions on research. So it's losing money. I actually think it's going to go bust.

[Robert Peston]

Just make quite a big claim, which I can't let go by. Why do you think they're actually going to go bust?

[Sebastian Mallaby]

Because.

[Robert Peston]

Hello, and welcome to the Rest Is Money with me, Robert Peston. And I'm delighted today to be joined by Sebastian Mallaby, who's written a huge number of books, often on finance, but his latest book is absolutely of the moment. It's called the Infinity Machine. Now, it says that it is about Demis Hassabis, who was the founder of DeepMind and, you know, arguably, if not the most influential player in the artificial intelligence world, certainly one of the two or three jockeying for that title. But actually, it's about much more than that as a book. And the reason, you know, I might as well get my praise out the way that I loved it is because it's filled with really important ideas about how this wave of AI technology is changing our economy, changing society. Something that, on this podcast, we're completely obsessed with. But it's also got an element of a thriller because it's filled with, I mean, weirdos, let's be completely honest, the enormous brains of the digital technology AI world. These are extraordinary characters. I do want to drill down into many of the ideas, but I thought I'd sort of start actually with the biggest question of all. Reading between the lines of your, as I say, gripping book, it was clear to me that you take this idea of what, what those in the industry call P doom, which is the prospect that AI could exterminate us. You take that very seriously, don't you?

[Sebastian Mallaby]

I do take it seriously. I mean, for the first year or two of my research, I consoled myself with the idea that, look, machines will be more intelligent than humans, but they don't have an incentive to kill humans. They don't want to compete with humans. We have evolved, you know, over centuries. We want to pass on our DNA, we want to survive. Survival is our top objective. Machines, on the other hand, they don't evolve, right, and they don't particularly need to survive, so why would we feel threatened? And so I went to see Geoffrey Hinton, the professor in Toronto, who is One of the big P doomers. And unfortunately, he upset my equilibrium.

[Robert Peston]

And we should just remind people, Geoffrey Hinton was the scientist who came up with the sort of set of algorithms that underpin so much AI. And he also has a Nobel Prize. So he's somebody we have to sort of take fairly seriously.

[Sebastian Mallaby]

Right, Right. So there I am in Toronto, sitting in his kitchen for a couple of hours and debating him on whether he's too gloomy. And I said, look, Jeff, you've been working on this since the 80s, but I have to say I don't see why they're going to attack us, these machines. And he says, okay, imagine you have a good AI. Imagine that there are rival AIs controlled by your enemies. Those rival AIs are going to try and destroy yours, hack yours, get into it. And so you're going to have to tell your own AI to defend itself. And the moment you tell it to defend itself, it's got a survival instinct. It's got a sense of pain, it's got a sense of winning, defending itself. And so don't tell me, Sebastian, that these machines won't have a survival instinct. Cause they're going to.

[Robert Peston]

Sebastian, we've just got to break off for a couple of minutes for a break, but tons more to talk to you about.

[Greg Jackson]

We're proud to say that the rest is money is powered by Octopus Energy this year. Greg Jackson is back to answer another question. Now, this is something that we see a lot that I wanted to ask you about when you're building a business from scratch. Like what? What's the most important thing early on? And what do people get wrong?

[Robert Peston]

Yeah, look, early on, the most important

[Sebastian Mallaby]

thing is to start building a customer base. Until you've got customers, you have no

[Robert Peston]

idea whether the products and services you're

[Sebastian Mallaby]

offering are going to be the ones that people want. So a lot of people spend far too much time building out pages and pages of business plans, thinking too hard

[Robert Peston]

about what they're going to do rather than just doing it.

[Greg Jackson]

What surprised you most when you were launching Kraken?

[Robert Peston]

You know, the great fun of launching

[Sebastian Mallaby]

Kraken was it was the engine that powered Octopus to grow. You know, ultimately it's the biggest energy supplier in the UK with, I think, the best service, but we were able

[Robert Peston]

to license it to our rivals as well.

[Sebastian Mallaby]

So the interesting thing is the world is more complicated than you think, and

[Robert Peston]

your competitors will work with you if it's in their interests.

[Greg Jackson]

Cheers, Greg. Right, well, you'll be hearing more from Greg throughout the year. But now let's get on with this episode.

[Robert Peston]

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[Sebastian Mallaby]

Yeah. Well, they're improving. That's the human coder.

[Robert Peston]

Is that not. Is that not the same thing as evolving?

[Sebastian Mallaby]

It's a good point, particularly recently, because what's happening recently is the machines are coding new code into their own code, if you can get your mind around that.

[Robert Peston]

So we're almost at that point what people call recursion, where basically we've got machines that know how to improve themselves. And that would feel to me like evolution.

[Sebastian Mallaby]

I agree now, right. Even if we conceded evolution, we might say optimistically that why do they need to survive? I mean, I think there's a. You know, Kazuo Ishigura's novel about machine intelligence ends with the robot. I'm forgetting her name, but she's sort of quietly dying perfectly happily in a car park when she's been abandoned at the end and seems totally relaxed about the whole thing. And that vision of a machine not minding about its own sort of life extension was. That was what was comforting me. And that's what I. That he gave up.

