For the last year, I’ve been wrestling with what AI sovereignty means for us, here, in Britain.
What does it mean in practice? Semiconductors have become a strategic chokepoint, but what does that actually mean when the Netherlands, which is home to ASML, the monopoly provider of the EUV machines that are critical to fabricating chips, cannot really even leverage this position. What does “sovereignty” look like when it’s interdependency all the way down?
Elsewhere, while the US AI capex buildout continues, is that the only strategy available or are there other approaches that suit Europe better, especially given our energy and compute constraints?
And then there’s state capacity, which is critical to industrial policy going well. What will it take for SovAI, the government’s new strategic AI venture fund, to succeed?
To explore these questions, I had a lot of fun catching up with my friend Lawrence Lundy-Bryan, who has just launched Europe’s first dedicated semiconductor fund, Cloudberry. He’s spent his career going deep on frontier technologies and has thought more than almost anyone I know about the interplay of AI progress, structural shifts in venture capital, and UK sovereignty. Lemme know what you think.
How to invest in AI sovereignty, with Lawrence Lundy-Bryan
Lawrence Lundy-Bryan is GP at Cloudberry, Europe’s first dedicated semiconductor fund. He also writes the State of the Future substack, which researches frontier technology analysis.
You just launched Europe’s first semiconductor VC fund. Why on earth would you do that?
[00:01:37] Lawrence Lundy-Bryan: The truth is I’ve jumped on the bandwagon here. Like Veera and Rene, my partners, did all the hard work. there’s a VC bet that I’m making, and then there’s a macro bet.
The VC bet is, there’s only gonna be two types of VC funds in a decade:
the capital agglomerators, the AUM, the Andreessen’s $15bn four, five funds or whatever. Sequoia, Benchmark, those guys that just raise all the money.And then specialists,
I’m not sure exactly the extent to which I think deep tech was a sort of the first wave, the first attempt to move away from just SaaS to understanding infrastructure atoms and deeper, technologies.
But even then, that’s still quite broad.
Yeah.
[00:02:21] Lawrence Lundy-Bryan: I mean what is, deep tech? It’s a meaningless term. you see some funds that just invest in quantum computing. Or funds that just invest in photonics or, nuclear fusion, I think the world, will be made up of lots of those micro funds, that just know one technology and market really deeply.
Number one, because you can actually deeply understand something to the same level as a founder.
Slightly lower than a founder.
We’ll come back to that.
[00:02:45] Lawrence Lundy-Bryan: You at least can pretend.
And so you understand something, but then also you can diligence something really well with your network.
So you can actually make good investments. And second, you can “add value” in a way that isn’t just air quotes because your LPs, or your former colleagues, or your previous investments are all part of that same ecosystem.
Yeah.
[00:03:06] Lawrence Lundy-Bryan: So you really can say, once we’ve invested, we’ll introduce you to, in our case, Global Foundries to help you tape out your chip.
Or in other cases, a hyperscaler CTO as a purchaser. my view is on the VC side, specialism is the place to be. And on the macro side, semiconductors is massively over, sorry, massively under invested in.
Over invested?
[00:03:27] Lawrence Lundy-Bryan: Was over... I mean NVIDIA’s price, potentially, but that’s irrelevant.
just from a VC perspective, it’s like a huge gap in semiconductors. And I think over the next decade we’ll start to see, a way in which we haven’t seen in the past 20 years, chips be made much more specialist.
broadly speaking, there’s only two types of chips that exist CPUs, for a very long time, GPUs, and really there’s very few other types of chips that exist, at the margins. the bet over the next decade and beyond is that we’re gonna have an explosion of new types of chips. that creates good investment opportunities.
So I definitely wanna come back to the smiling curve that you talked about — in terms of the agglomerators versus the small specialist funds — because I think it’s relevant to wider, like industrial strategy and how you think about the partnerships that you might want in government and between sort of capital allocators. But before that, let’s just go deeper on the semiconductors thesis. Like, you’ve gone way deeper into this than so many people. If you are a lay person, you’ve seen like NVIDIA explode over the last few years and you go, oh, I guess like GPUs are important. Now you know what GPUs are. You previously just had your CPU in your laptop, that’s it.
