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you play this forward in your brain.
You you've been in the tech industry for a

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long time and from looking at your work,
you it feels like you're describing this

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as the most sort of transformative,
potentially harmful technology that

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humans have really ever seen. You know,
maybe alongside the nuclear bomb, I

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guess, but some would say even

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potentially worse because of the nature
of the intelligence and its autonomy.

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You must have moments where you you
think forward into the future and your

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thoughts about that future aren't so rosy.

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>> Well, >> because I have
those moments. Yes, but

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but let's let's think let's answer
the question. I said think five years. In

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five years, you'll have two or three
more turns of the crank of these large

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models. These large models are scaling

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with ability that is unprecedented.

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There's no evidence that the scaling has

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laws as they're called have begun to

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stop. They will eventually stop,
but we're not there yet. Each one of these

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cranks looks like it's a factor of two,
factor of three, factor of four of

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capability. So let's just say turning

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the crank all of these systems get 50

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times or 100 times more powerful in and

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of itself. That's a very big deal
because those systems will be capable of

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physics and math. You see this with O.1

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and um and open AI all the other things

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that are occurring. Now what are the

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dangers? Well there's the most obvious
one is cyber attacks. There's evidence

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that the raw models, these are the ones
that have not been released, can do what

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are called day zero attacks as well or
better than humans. A day zero attack is

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an attack that's unknown. They can
discover something new. And how do they

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do it? They just keep trying because
they're computers and they have nothing

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else to do. They don't sleep. They don't
eat. They just turn them on and they

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just keep going. Um, so the so cyber
is an example where everybody's concerned.

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Another one is biology. Viruses are
relatively easy to make and you can

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imagine coming up with really bad viruses.
There's a whole team. I'm part

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of a commission. We're looking at this
to try to make sure that doesn't happen.

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I already mentioned misinformation.

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Another probably negative,
but we'll see is the

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development of new forms of warfare.

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I've written extensively on how war is

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changing. And the way to understand

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historic war is that it's the

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stereotypically the the soldier with the
gun, you know, on one side and so forth.

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World War trenches. You see this, by the
way, in Ukra in the Ukraine fight today

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where the Ukrainians are holding on
valiantly against the Russian onslaught.

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But it's sort of, you know, mono ammono,

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you know, man against man. Sort of all

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of the stereotypes of war. So in a drone
world, which is the sort of the fastest

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way to build new robots is to build
drones, you'll be sitting in a command

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center in some office building connected
by a network and you'll be doing harm to

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the other side while you're drinking
your coffee. Right? That's a change in

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the logic of war. Um, and it's
applicable to both sides. I don't think

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anyone quite understands how war will

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change, but I will tell you that in UK
in the Russia and Ukraine war, you're

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seeing a new form of warfare being

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invented right now, right? Um, both

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sides have lots of drones. Tanks are no

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longer very useful. A $5,000 drone can

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kill a $5 million tank. Um, so that's
called the kill ratio. So basically,

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it's drone on drone. And so now people
are trying to figure out how how to have

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one drone destroy the other drone.

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Right? This will ultimately take over

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war and conflict in our world in total.

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>> You mentioned raw models. This is
a concept that I don't think people

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understand exists. The idea that there's

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some other model that's the raw model
that is capable of much worse than the

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thing we play with on
our computers every day.

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>> It's important to establish how
these things work. So you the way these

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algorithms work is they have complicated

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uh training things where they suck all

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the information in and they uh one we
currently believe we've sort of sucked

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all of the written word that's available.
It doesn't mean there isn't

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more but we've we've literally done such
a good job of sucking everything that

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humans have ever written. It's all
in these big computers. And when I say

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computers I don't mean computers. I mean
supercomputers with enormous memories

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and the scale is mindboggling. Uh,
and of course there's this company called

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Nvidia which makes the chips which
is now one of the most valuable companies

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in the world. Um, surprisingly so

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incredibly successful because they're so
central to this revolution and good for

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Jensen and his team. So the important

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thing is when you do this training it
comes out with a raw model, right? It

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takes six months and you know you wait
24 hours a day you can watch it. It gets

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close to there's a measurement that they
use called the loss function. when it

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gets to a certain number, they say,

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"Good enough." So then they go, "What do

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we have?" Right? What do we do? Right?