[Robert Peston]

Now, one of the striking things about Demis Hassabis, and he is the main character in your book, even if there are lots of other characters in it too, is he does take the risk of human extinction seriously.

[Sebastian Mallaby]

He does.

[Robert Peston]

He doesn't dismiss it. And yet, you know, he goes on and on and on building a better version of AI. How does he justify that to himself?

[Sebastian Mallaby]

Well, I think there's two answers. One is, look, if he quit his job at running Google, DeepMind, the whole engine room for Google, and said, I don't want to build this stuff anymore because it's dangerous, I'm going to take a professorship at Princeton, it wouldn't make the world safer because there'd be a bunch of other labs racing ahead. Somebody else would take his position. How is that helping? So that's one reason to continue. And then the other reason is that. And I thought about this a lot. But, you know, people over the millennia have understood that technology is both exciting and frightening. And we, yet we go ahead with it, we embrace it and we do this because otherwise we would still be living in caves. So to some extent, Demis continuation of his quest for superintelligence feels irresponsible because he admits it's dangerous. On the other hand, he's an enlarged version of you and me.

[Robert Peston]

What do you mean by that? Sorry.

[Sebastian Mallaby]

We all have this impulse, right, that we would like to, you know, we're frightened of technology, but we're excited by it and we move ahead. We're worried and we nonetheless move ahead. And that's what I'm saying, that he's, he's doing the same.

[Robert Peston]

So. Yeah, look, I, of course that's right. I guess one of the things that is just, I don't, I mean, look, if I'm honest with you, I can. I sort of get Demis Hassabis. There are certain things that he's able to do that I'm incredibly jealous of. But he is definitely very different from me in the sense that, you know, here is this individual who I think you say, you know, he comes from a pretty, I mean, certainly not a wealthy north London background. Correct. His mom, I think, grew up in absolutely, you know, pretty extreme poverty in Singapore. Is that right?

[Sebastian Mallaby]

Right.

[Robert Peston]

And his dad is a Greek cypr, sort of hippie, ish musician, Is that correct?

[Sebastian Mallaby]

Yep, that's correct.

[Robert Peston]

And at the age of four, I think you say he's watching his dad play chess and just sort of picks up the rules sort of by osmosis and within an incredibly short space of time is on the chess circuit, the chess competitive circuit. I mean, I'm not getting this wrong, am I?

[Sebastian Mallaby]

No, that's correct. And you know, he was the best youth chess player in Britain, second best in the world. We're talking seriously competitive.

[Robert Peston]

And I mean, one of my favorite early stories is how he gets identified really, when he's still really little, by a sort of chess guru. He's so young, he falls asleep at six o' clock over the chessboard during the competition. So he doesn't manage to win that particular. But he gets identified by this guru as this great prodigy. And that's why his father goes from being sort of laid back music hippie to, you know, the great sponsor of

[Sebastian Mallaby]

this, this prodigy's chess career, 1980s version of a helicopter parent.

[Robert Peston]

So what, so at what point and why does he move out of, you know, wanting to be chess world champion into, I mean, in his own words, wanting to understand absolutely everything, as it were. He's, he is, he is a really paradoxical and intriguing character because on the one hand there's so much about him which is attract, and then he comes up with these statements like his great ambition in life is to understand everything. And you just think, my God, you're a most incredible megalomaniac. So which is he?

[Sebastian Mallaby]

Well, both, I mean, you know, he. So I had this experience right from the beginning of spending time with him. I spent more than 30 hours and it was just the most amazing ride. And right at the beginning he said, look, before we have dinner, I want you to read this book called Ender's Game, which is a science fiction story about a teenage boy who is trained in a battle station in space. And then he defends all of humanity against the invading space aliens and essentially saves humanity. So I'm reading this, I think, does he mean to suggest that he's also going to save all of humanity? Because that's quite a lot of humanity to be saving.

[Robert Peston]

It's quite a big ambition.

[Sebastian Mallaby]

Yeah. So I go along, I have supper with him and he says, yeah, you have to understand this because this is how I see myself. And it's partly also just the sacrifice of this child who gives up everything to be excellent at space battles. And I'm doing the same with AI and that's my mission and that's why I stay up till 4 o' clock in the morning every day, because I have to solve problems. The nature of reality. And by the way, Einstein, maybe not Einstein, but I think he said Newton and Richard Feynman, the physicist, they were failures. Failures because they only understand some of physics, not the whole thing. So I need to do better than that. And I'm building AI because then it gives me a tool, a new source of cognition with which to understand all of reality. And that's what we need.

[Robert Peston]

It is extraordinary because he also talks about which you wouldn't think is being consistent with that. And I don't know if this is true, but he says that he puts a very high weight on empathy and understanding people. Do you think he does understand people or do you think this is a slight illusion on his part?