What’s missing from that story? People may know Intel and NVIDIA, but there’s so much more of the story here? Just talk us through the story of semiconductors, like where we’ve been, how we got here, and then why you think that this is interesting going forwards.
[00:04:53] Lawrence Lundy-Bryan: The truth is Silicon Valley, semiconductors is one of the first, examples of venture capital. It’s surprising to me that it’s flown under the radar, because I think the truth is everybody was looking at software and the internet. most people that you speak to, apart from veterans, really grew up in the internet and software age.
So most mental models around financing, around innovation, around what a foundry even looks like are based around the social network and Facebook and that sort of stuff.
It’s not so much, it’s not been important. It’s just been under the media radar or the average person’s radar.
But it’s always been fundamental. I mean smartphones, right? ARM, people might not have heard of Qualcomm, but people have probably heard of ARM and how you design chips. Then there’s this $500 billion industry, maybe larger now, probably a trillion by 2030 It’s this huge industry that is global, one of the first globalised industries, hugely interconnected, but flies under the radar, right?That makes it a good investment opportunity, firstly. But the reason to say that is because it never really mattered to the average person what Facebook ran on. No one needed to know that Facebook ran on, whatever it was. And like how Google was able to serve trillions of queries. No one really knew or cared. And I think it’s reached into public consciousness for two reasons.
One is, COVID and the automotive example, people might have heard of that. It’s oh, we can’t make cars because, oh, there’s this one component that we can’t get access to. So it made it into public, consciousness. And then people realized how global the supply chain was, how political it was because of Taiwan. And I think there was the book Chip Wars.
Yeah, the Chris Miller book..
[00:06:37] Lawrence Lundy-Bryan: Yeah, exactly. So people started to read that. I think people realised it’s a geopolitical thing, number one.And then number two, before the NVIDIA runup, this data centre build out and people starting to realise that AI needs a lot of computing power. When you say, why does it need so much computing power? Then you say, GPU, and then you say, what are these compute chips?
The reason why I think it’s really interesting now is we’re still really at the beginning. Regardless of if you think it’s a bubble or not. We have 5, 7, 8 year build outs of data centres that are being bought and paid for that involve buying chips. this isn’t slowing down or stopping if you believe, in, the importance or the value of ai. And I do. I think all of it needs to run on computer chips. I think it becomes one of the most important components, most important technologies for any company or country in the next decade.
And play that forward. What are the bottlenecks that you foresee existing chips and kind of chip architectures not being sufficient for?It’s funny. First principles is never the best way to think about how things are adopted.
It’s mainly path dependency, but the truth is, we are using the same thing that ran the SEGA Dreamcast to run large language models. It’s just these GPUs, right? It’s remarkable, frankly. And that’s not quite true.
What’s, wrong with that?
[00:08:05] Lawrence Lundy-Bryan: Yeah, exactly. Well, path dependency, and it’s the same with lithium ion batteries. We can come up with a quote unquote “better chemistry”.
But you can never beat the cost and the economies of scale. So as an engineer, you can always point holes at something and say, I can make that better because of whatever reasons. But it is, an observation to say we are running these huge models on ultimately something that was designed for something else.
it’s not quite true because they’re not really GPUs now, they have little accelerators that accelerate certain parts of the operation — like matrix multiplications really fast. so they are bespoke to the tasks of running AI training and AI inference.
But there’s two things that have changed that mean that we probably will start to see the world that I described, I could call it heterogeneous computing: the idea that, we’re gonna have lots and lots of specialised things out in the world.And that’s for two reasons. One is that we just can’t make enough GPUs, like we had actually can’t make enough and
Taiwan just not working hard enough.