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Um so the first thing is let's
figure out what it knows.

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So they have a set of tests and of course
it knows all sorts of bad things

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which they immediately then tell it not

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to answer. To me the most interesting

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question is in over a fiveyear period

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these systems will learn things that we
don't know they learn. How will you test

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for things that you don't know they know?

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The answer in the industry is that they

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have incredibly clever people who sit
there and they fiddle, literally fiddle

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with the networks and say, "I'm going to

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I'm going to see if it knows this.

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I'll see if it can do this." And then
they make a list and they say, "That's

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good. That's not so good." Right?
So all of these transformations. So for

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example, you can show it a picture of a
website and it can generate the code to

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generate a website. All of those were
not expected. They just happened. It's

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called emergent behavior.

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>> Scary.

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>> Scary but exciting. And so far um the

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systems have held. The governments
have worked well. Um the these trust and

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safety groups are working here in the

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UK. Um one year ago was the first trust

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and safety conference. Um the government
did a fantastic job. The team that was

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assembled was the best of all
the country teams here in the UK. Um, now

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what's happening is these are happening
around the world. The next one is in

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France in uh early February,
and I expect a similar good result.

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>> Do you think we're going to have
to guard I mean, you talk about this, but

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do you think we're going to have
to guard these raw models with with guns

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and tanks and machinery and stuff?

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>> I worked for the Secretary of Defense
for a while. Uh, in my in Google, you

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could spend 20% of your time on other
things. So I worked for the secretary of

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defense to try to understand the US

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military and um one of the things that

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we did is we visited a plutonium um

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factory. Plutonium is incredibly
dangerous and incredibly secret and so

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this particular base is inside
of another base. So you go through the

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first set of machine guns and then you
have normal thing and then you go into

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the special place with even more machines,
guns and even because it's so

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secure. So the the metaphor is do you

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fundamentally believe that the computers
that I'm talking about will be of such

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value and such danger that they'll have
their own data center with their own

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guards which of course might be computer
guards. But the important thing is that

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it's so special that it has to be
protected in the same way that we

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protect nuclear bombs and prolifer uh

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and programming. An alternative model is

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to say that this technology will spread
pretty broadly and there'll be many such

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places. If it's a small
number of groups, the

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governments will figure out a way to do
deterrence and they'll figure out a way

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to do non-prololiferation. So,
I'll make something up. I'll say

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there's a couple in China, there's a few
in the US, there's one in in Britain. Of

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course, we're all tied together between
the US and Britain and maybe in a few

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other places. That's a manageable
problem. On the other hand, let's

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imagine that that power is ultimately so

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easy to copy that it spreads globally

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and it's accessible to for example
terrorists. Then you have a very serious

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proliferation problem which is not yet

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solved. This is again speculation

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>> because I think a lot about adversaries

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in China and Russia and Putin and and I

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think I know you talk about them being
a few years behind, maybe one or two years

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behind, but they're eventually going
to get there. They're eventually going to

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get to the point where they have these
large language models or these AIs that

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can do these day zero attacks on our

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nation and they don't have
the same in like sort of

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social incentive structure if they're a

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communist country to protect and to

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>> um guard against these things. Are you
not worried about what China's going to

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do? >> Um I am worried
and I'm worried because

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you're going into a space of great power
without fully defined boundaries. What

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Kissinger and we talk about this
in the book the the genesis book is

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fundamentally about what happens
to society with the arrival of this new

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intelligence and the first book we did

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age of AI was right before chat GPT so
now everybody kind of understands how

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powerful these things are we talked
about it now you understand it so once

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these things show up who's going to run

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them who's going to be in charge how

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will they be used so from my perspective

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I believe at the moment anyway that

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China will behave relatively responsibly

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and the reason is that it's not in their

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interest to have free speech

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in every case in China when they have a

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choice of giving freedom to their
citizens or not they choose non-freedom

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and I know this because I spent through

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all their I spent all that time dealing

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with it so it sure looks to to me like

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the Chinese AI solution will be

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different from the west because of
that fundamental bias against freedom of

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speech. Because these things are
noisy. They make a lot of noise.