[Sebastian Mallaby]

Well, no. So this is, I mean, look, he's such a fascinating person, but he is somebody who was brought up by this mother who had been an orphan in Singapore, as you said, who was quite religious, who took him to church, who made him pray in the evenings, who made him do church based philanthropy and to care about other people. And it was a big rule, you shouldn't control or dominate other people. And he's very empathetic. And you know, in my experience with him, he comes across as a normal person. He relates unlike most computers, even though

[Robert Peston]

he comes out, because you know, the quotes in the book are, some of them are jaw dropping. Even though he comes out with these really extraordinary, almost messianic statements. Nonetheless, when you meet him, he comes across as a sort of normal bloke.

[Sebastian Mallaby]

Yeah, he comes across as normal bloke. And also you sit back and you think, wait a minute, he just said he wants to be better than Isaac Newton. But actually, you know, what with AI, he probably will discover new stuff that Isaac Newton didn't know. So maybe he's just being objective. I mean, he's so extreme in his attainment that he's allowed to be a bit extreme in his self description.

[Robert Peston]

I mean there are so many sort of amusing anecdotes related though to his competitiveness. I mean, I find it absolutely hilarious that on the one hand, you know, he, I can't remember, there's some competition which I only actually ever came across through your book, which is like the international mega, you know, brainy games compass, you know, there's the World cup of Brainy Games or something which he's won. You have to tell us what the actual title of this thing is. But he's won it four times, actually,

[Sebastian Mallaby]

the Mind Sports Olympiad, five times in a row. And he will remind you.

[Robert Peston]

But he also insists that he is the world's best table footballer, which is so bizarre as a combination.

[Sebastian Mallaby]

Again, I mean, it might be true, it probably is true, but to insist on it, that's the interesting bit. And I said to him, yeah, whatever, you know, table football, who cares? And you know, this is quite serious. No, I went and watched, I looked up on YouTube, Sebastian, you can now see the world championships and table football, the American players, because they have a professional league and they don't know the snake shot. They don't know how to hook their arm underneath the lever and like twist it over and get double speed on it. And I did, and that's why I was the best player in Cambridge.

[Robert Peston]

Anyway, we should, I suppose, get ourselves back to the stuff that is transforming our society now. Got a bit of a sort of sense of the sort of anthropology of all these people who've been contributing to this extraordinary revolution in terms of where we are with artificial intelligence. When for you, let's. I mean, obviously, you know, we could talk about Turing, we can, you know, talk about, you know, Ada Lovelace or whoever, but I'm just talking about this generation. When does it all start and why does it all start?

[Sebastian Mallaby]

Yeah, so in the late 2000s, around 2008. Nine, I think, was really the foundation when two things began to work. The first was the early deep learning, and that's the Geoffrey Hinton stuff, where basically you train a model on lots of data and it can make sense of some data. And then another thing was early experiments in reinforcement learning. And this was learning through experience, trial and error. Playing a game, for example, trying a random move and seeing things.

[Robert Peston]

This is the David Silver stuff.

[Sebastian Mallaby]

Yeah, exactly. David Silver being The scientist at DeepMind who was a specialist in this. And both these fields showed early, early, early signs of WA up in the late 2000s. And then around 2012, both of them had a breakthrough. The first one was the ability to recognize pictures. And there was a competition called ImageNet and there was a paper, colloquially known as the CATS paper, and the AI could recognize a picture of a cat for the first time. It's amazing. I mean, you think about how short of a time it's been since 2012, right? 14 years. And we've come from, oh, wow, it can recognize a cat to oh my goodness, it can like break every cyber code in the world. So that was the deep learning side. And then in the game playing, reinforcement learning side, DeepMind Demis company produced a system called DQN which played Atari games. I don't know if you remember Pong or breakout or seaQuest or one of these ones. And essentially the computer could play at a human or better than human level at all these different Atari games.

[Robert Peston]

And so that's the initial breakthrough. Are we already then. Because if we look at it today, there is definitely a race on. We've obviously got DeepMind and Google, and we've got OpenAI and we've got Anthropic and in China we've got a bunch of competitors as well. And Deep Seq is the one that most people have heard of is, is it that. Is this, does the race begin there?

[Sebastian Mallaby]

So I think round one of the race you can identify as being 2013 going into early 2014 because there was a bidding war to buy DeepMind. You know, Google was the one who bought it, but actually Meta, which was then Facebook wanted to buy it and then Elon Musk wanted to buy it. And so three of the biggies wanted to get Demis and Demis chose one of them. And then, you know, can I just

[Robert Peston]

ask you on that because it's something we've obviously talked a lot about on this podcast, which is in a way what a sort of national tragedy it is for the UK that DeepMind and Demis felt that they could not finance their ambitions in the uk. Was he right that in order to achieve what he felt he had to achieve, there was no route to remaining British?

[Sebastian Mallaby]

I think that's true. There wasn't an alternative because you needed to be acquired by a company with A, deep pockets and B, a ton of computing power.

[Robert Peston]

I can ask you. So I'm sure that's right. That wasn't available then. So the, the obvious follow up question is if the equivalent of DeepMind were facing the same conundrum, the same quandary today, would it be possible for them to remain British today? Because I'm not sure they necessarily could.

[Sebastian Mallaby]

Well, I'll make two points. So one of them is yes, today American venture capital, or we should just say global venture capital, A has more money than it used to and B is quite happy to show up in Britain and back a company like say Wise, formally transferwise or other British startups. And so you can raise a lot of capital and stay in the uk.