[00:09:10] Lawrence Lundy-Bryan: the Taiwanese don’t work hard enough, clearly.
what’s funny about that supply chain, it’s not really the GPU — I wrote about this a while ago — it was never, GPUs aren’t really the problem we can make enough GPUs. It’s the memory.
Memory.
[00:09:22] Lawrence Lundy-Bryan: it’s actually the high bandwidth memory that you need. which are only made by three companies globally.
it’s funny when you look at bottlenecks. You always find a good example is, as I say, it’s one of the most globalised, industries in the world.
If you ever think that we can’t make enough of something, and you look all the way down the supply chain, it probably, it wasn’t really even, we couldn’t make enough memory, it was actually that there was only one facility TSMC (Taiwanese Semiconductor Manufacturing Company) owned that does advanced packaging where you ship these things to and they actually put this thing together.
So that fab didn’t have the right, it wasn’t large enough. So they’d have to build another fab to be able to... so the capacity is always growing and shrinking and, if you’re TSMC you don’t just want to ramp up because you’ve got demand now, because what about demand in two or three years?
So the point there is that it’s this very orchestrated machine.
But you, ask, why can’t we just carry on with what we got?
Number one: demand is outstripping supply and the type of things that we want to do we need specialist chips. So the, reason that I think we’ll live in a world of heterogeneous compute is because everyone’s chasing server chips — bigger data centres, power them with nuclear power plants, and just stick these really powerful chips with loads of memory in it. But that’s not what the world will look like in 10 years time. The so-called edge is going to be a really critical part of this.
Can you break that down? When you say that’s not what the world is gonna look like in 10 years time... talk us through this contrast.
[00:10:49] Lawrence Lundy-Bryan: Why.
Yeah, why.
[00:10:51] Lawrence Lundy-Bryan: Well because, if you want a really fast response, whether it be in an autonomous car or a drone, high frequency trading or something in an industrial plant, you can’t wait for the response to go all the way to the data centre and come back.
So number one, latency. If you want extremely low latency, you’ll want as much as possible to happen on the device. Whether that’s a robot a car a smartphone or whatever. Right now we don’t have the applications that require super low latency, but we will.
Privacy being another reason as to why I think, we’ll, have a lot of local devices running models so we don’t have to send all the data back to the cloud unencrypted, to wherever datacentre could be on any jurisdiction. So we want things, private. We want things local. And cost.
one of the really interesting factors is that...what’s the build out? A hundred billion, they’ll probably exceed that. That was last year or this coming year. We’re talking $500 billion build out for just Stargate. These numbers are extortionate, and my own personal opinion is that the value will justify that capex spend. there is still value, but we will need to offload a lot of that performance, a lot of those applications, to the user and to local devices.
So what I mean is it’s cheaper to run a local device on a smartphone, just from an infrastructure cost, and also the user pays for it. The user’s paying for the electricity bill. The user’s paying for the phone. So there’ll be a point from a cost of serving customers’ perspective, where soon we will start to see as much as possible, be offloaded locally.
And it won’t just be data centre and edge. It’ll be how do you, what needs to run at the edge, what needs to run at the data centre? And all of the different performance trade offs, as I mentioned, latency, performance, privacy, cost.
That’ll be traded off by the application. So you might see autonomous cars will be an edge. Whereas, scientific simulations will all be data centre. But at the moment, everything’s data centre.
And you, are you interested in investing across that spectrum or are you focused, like when you describe many of the features that you’ve just described, feel like the sorts of things that the UK and Europe and middle-sized countries with energy constraints and a whole load of other kind of structural issues.
They might be particularly interested in as a way to be able to capture value in this, new stack. And it feels like maybe we’re gonna be able to fix our grid infrastructure, fix our planning system,
[00:13:26] Lawrence Lundy-Bryan: I’m sure we will.
…and build out loads of, data centres.But also whether or not we do that we could also be doing quite a lot more on, on device inference.