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>> They'll probably still
make AI weapons though.

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>> Well, on the weapon side, you have to

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assume that every new technology is

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ultimately strengthened in a war. Um the

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tank was invented in World War I. At the

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same time, you had the initial forms
of uh airplanes. Much of the Second World

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War was an air campaign which

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essentially built many many things. And
if you look at the the there's a a book

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called Freedom's Forge about the

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American U structure. According to the

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book, they ultimately got to the point
where they could build two or three

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airplanes a day at scale. So in an

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emergency, nations have enormous power.

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>> I get asked all the time if everyone's
if anyone's going to have a job left to

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do because this is the disruption
of intelligence and whether it's people

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driving cars today. I mean, we saw
the Tesla announcement of the robo taxis,

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whether it's accountants, lawyers,
and everyone in between, that's job or

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podcasters.
Are we going to have jobs left?

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>> Well, um, this question has been
asked for 200 years. Um, there was

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[clears throat] there were the lites
here in Britain way back when. And

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inevitably when these technologies come
along, there's all these fears about

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them. Indeed, with the lites, there were
riots and people, you know, destroying

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the looms and all of this kind of stuff,

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but somehow we got through it. So um my

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own view is that there will be a lot of

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job dislocation

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but there will be a lot more jobs not

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fewer jobs and here's why we have
a demographic problem in the world

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especially in the developed developed
world where we're not having enough

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children. Uh that's well understood.
Uh furthermore we have a lot of older

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people and and the younger people have
to take care of the older people and

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they have to be more productive. If you
have young people who need to be more

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productive, the best way to make them
more more productive is to give them

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more tools to make them more productive.

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Whether it's a machinist that goes from
a manual machine into a CNC machine or

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in in the more modern case of a
knowledge worker who can achieve more

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objectives. We need that productivity
group. If you look at Asia, which is the

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centerpiece of manufacturing, they have
all this cheap labor. Well, it's not so

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cheap anymore. So, do you know what they
did? They added robotic assembly lines.

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So today when you go to China
in particular, it's also true in Japan and

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Korea, the manufacturing is largely
done by robots. Why? Because their

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demographics are terrible and their cost

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of labor is too high. So the future is

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not fewer jobs. It's actually a lot of

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jobs that are unfilled with people who
may have a job skill mismatch, which is

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why education is so important. Now, what

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are examples of jobs that go away?

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Automation has always gotten rid of jobs

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that are dangerous.
physically dangerous or ones which are

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essentially too repetitive and too
boring for humans. I'll give you an

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example. Security guards. It makes sense

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that security guards would become
robotic because it's hard to be a

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security guard. You fall asleep.
You don't know quite what to and these

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systems can be smart enough to be very
very good security. Now, these are these

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are important sources of income
for these people. They're going to have to

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find another job. Another example in
in the media in um Hollywood, everyone's

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concerned that AI is going to take
over their jobs. All the evidence is the

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inverse. And here's why. Um the stars
still get money, the producers still

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make money, they still distribute
their movie, but their cost of making the

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movie is lower because they use
more they use, for example, synthetic

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backdrops. So they don't have to build
the set. Um they can do synthetic

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makeup. Now, there are job losses there.

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So the people who make the make make the
set and do the makeup are going to have

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to go back into construction
and personal care. By the way, in America,

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and I think it's true here, there's
an enormous shortage of people who can do

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highquality craftsmanship, right?
Those people will have jobs. They're just

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different >> and they
may not be in Los Angeles.

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>> Am I going to have to interface with
this technology? Am I going to have to

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get a neural link in my brain? because
you we you you go over the subject of

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there being these sort of two species of

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humans potentially ones that do have
a way to incorporate themselves more with

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artificial intelligence and those
that don't and if and if that is the case

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what is the time horizon
in your view of that happening

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>> I think neuralink is much more
speculative because you're dealing with

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direct brain connection and nobody's
going to drill on my brain until it

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needs it trust me >> I
suspect you feel the same

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>> uh I I guess my o
my overall view is that um

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you will not notice

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how much of your world has been co-opted

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by these technologies because they will

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produce greater delight.