[Robert Peston]

So let's just on that because we might come back to the significance of this later. So the fact that, so for example, we've already talked about Reinforcement Learning and David Silver, you know, he's just created this business called Ineffable Thinking and we might talk about actually the significance of his technology versus the sort of Hasabis Gemini approach, because I think there is, there's a very interesting sort of new battle going on for what the future of AI will be. But you know, he is raised, you know, he's raised, seems to be raising an enormous amount of money, but it's all coming out of Sequoia in America. You don't think, you don't think that matters where the money comes from. That doesn't make his business in a sense an American business. If it's venture money you're not worried about the source of the funding?

[Sebastian Mallaby]

Well, he'll still be the CEO. He'll be in control. So it is a bit different. But I would make a bigger point, which is that I think, as you know, from a British patriotic point of view, what we should care about is having great science companies headquartered in Britain. Don't you want the profits staying here

[Robert Peston]

and the tax being paid here?

[Sebastian Mallaby]

Let's put it like this. You know, when Demis sold his company in 2014 to Google, over the next 10 years, Google poured in nearly a billion dollars per year of research and development funding into London. Into London, yeah, because all of DeepMind's operations were in London. And so we could regard this as a victory for Britain, that it persuaded this American group, Google, to just rain down research funding onto Britain. It's great. Right? And in fact, they were quite hands off about the management of Google. They didn't really inter. I mean, of management of DeepMind. They didn't intervene in what Denis wanted to do very much. And so, you know, I think that's great because, you know, a lab of brilliant people remained in London and I

[Robert Peston]

suppose so I said, look, there's still an opportunity cost in the sense that you don't get the profit flows that generate the tax revenues and all the rest of it. That would have been British had there been a way of. I mean, look, I absolutely take the view. I think it's perfectly rational for him to do what he did when he sold more than 10 years ago. But I still think there was a

[Sebastian Mallaby]

cost to the uk, but there were no profits. That's the thing you say there was just money coming in for research.

[Robert Peston]

There are today massive.

[Sebastian Mallaby]

No, actually, look at OpenAI as your experiment, your thought experiment. OpenAI is losing money hand over fist, right? It's spending hundreds of billions on research and the revenues are tiny compared to the expenditures. So it's losing money. I actually think it's going to go best. So even in Silicon Valley, it may not be very easy to create an independent, freestanding AI company. So had DeepMind tried to do that, would the taxpayer in Britain have had any relief because DeepMind was paying taxes on its profits?

[Robert Peston]

You just made quite a big claim, which I can't let go by. Why do you think OpenAI is going to go? I mean, obviously they've had to scale back some of their financing recently, but why do you think they're actually going to go bust?

[Sebastian Mallaby]

Because, you know, they produce forecasts for their clients, for their, for their investors, and these are always leaked. And if you look at the leaked forecasts, their own estimates have been that they're going to burn $660 billion before they start making a profit.

[Robert Peston]

So it's 100. Let's just say that number again.

[Sebastian Mallaby]

Yeah, it's a good point. 660 billion with a B. I mean this is insanely.

[Robert Peston]

They're going to lose that amount of money.

[Sebastian Mallaby]

That's how much they're going to burn in other. Lose that money.

[Robert Peston]

Negative cash flow.

[Sebastian Mallaby]

Negative cash flow because their revenues are paltry. I mean they're growing, but from a very low base. They got almost a billion users, but only 5% pay them money. Nearly all of them pay nothing. And so they can probably scale back some of that 600 billion of intended investment. And that's why they've cut their project in Britain, the Stargate project. That's why they've cancelled their whole video generation thing. Sora. They're going to be having to tighten their belts.

[Robert Peston]

You will have read that very long New Yorker character destruction of Sam Altman, where putting it in crude terms over thousands of words, it basically says he's a pathological liar. There's not a lot more to be said about that about it. Or actually no, they would say a power mad pathological liar. I think what they would say. And a lot of the testimony came from, you know, this blokes, Ilya Suskova who worked with him for years and you know, again, a very senior person within this, within this industry. I mean, do you think that will have an impact on the confidence of investors? And you know, to go back to your question about the challenges that OpenAI faces, what did you make of that article?

[Sebastian Mallaby]

Well, look, I mean, it was in some ways a very good assembly of stuff that people knew already. I mean, people knew he was a pathological liar. This was sort of fairly common line of analysis in Silicon Valley. I would say that what's going on with OpenAI is that they've raised a record amount of money, the most in the history of capitalism as a private company. That game is now up. And you can see this in the secondary market for their stock. When you have private markets, it's not like there's no stock exchange, you can't trade it, you can't see the price. But people do try and trade stock kind of one to one. And there are these exchanges that do that. And if you look on those, you see that the secondary market price of OpenAI shares is a lot below the announced official price. So in other words, so the implementation,

[Robert Peston]

the implied funding round price is way above where it's actually trading in shadow form.