And that is probably true across Europe or…there’s this company, Emerald AI, which is doing like compute workload orchestration so that, you’re doing model training runs, at the right time based on grid requirements that’s the sort of thing that feels like it would make sense in a sort of like energy constrained sclerotic state like we have today.
And so are you, we haven’t just talked about yet, like you’re focused on Europe, like you’re not investing globally, you’re focused on Europe. What are the companies that you think will come out of Europe? How much do they relate to these factors that you’re talking about?
[00:14:11] Lawrence Lundy-Bryan: I think that we don’t have a, okay. There’s an investment perspective, then there’s Europe and UK perspective, I would say
Yeah. Obviously, you’re bullish on Europe in public, and then in private…
[00:14:19] Lawrence Lundy-Bryan: No, because we have to do something. We might as well try it. I think thatwe can’t play the CapEx game. We, haven’t grown in decades.
So there’s there, okay. I’m a vc, so you play the probability I can get 20 shots on, goal, so I’m wrong, 17 times, that’s fine.
So I’m used to being wrong. that’s fine. But also I think in, probability. And thinking in, in, in bets 50% of all AI inference,
take place at the edge. I, don’t know, but in that world,
We have a shot at the, UK
and Europe.
is it 20, is it 30%?
It probably depends on, the timeline.
but point being, we can’t spend as much as the US the Gulf, and China.
we know that. So let’s just deal with the world as it is. And, take the bet on edge. Now, am I a hundred percent certain? Of course not.
but I can say for sure that, more AI inference will take place at the edge tomorrow than it did today. And certainly that will increase to some ceiling. So yes, I think your instinct, in the question is correct. We haven’t lost the game. And of course it’s in the US’s interest and OpenAI and others’ interest to, to just go all in on data centre. Because they can, it’s easy, for them
to raise money. But let’s not play that game then. And, we have,
Do you not think there’s at least a minimum viable domestic capacity that’s required?
[00:15:48] Lawrence Lundy-Bryan: it depends on your perspective of geopolitics. The uncertainty of geopolitics over the next two to five years.
You’ve written about, say, what if Nvidia or Broadcom or whoever else are banned from exporting to us due to some wider tariff dispute? I think actually I was reading earlier and you literally wrote about what if the US wants to invade Greenland and it starts using these economic tariffs and here we are in this week where this is exactly the question we’re facing. Maybe not specifically with those companies, but the playbook is in play.
[00:16:15] Lawrence Lundy-Bryan: Oh, yeah. I, yes.
Like, if the long term thesis is that AI becomes a critical input to production in the way that energy is, or labour is today, and you are basically streaming that from abroad, and suddenly overnight your input costs become like 20% more expensive.
[00:16:35] Lawrence Lundy-Bryan: It depends on the extent to which you think, deglobalisation is a structural trend or a fad. a fad is, will this, will the deglobalisation, trend continue for the next 20 years? put a probability on that, and everyone will put a slightly different probability.
Yes. I’ve said I think that it’s close to impossible to truly have a sovereign stack. So sovereign technology
I think that’s coming from a semiconductor perspective. that’s really telling, because as I mentioned earlier, this is complex orchestration of thousands of component suppliers.
So the first order you go, let’s have our own AI chip and let’s have our own data centres. sure. But, okay,
Isn’t that a little bit binary? I definitely get your point about the limits of being able to leverage these choke points or whatever.
ASML is like a massive choke point in the semiconductor supply chain, but the Netherlands can’t leverage it because they don’t control their defence or asml are themselves dependent on suppliers based in the us. So it’s not clear that they have like escalation dominance.
But equally Netherlands does have a stake in like the semiconductor supply chain in a way that we do with ARM, although maybe it’s harder to leverage. It’s not quite so physical. But like, there is surely, sovereignty is a spectrum, not a binary. Like we don’t have to go full autarky.
[00:17:54] Lawrence Lundy-Bryan: Brexit. we don’t have to go all in.
No. I’m not saying we should be self-sufficient. I’d like to be totally clear.