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If you think about it, a lot of life is

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inconvenient. It's fix this, call this,
make this happen. AI systems should make

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all that seamless. You should be able
to wake up in the morning and have coffee

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and not have a care in the world and have
the computer help you have a great

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day. This is true of everyone. Now, what

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happens to your to your profession?

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Well, as we said, no matter how good the
computers are, people are going to want

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to care about other people. Another
example, let's imagine you have Formula

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1 and you have Formula 1 with humans
in it, and then you have an a a robot

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Formula 1, which where the cars are
driven by the equivalent of a robot. Is

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anyone going to go to the robotic

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Formula 1? I don't think so. Because
of the drama, the human achievement and so

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forth. Do you think that when they run
the marathon here in London, they're

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going to have robots running with humans?
Of course not. Right? Of course,

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the robots can run faster than humans.

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It's not interesting. What is interesting
is to see human achievement.

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So, I think the commentators who say,
"Oh, there won't be any jobs. We won't

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care." I think they miss the point that we
care a great deal about each other as

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human beings. We have opinions. You have
an a detailed opinion about me having

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just met me met me right now and I
for you. We just sort of naturally set up

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your face, your mannerisms and so forth.

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We can describe it all right. The robot
shows up is like, "Oh my god, what

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another robot. How boring."
>> Why is Sam Alman working on the the

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founder of Open AI, one of the
co-founders of OpenAI, working on

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universal basic income
projects like Worldcoin then?

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>> Well, WorldCon is not the same thing as

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universal Bitcoin. uh um universal basic

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income. There is a belief in the tech

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industry that it goes something like

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this. The politics of abundance, what we

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do is going to create so much abundance

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that most people won't have to work
and there'll be a small number of groups

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that work who typically these people
themselves and there will be so much

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surplus everyone can live like
a millionaire and everyone will be happy.

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I completely think this is false.
I think none of what I just told you is

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false. But all of these UBI ideas come

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from this notion that humans don't
behave the way we actually do. So I'm

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I'm a critic of this view. I believe

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that that we as humans, so I'll give an

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example is um we're going to make legal

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the legal profession much much easier
because we can automate much of the

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technical work of lawyers. Does that mean
we're going to have fewer lawyers?

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No. The current lawyers will just do
more laws. They'll do more they'll add

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more complexity. The system doesn't
get easier. the humans become more

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sophisticated in their application
of the principles. We are naturally

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basically uh we have this thing called

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um basically reciprocal altruism.
That's part of us but we also have our bad

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sides as well. Those are
not going away because of AI.

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>> When I think about AI, this simple
analogy you often think of is say my IQ

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is Steven Barla is 100 and there's
this AI that's sat next to me whose IQ is

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1,000. What on earth would you want
to give Steven to do? because because that

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10,00 IQ would have really bad judgment

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in a couple cases because remember that

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the AI systems do not have human values

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unless it's added right I would much

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rather talk to you about something
involving a a moral or human judgment

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even with the thousand I wouldn't mind
consulting it so tell me the the history

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00:17:38,080 --> 00:17:42,157
how was this resolved in the past how
were these but at the end of the day in

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my view the core aspects of humanity
which have to do with morals and

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judgment and belief beliefs
and charisma, they're not going away.

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>> Is there a chance that
this is the end of humanity?

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>> No. Um, the way humanity does is much

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it's much harder to eliminate all
of humanity than you think. All the people

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that I've looked with on these
biological attacks say it's it takes

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more than one horrific pandemic and so

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forth to eliminate humanity. And and the
the pain can be very very high in these

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moments. Look at the World War I, World

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00:18:14,160 --> 00:18:17,117
War II, the holodore in uh Ukraine in

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00:18:17,200 --> 00:18:19,517
the 1930s, the Nazis. You know, these

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are horrifically painful things, but we

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survived, right? We we as a as
a humanity survived and we will.