[Sebastian Mallaby]

Correct. Whereas with Anthropic, its rival, it's the other way around. Anthropic secondary shares are above the official valuation. So that means that the insiders in Silicon Valley, the kind of private investors, the venture capitalists and so forth, know perfectly well that that OpenAI is in deep trouble. So deep. OpenAI's escape hatch was going to be to go public and start tapping the retail investors who don't know so much. And if you want to tap the retail investors, it's not helpful if the New Yorker publishes thousands of words on how the CEO is a liar, because that will percolate out into the public consciousness and make it harder to go public.

[Robert Peston]

And just to be. I'd like to move on or back to the book in a second. But were it to be on the brink of going bust, Microsoft wouldn't rescue it.

[Sebastian Mallaby]

Oh yeah, absolutely. I think that either Microsoft or Amazon or somebody would snap it up at a discount because it's a great.

[Robert Peston]

It wouldn't disappear.

[Sebastian Mallaby]

Correct.

[Robert Peston]

Okay, so we're not. Yeah, we're just talking about, you know, some people losing some money.

[Sebastian Mallaby]

Essentially. I think there's no AI bubble, but there is an open AI bubble. It's a specific company that has a problem.

[Robert Peston]

Okay. It's very interesting. It feels to me as though we're only on the early chapters of this conversation, as it were. Tons more to talk to you about. We'll be back in a minute or two.

[Greg Jackson]

This episode is sponsored by Starling, the bank that helps you organize your money, build great habits and stay in control of your spending. Now I talk a lot about financial literacy and its importance in our economy. You know, giving people knowledge but also confidence with money too. And Starling reckons anyone can be good with money. And you can start simply by checking your balance daily. It gets gets easier every day and it takes the mystery out of it and then the real value comes from digging into the details with tools like Starling Spending Intelligence. So this is an AI powered search bar within Starling Current accounts where you can ask a question about your spending habits and get an instant answer in app. It helps deepen your knowledge and make more informed money decisions. It's a little like having a financial co pilot in your pocket mapping out exactly where your money goes. Search Starling bank to find out more Good with money starts here.

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[Robert Peston]

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[Sebastian Mallaby]

How does, how has that happened? It's remarkable. I mean, you know, Dariama Day was one of the top scientists at OpenAI before he left. He took quite a big team with him, a dozen or so people. So he, he stole quite a big chunk of the brain trust at open. Initially, OpenAI stayed ahead, but now, as you say, Anthropica's caught up. I think part of the secret there is that they cleverly focused on high value products which businesses were going to pay money for. And notably coding. They are very, very good at coding. They've just released this, or they haven't released it, but they've announced it. This cybersecurity model for Seraphim.

[Robert Peston]

Mythos.

[Sebastian Mallaby]

Yeah, correct. And the idea there, well, at least part of the idea is that's going to be a huge money spilling for them. I mean, if you create something and you basically say to all of the corporations in the world, if you don't have this system to get the bugs out of your own code, you will be hacked. Imagine how much those businesses will pay you for access to the software. A lot.

[Robert Peston]

It's created within the financial world a lot of fear. Bloomberg was reporting, for example, that Scott Bezant, the Treasury Secretary, had brought in the heads of various banks to talk to them about what AI could now do and in particular what this particular service Mythos can do is essentially identify all the flaws in their software. And if it got into the wrong hands, they would be hacked and brought down. And they might think that their systems are secure. They almost certainly aren't. And as I say, this AI would be able to infiltrate them within seconds, as it were. So this seemed terrifying. But as you say, the corollary of that is, and as I understand it, they've more or less been instructed to use Mythos and actually check themselves out, as it were. But you're right, the corollary of that is, I suppose any organization anywhere in the world is not going to want to buy it.

[Sebastian Mallaby]

Yeah, yeah, yeah. And one of the interesting questions is whether they'll be allowed to buy it, because the.

[Robert Peston]

Why?

[Sebastian Mallaby]

Well, so. All right, let me just frame this. So there used to be two kinds of ways of releasing artificial intelligence models. There was open weight, where you just let people download it and do whatever they want. Then there were proprietary models where you let them use it, but they can't download it, and you still control it. Now we have a new thing which Anthropic has just invented for Mythos, and that's basically, I would call it restricted proprietary, where they retain it, but they restrict. They have a kind of special invitation list of other companies that are allowed to get their hands on it and use it and use it to debug their own software.

[Robert Peston]

Can I just ask you on that, Can Anthropic see that you're using it for defensive purposes rather than aggressive purposes? Because obviously the thing that would worry or should worry all of us is that somebody gets their hands on Mythos, and they might try and make their own fortress secure, but they might also simultaneously say, well, I know that business over there that's been causing us problems. Let's just bring it down. Realm.

[Sebastian Mallaby]

Yeah, I think that might be a bit obvious if they did that. I mean, I think the idea is you pick 10 or something, whatever the number is. Companies like Apple, you know, companies that have operating systems, companies that offer web browsers, like Google does, and you give it to those players who have huge reputational risk if they do something bad with it and they're going to use it defensively. But then the problem is going to

[Robert Peston]

be, how do you stop it from getting into the hands of a malign actor?

[Sebastian Mallaby]

Well, if you only have it, you know, give it to sort of eight or ten companies, maybe you can.

[Robert Peston]

You can stop it leaking.