[00:17:58] Lawrence Lundy-Bryan: Yeah. Okay. Fair point. Alright. Good pushback. I think, I think, yeah. My point would be you want some, strategic,
assets. and we have to think, what are our strategic assets?
What are we good at? And how do we, grow those industries,
to be even more strategic?
I would say two things. What we are not good at as a state, and I think what Europe
is, I don’t know if this is true of the political class more broadly, but
you need to say, you need to think what will be strategic in five years.
Not what strategic now. Yeah. And, we can get back to that because I think
that’s important
and beyond that it’s, do we have the stomach, both in terms of capital, but also in, in attention to, to think about this over the long term. Which is what China’s particularly good at.
When it comes to quantum, when it comes to,
semiconductors and other things, which is to say, you need a very clear industrial strategy. Isn’t this next three years, we need to make sure we’ve got a 20 year roadmap. And if you really want to do this and build out capacity, it’s gonna cost money for 20 years.
you can’t just suddenly get FOMO’d into doing industrial strategies everyone else is.
And when it comes to the AI stack, as I say, if we were serious about it and Europe was serious about it, we are not doing anywhere near enough thinking about what that means. It is not a AI chip and it is not a AI interconnect.
this, is half of the battle was my joke. I was in the substack, who’s your neon guy? Where you getting your neon from? And they’re like, yeah. and it’s,
There’s interdependency all the way down.
[00:19:27] Lawrence Lundy-Bryan: Interdependent. Yeah. Turtles all the way down. Exactly. so let’s the, world as it is, so to your point, what are we good at?
What could we be good at? What could the choke points be?
or where we have the equivalent of an ASML, and this is where being a vc,
you have to look not what, as I say what the world is, today
and think three, five years.
What markets, what applications, what, what customer demand will exist that doesn’t exist now, that’s likely to grow. And in which case, what is the UK or Europe currently producing, but at low volumes.
it would require government support to grow to the point at which maybe you would find external capital.
This is a really hard pitch to make and I can make it really specific: compound semiconductors, which I’ve written about. Compound semiconductors is basically, instead of using silicon, which is what all of our chips are broadly made from,
use other types of materials. So things like silicon carbide, which is a different material
or gallium nitride,
Each of these materials has a different property, which makes it useful.
they are better at running hot, at higher frequencies. you can’t stick a silicon chip next to a battery.
it just gets too hot. so you use other materials, silicon carbide or GaN think about, electric cars being a really good example.
What about the chips inside? You don’t think China? Were thinking about that 10 years ago. yeah,
and so that’s just like example.
but we do have very good,
compound semiconductor capacity in uk.
We’re very, particularly good at a Cardiff, down in Cardiff we have a great ecosystem. We have
some companies that are leading, in this space. the reason I tie this back to the, government,
focus is because I’ve looked at lots of compound semiconductor companies,
and with my VC hat on I look at pretty small markets, pretty small growth rates, limited number of buyers, a couple of ev in the uk. And I think, that, doesn’t seem like this developer tool company around the corner that’s growing a hundred percent year over year.
it’s not the best place to put my money.
that is a place the government should be thinking.
So do you, I wanna tease this out a bit more, you’ve just launched a semiconductor fund, where do you see for the companies that you’re speaking to or the ones that you’ve already invested in, who are the bigger customers that are buying their products?
There’s existing demand in the semiconductor ecosystem today. And you think there are new companies that can be founded to serve that existing demand, but better. Or are you also looking at new applications, new use cases, growing parts of the market where there’ll be new customers coming to the fore, enabled by some kind of new chip design, whatever it is. Like how much are you at a high level with your thesis, do you have a rough, weighting towards one of those two?
[00:22:12] Lawrence Lundy-Bryan: Space is a good example.
Interesting.
[00:22:14] Lawrence Lundy-Bryan: Put chips into space. We do, but they, have to be radiation hardened because space has radiation, so that’s pretty tricky for silicon chips to deal with.
we can stick,
more chips into space. That’s not to talk about this idea of
So
This is specifically for for the compute of space operations rather than…I’m also thinking about quite a lot of people in Silicon Valley now being like, we need to actually make chips in space?