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>> I wonder if this is the moment where
humans couldn't see past around the

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corner because, you know, I've heard
you talk about how the AIs will turn in,

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they'll be agents and they'll be able to
speak to each other and we won't be able

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to understand the language.
>> I I have a specific proposal on that.

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Um, there are points where humans should

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assert control and I've been trying
to think about where are they. I'll give

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you an example. There's something called
recursive self-improvement where the

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system just keeps getting smarter
and smarter and learning more and more

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things. At some point, if you don't know
what it's learning, you should unplug

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it. >> But we can't unplug them, can we?

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00:19:02,160 --> 00:19:05,597
>> Sure you can. There's a power plug
and there's a circuit breaker. Go and turn

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the circuit breaker off. Another

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example, um there's a there's a scenario

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theoretical where the system is so
powerful it can produce a new model

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faster than the previous
model was checked.

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>> Okay, that's another
intervention point.

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So in each of these cases um if the if

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agents and the technical term is called
agents, what they really are is large

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language models with memory and you can
begin to concatenate them. You can say

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this model does this and then it feeds
into this and so forth. You can build

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very powerful decision systems. We
believe this is the the the thing that's

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00:19:41,280 --> 00:19:42,797
occurring this year and next year.

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Everyone's doing them. They will arrive.

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The agents today speak in English. You
can see what they're saying to each other.

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They're not human, but they are
communicating what they're doing.

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English to English to English. As long
as, and it doesn't have to be English,

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but as long as they're human
understandable. But let's So the thought

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00:20:02,080 --> 00:20:05,437
experiment is one of the agents says,
"I have a better idea. I'm gonna

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00:20:05,520 --> 00:20:08,797
communicate in my own language that I'm
going to invent that only other agents

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understand. That's a good
time to pull the plug.

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>> What is your biggest fear about AI?

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00:20:15,280 --> 00:20:18,557
>> My actual fear is different from what
you might imagine. My my actual fear is

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that we're not going to adopt it fast
enough to solve the problems that affect

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00:20:21,600 --> 00:20:24,637
everybody, right? And the reason is that

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00:20:24,720 --> 00:20:27,437
the that if you look at every everyone's

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everyday lives, what do they want? They
want safety. They want health care. They

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00:20:32,400 --> 00:20:35,917
want great schools for their kids. Why
don't we just work on that for a while?

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00:20:36,000 --> 00:20:39,837
Why don't we make people's lives just
better because of AI? We have all these

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other interesting things. Why don't we

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00:20:41,680 --> 00:20:45,357
have a um a teacher that is an AI

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00:20:45,440 --> 00:20:50,397
teacher that works with existing
teachers in this language of the kid in

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00:20:50,480 --> 00:20:54,317
the culture of the kid to get the kid as
smart as they possibly can. Why don't we

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have a doctor or doctor's assistant

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00:20:56,160 --> 00:21:01,357
really that enables a a human doctor
to always know every possible best

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00:21:01,440 --> 00:21:04,477
treatment and then based on their
current situation, what the inventory

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00:21:04,560 --> 00:21:07,757
is, which country is, how their insurance
works, what is the best way to

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00:21:07,840 --> 00:21:11,517
treat that patient. Those are relatively
achievable solutions. Why don't we have

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00:21:11,600 --> 00:21:13,997
them? If you just did education and

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00:21:14,080 --> 00:21:17,037
healthcare globally, the impact in terms

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of lifting human potential
up would be so great,

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00:21:21,200 --> 00:21:23,597
>> right? that it would change everything.

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00:21:23,680 --> 00:21:26,557
It wouldn't solve the various other
things that we complain about about, you

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00:21:26,640 --> 00:21:31,197
know, this celebrity or this misbehavior
or this conflict or even this war, but

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00:21:31,280 --> 00:21:35,517
it would establish a level playing field
of knowledge and opportunity at a global

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00:21:35,600 --> 00:21:39,917
level that has been the dream for decades
and decades and decades. If you

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00:21:40,000 --> 00:21:41,757
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