[Sebastian Mallaby]

Okay, But. But. But the pressure is going to be. There's going to be lots and Lots of other companies who say, hey, what about me? I want it too. And then there'll be local government entities who say, I don't want to be hacked. And then, you know, everybody will be lining up saying, me too, me too, I want it, I want it. Can a company like Anthropic deny hordes of supplicants who say, well, you know, that's not fair. You've only given it to this oligopoly of insiders. And then if you start handing it out more widely, then it will leak. So I think it's not a tenable position. Their vision is restricted, proprietary indefinitely. We will just not release it beyond institutions we trust. Yeah. And I just don't know if that's politically sustainable.

[Robert Peston]

But also in a world where there is this rampant competition, presumably at some point some other. I mean, why do we not think the Chinese are going to develop their equivalent version of this?

[Sebastian Mallaby]

Totally, yeah. Are very good at that. I mean, they basically do what's called distillation, where every time there's a cutting edge American model, they reverse engineer it.

[Robert Peston]

Yeah. And they've done that in all sorts of other areas for years, very successfully. Can I just ask you, though, I suppose a question that might make one feel slightly more optimistic, which is one of the things that, you know, having followed Amede for a while, you know, is clear about him, is he definitely takes safety seriously.

[Sebastian Mallaby]

Right.

[Robert Peston]

And I wondered whether something that might make us feel a bit better about this world, the fact that Anthropic seems to be doing really relatively well is because it is run by somebody who, I think we believe takes safety seriously.

[Sebastian Mallaby]

Yeah, I think that's right. I think, you know, being sort of branded as safe means it's easier to attract lots of scientists who would really rather not destroy the world. And Demis has that too. I think, you know, his type of safety approach is different to Dario Amadeus, but it's more behind the scenes. You know, I think he, you know, he'll be at the moment, I'm guessing, you know, trying to persuade other labs to come together and agree on some joint sort of safety standards for new models. And the Mythos power, which is frightening, will give him more talking points when he's trying to persuade others to come together. And so, I mean, I think Demis is pushing for safety behind the scenes. Dariama Day is a bit more out there and public about it, but they share the same safety concerns. They share. They're both PhD scientists, whereas Sam Altman dropped out of university and doesn't have a degree. So, you know, I think there are differences of how much these people, you know, are white hatted or black hatted.

[Robert Peston]

We're in the Wild west, as you point out. As you point out, one of the things I like about your book is, you know, there are these characters who turn up when demisabis is young. So he meets this bloke, David Silver, another sort of Cambridge super brain.

[Sebastian Mallaby]

Correct.

[Robert Peston]

I mean, one of the sort of most poignant stories is Silver joins DeepMind at the beginning, but because he's been so burned by the early experience of working with Asabis, you reveal that Silver refused to take any equity into Heat Mind, which was a very, very expensive decision, as it were. You know, meant that he was many millions of pounds poorer than he would otherwise be anyway. But nonetheless, they have this interesting relationship over many, many years. And he does join DeepMind and he ultimately is responsible for the great Alpha Ghost triumph, which we've already talked about. But his vision, and rather than me summarizing, I'd much rather hear it from you, his vision of how you get to artificial general intelligence is pretty different from Demis Asabis because he, I think, and I think the phrase that people use, he is more interested in what I think are now widely referred to as this world model approach, which is, as I understand it, is much more about AI learning in the way that sort of humans learn, which is sort of by trial and error and reacting rather than just starting with this unlimited database and then seeing patterns. But am I describing it correctly?

[Greg Jackson]

Yeah.

[Sebastian Mallaby]

I mean, humans learn broadly in two ways. They can read a book, go to the library, understand things through some description. So you're getting it secondhand, but that can be a very efficient way of learning. Or you can go out and you want to decide to, you know, understand geology or something. So you go and dig a hole, look at the rocks and try and figure it out. Or more practically, when we're talking about world models, which is sort of how does the world work? You know, you pick up a glass, it's got water in it. You know, if you turn it over, the water will come out. If you drop it on a hard floor, it'll shatter. You know, all these things about the physical world because you've done them as a human. And so with AI, there's a bit of that too. It can look at data, which you just suck up from the Internet and learn things secondhand.

[Robert Peston]

And that seems to me to have been the sort of conventional approach for many of these models over the last Few years.

[Sebastian Mallaby]

Correct.

[Robert Peston]

Right.

[Sebastian Mallaby]

But you can also learn through trial and error. And what I would. I'd say actually.

[Robert Peston]

And Silver is more in the trial and error camp, is that right?

[Sebastian Mallaby]

I would say Silva is a trial and error maximalist. He really, really wants to use that as much as possible. On the other hand, Ilya Satskever, who you mentioned, who was the Chief Scientist at OpenAI, now also gone off to do a startup because he can't stand Sam Altman, you know, he's a maximalist on deep learning, on learning from data. Okay. And I would actually say that Demis.

[Robert Peston]

So they're the sort of. They're the two poles.