[00:22:37] Lawrence Lundy-Bryan: yeah, that’s an interest and we have a good company Space Forge that is trying to do this there are some benefits in terms of gravity, in terms of. Solar power, but I know that aside
Fewer planning restrictions in space…
[00:22:48] Lawrence Lundy-Bryan: Exactly. that’s interesting. I’m not sure if the economics actually makes sense in just doing it on, the ground, but,
but certainly we have these satellites that are very underpowered in terms of what they can do. And also if you think about the round trip — I mentioned latency — the round trip to a data centre.
The roundtrip up to space is costly. You don’t want, you don’t wanna send, much up there. So there’s some really interesting, designs and thinking about, if we wanted to, put a more powerful computer up in space. how would you do it first? how would you design it?
some of this is called compute stick,
the compute in the sensor itself. you can actually do some logic or operations within the sensing data. imagine this, you take a, a huge,
a couple of a terabyte worth of data, right? And instead of send, right now, you’d send all of that back for processing, and then you’d send
the results.
But if you could do some processing at the edge or on the on board, and it turns out the only important part of that is the bottom left, whatever it might be, and you just send that back, you save yourself fortune in terms of, cost. So that’s just like one example of we don’t really have specific specialised chips for space, but we could, another really good example is, and I think this is gonna be a much larger part of the fund, is photonics:
computing with light. We already move pretty much all of our data around the earth over fiber optic, So we already use light to move data. as we get better, at building little lasers to make the light, and as we get better at building little modulators to modulate the intensity and photo detectors to know if the light is on or off.
All of these things, again, smaller and smaller, to the point in which,
relatively recently we’re able to stick with these on a chip or photonic integrated chip. this is all very immature compared to silicon. which churns these things out in the trillions.
it’s still hard to do.
It’s still quite complex, but we are getting to the point now where we can put all of these components
on a chip,
on a different material. It’s generally not silicon.
what can we do if we can shrink, these lasers and things to smaller and smaller sizes?
A whole bunch of things. if you’re wearing an Apple watch You’ve got an image sensor on the back of that.
blood and sensing various other biomarkers. If you have a more powerful,
photonic integrated chip, you could sense more biomarkers.
any sort of wearable device will be seeing more and more powerful chips.
Yeah.
[00:25:12] Lawrence Lundy-Bryan: So they’re just two examples and you can think about autonomous cars or robots as other places for which,
we’re probably not gonna stick GPUs in the next five or 10 years. That’s just a couple of new application areas That we can see whole new chip companies.
Interesting. I want to unpack a little bit more about, the fund is a $30 million fund. And you talked about making kind of 20 bets, give or take. Talk us through the fund sizing. You were talking a little bit before about some of the massive deals in this space. I’m interested in…if I’m someone that wants the UK to win in semiconductors. I think funds that invest in UK companies in semiconductors are a good thing. Why have you rightsized your fund to make that work?
[00:25:56] Lawrence Lundy-Bryan: We haven’t have, we, this is the truth. Maybe that’s the question. It’s not for lack of desire, ambition or, willing. It’s an MVP to prove that this is, important. just like any startup, I see this as a pre-seed, to prove, and what validation points do we have in 24 months
That prove, you should give us more money to do this bigger and better, and to scale. That’s the best way to think about this. it’s not right sized.
it’s too small. a good data point recently, is
There’s a company, in Europe raising a 200 million seed.
Etched, which is public information now, which is an AI chip company raised a 500 million series A, I guess.
And some of those numbers are signal. “We are serious.” But also some of those signals are we’re taking on these big chip companies. we need to have a lot of capital both for hiring, but also like actually going to a fab to make chips costs a fortune.
there’s an interesting thesis about how do we make chips cheaper to make Which is like a how do we get away from the, fab cost 10 billion. why doesn’t the fab cost a hundred million? It’s an interesting series of, challenges there, but broadly, the world as it is now, you want some tape outs? Might need a hundred million, like for like advanced nodes, which is like the most, if you wanted very small chips for smartphones or for AI, chips.