[Sebastian Mallaby]

They're the two poles and Demis is kind of in the middle. A lot of what DeepMind has done has combined deep learning with reinforcement learning. And the balance of the two changes according to what point in AI history you're in. But I think it's useful for people. AI is sort of the headline that everybody knows now underneath the hood there are these two schools, reinforcement learning and deep learning. And if you can get that in your head, you're a step ahead of others.

[Robert Peston]

But what you're broadly saying is that Demis is sort of eclectic, as it were, in the sense that his approach is to exploit both.

[Sebastian Mallaby]

Yeah. And it's interesting because he did a PhD not in computer science, but in neuroscience. And he did that because he thought the human brain was the existence proof for intelligence. So if you wanted to build artificial intelligence, you should understand human intelligence first. And the main takeaway for him about doing neuroscience was that that the brain has these different bits to it. Right. It's got a hippocampus, it's got a cerebellum, it's got different components, and it's the way those components combine that produces the magic of human intelligence. And so his view has always been that with machines you're going to decompose intelligence into a bunch of different functions. And there's a whole area of memory, another area of planning, another area of recognizing, using vision. He's always looking for the eclectic, brilliant combination. Other people are more trying to push one strategy. Different people have different emphases.

[Robert Peston]

This is a very trite question, but I'd love to know what you think. Is he a genius like Newton or Feynman, or is he just an exceptionally talented person in terms of understanding the way science is going, recognizing other brilliant people exploit. Because he has had a team of absolutely brilliant people around him all the way through. Right. You know, he's not Newton sitting Under a tree on his own. You know, everything he's done has been a team effort. I mean, you know, maybe it doesn't matter whether he's a genius or not, because, you know, but I'm just. I'm quite interested in these personal questions.

[Sebastian Mallaby]

Yeah, yeah. So, look, clearly he's amazing in terms of the breadth. Right. As you said. And he is both somebody who can lead a company, set a company up, be an entrepreneur, be a normal person you can relate to. Riff about movie history and also he's a scientist who has a Nobel Prize.

[Robert Peston]

Did you take a view? Because he's won. He won the Nobel Prize for AlphaFold, this extraordinary AI achievement of being able to describe every protein. But there are some people who say that the fundamental research was done by John Jumper, not by him. What's your view on that?

[Sebastian Mallaby]

It's true. John Jumper did more of the research.

[Robert Peston]

Research.

[Sebastian Mallaby]

It's also true that he was put in a position to do that research by Demis Hassabis, making a judgment that the research was going to work. So I think Demis may have had specific conversations with John Jumper that prompted him in a useful direction. But the bigger thing is that there was this moment, after two years of researching AlphaFold, when the team leader, who was called Andrew Senior, told Demis that we're stuck. We've got the best system in the world, We've beaten all our rivals in this space, but we haven't actually solved the shapes of all proteins in nature. But we know what we're not going to. It's too hard. We have to stop. We have to declare victory and move on. And Demis went and sat in the meetings of the team, listened to the scientists debating, and he had this fluidity test. If the ideas were flowing fluently, then his judgment would be, well, there's lots of things we could explore, so we should go on. And he listened. He could understand the debate perfectly well. I mean, he obviously was in it himself and he made the correct judgment that you should go on and that furthermore, you should switch out the leader. Andrew Senior went to do something else. John Jumper became the new boss of that team and it worked. So I think.

[Robert Peston]

So he's sort of like Oppenheimer in the Manhattan. Yes, Oppenheimer doesn't win a Nobel Prize. He's, you know. But everybody said he was absolutely brilliant. But what he was good at was bringing again all these brains together, adjudicating about the right way forward and all that.

[Sebastian Mallaby]

But I don't think you assemble and juggle the Brains. Unless you yourself have an amazing brain.

[Robert Peston]

I know, I think we recognize both have amazing brains. And look, I am definitely not qualified to judge whether or not he really is a genius. You've spent a lot of time with him and you've thought about it. I just wonder what you thought.

[Sebastian Mallaby]

I was in the same position as you. And so what I did is I actually, actually talked. I interviewed his postdoc supervisor at mit, a guy called Tommaso Poggio. And I was talking to Mass Apoggio, who is this like, you know, revered professor at mit. And I said, well, what did you think about Denis? And he said, well, you know, in my career academically, I've known many people who have got the Nobel Prize. Some of them were very clever and lucky because they happened to choose as a research subject which was turned out to be soluble and important. So they got, because they got the prize, because they chose the right topic. Others, he said, were so off the charts brilliant that they would have got whatever they did. And so for example, he said there's Richard Feynman and there's Demis Assarbis. So you know, I mean, so he

[Robert Peston]

puts him in the same category as Poggio.

[Sebastian Mallaby]

Puts him in the same category as Feynman.

[Robert Peston]

Okay, well that's, yeah, that's a pretty high accolade.

[Sebastian Mallaby]

That's a testimony we should pay attention to.

[Robert Peston]

All right, so having got that testimony, the epilogue of your book is a very interesting conversation with Hasabis about how you understand the universe. And he describes himself as the disciple of Turing. And he believes that what he calls classical computers and the classical approach to digital development, and in this case the creation of a super intelligence AI will be enough for him at some point point to understand the entire universe. And he doesn't need a quantum computer. But one of the things I was going to ask you is does he actually think, I mean, you know, Google is investing an enormous amount of money in quantum computing. Does he think that's a dead end? Does he just think it's a side issue? What does he think about quantum computing?

[Sebastian Mallaby]

Well, to be fair, I think he says that there are some specific math problems where quantum computers will be useful. When you've got a system that really works, what will it do? The first answer is, well, it's going

[Robert Peston]

to crack everybody's code and there'll be no computer in the world that's safe.

[Sebastian Mallaby]

Essentially correct. Which raises the question about why do we want quantum computing? But anyway, but Demis view is that you can get further with classical computing than people suspected. And it relates in a fascinating way to how you see sort of like the nature of the universe. Einstein's sort of classical physics seems to break down at a micro, micro, tiny, tiny scale. And that's where apparently quantum effects are thought to kick in. And there's a debate in physics as to, are we sure about that or do we just think that? And equally, in the human brain, there's a tradition of debating, you know, are we basically just ones and zeros in our head, or do we have what some people call quantum woo woo?

[Robert Peston]

And this is begin rose versus.

[Sebastian Mallaby]

Precisely. Precisely. So what's fascinating me about Demis's worldview is that it kind of connects. How do our brains work? How does the universe work? How do computers work? And the way he sees these things, they're all linked up.

[Robert Peston]

One of the questions that I wondered if you came away the last time you had a long conversation with Hasabis was the end of last year. Is that right, or.

[Sebastian Mallaby]

Yeah, I mean, it was towards the end of last year. It was the proper one, I think. We went on for three hours arguing about various things. I was going to write and he was objecting, but we ended amicably. And then we did see each other again in January. And tomorrow we're going to appear together on a stage that'll be in King's Cross.

[Robert Peston]

So where do you, you know, for all I know, you know, you'll have a different view of this tomorrow when you see him. But right now, how far does he think we are from artificial general intelligence? You know, the AI that is significantly brainier than any of us and godlike in that sense.

[Sebastian Mallaby]

So he is on the end of the spectrum, which puts it further out than, say, Dario Amodei does. Dario Amodei would say three years or something. Demis likes to say five years plus.

[Robert Peston]

And you think he's still there?

[Sebastian Mallaby]

Yeah, I think he is. And I feel a little suspicion that he loves scientific research so much that he doesn't want it to stop. So he keeps on saying, oh, we've got another five years of fun here. He can't bear for the idea. So he's always saying, we need a couple more incredible breakthroughs. I mean, amazing breakthroughs. Maybe I'll get another Nobel Prize in brackets. And he does, by the way, want a second Nobel Prize. That's not a joke.

[Robert Peston]

He appears to be competitive in a way that many of us might aspire to. I don't know. Anyway, he is remarkable in so many different ways. We talk about this Issue of the economic transformation, how many jobs are gonna be replaced and all the rest of it endlessly. On this podcast, does he believe in the so called world of plenty? The idea that in the end humans will not have to work at and the marginal cost of production will be zero because it'll all be done by machines and robots. Is that something he believes in?

[Sebastian Mallaby]

In the long term? Yes. I mean, he told me, quite frankly, and it's amazing how frank he is about these things, that his worldview on this was formed by a science fiction series he read as a teenager called the Culture Series by Ian Banks.

[Robert Peston]

And in this series, it's a great series.

[Sebastian Mallaby]

Yeah. Okay, sounds like you read it too. So there are all these different plans, planets with different kinds of AI beings. And the AIs, you know, go around on different planets and so do the humans because there's rockets all over the place and you can go sample different ways of living on different planets. And basically the point is the AIs are very, very clever, but they don't bother humans, but they do create plenty. So it's win, win. And so I think Demis has always been, you know, inclined to say people massively underestimate still today how transformative AI is going to be. We're going to not need corporations because if you have abundance, what is money, right? And therefore if there's no money, is there a corporation? I mean, all of these things he thinks sort of melt away in some theoretical future. I mean, the interesting thing, of course, is the next 10 years and what the heck does it feel like to get there? And the transition could be brutal.

[Robert Peston]

Yeah, I mean, again, and we won't go there now, but one of the things that is, I regard it as an extraordinary frustration and again, we talk about a lot on the podcast is there is no doubt that we are living through revolutionary change. And we certainly don't have a government in Britain that is remotely taking these challenges seriously. But it's hard anywhere in the world to see a government that takes these challenges seriously. Which is probably an okay moment to call this particular part of the conversation to a close. That was incredibly enjoyable. We'll have you back on. And just to reiterate, and to be clear, I don't say that all that often about the books we talk about on this podcast. Honestly, it's a great read, it's very entertaining and it's got important ideas in it. So thanks very much for joining us today. It's about the Sebastian Malaby. And that's it from this edition of the rest is money. See you soon. You can't reason with the sun. Trust us. We've tried. This summer, it's time to put that angry ball of fire on mute. Columbia's Omnishade technology is engineered to protect you from the sun's harsh rays that can burn and damage your skin. The sun is relentless. Relentless. But so is our gear. Level up your [e-mail] to spend more time outside and less time slathering on aloe lotion. You're welcome, Columbia. Engineered for whatever.