The point is, these things cost a lot. So what can we do with 30 million?
We have to be very early. And be, and because we’re specialist, we can go earlier than the average fund. Because you’d like to think we roughly understand the markets we’re operating in.
the second reason why I think we could be more capital efficient, I dunno if the right number is, we could be a £50m fund or a £100m, I don’t know. But we do have strategic investors that we can introduce to our portfolio where we can give them services that wouldn’t be able to get elsewhere.
So one, one of those is Global Foundries, the third largest, fab facility in the world. We also have a, Taiwanese,photonic, company called Radiant Optoelectronics.
We can introduce our portfolio to these companies and their surrounding ecosystem to do things faster and cheaper.So the hope would be: without us, you’d have to raise £5 million, with us you raise £2.5m. We could be more capital efficient, but I’m not here to say that’s anywhere near enough especially for these frontier AI chips. Now we’ve spent quite a lot of the interview talking about one important, but small part of the broader semiconductor space.
We could be talking about wifi chips, or innovation in sensing, hyperspectral imaging for drone warfare. We can talk about loads of other things where you don’t need a hundred million. you are talking much more sensible, deep techy type numbers. We still need millions, but you don’t need hundreds of millions. If we were only investing in AI chips. Yeah, you probably one a $200 million fund to off to start, but we’re not, and there’s loads of other spaces that are small, will grow.
And you can invest £1m.
I think it’s interesting ‘cause you maybe to go back to the point you started with explaining the fund, explaining the specialist kind of focus and structure. There’s clearly been this massive shift underway over the last few years.
You have, as you call them, the agglomerators kind of hoovering up evermore and more capital and actually also like ever increasing returns to scale because they can invest in the product, they can add more value, et cetera, et cetera. And then at the other end, the sort of specialists and maybe the messy middle eventually gets washed out.
We’ll see. But when you think about that context, if that’s one trend and then another trend that you’ve definitely thought about quite a lot is the increasingly close relationship between governments and particularlylarger capital allocators.
It’s interesting if you’re looking at this from the perspective, not just as like the GP in the fund, but from like a government perspective of
how do we secure sovereignty in AI? How do we invest well, how do we understand how the market is shaping around us, restructuring around us? And then like, where is the best place to intervene?
And so in the UK, the government has been proposing, is, launching SovAI, this new, this new strategic venture fund for AI, basically. And it’s not just investing in AI chips, it’s, gonna have a wider remit, 500 million, a mix of both capital and in kind support.
based on the reflections that you thought about there with Cloudberry, how do you think about applying those lessons to the government’s side of things as well? What does it, you talked about
with, industrial strategy, you’ve gotta be thinking five years ahead.
And Made in China 2025. It’s this long running strategy and it’s not impossible to do industrial strategy. I think there’s a lot of people who reject it on the merits, but it, requires the capability to do it well. And if you have the capability you can be more ambitious.
And this is a, SovAI is an exercise in capability building. What do you think is required to make that work?
[00:30:47] Lawrence Lundy-Bryan: I think that the single biggest challenge is that any way of thinking about industrial strategy, and us talking about it here, is top down.It’s define the specific things that everybody agrees are important.
and then allocate money to that. And that is sort of if you’re talking about manufacturing, agriculture. we want our own domestic food supply Because it’s relatively slow moving, space and industry. So this idea of top down, ‘this is important’, ‘this is important’ with some degree of certainty. Go ahead. I think you cannot do industrial strategy in 2026 by saying This is a hundred percent important, and this is a hundred percent important because we don’t know.
So the key, insight is that government and civil service are inherently not good at thinking about high levels of uncertainty and making bets because, That’s ultimately what you have to do good industrial strategy in this, in the age of ai, but more, more specifically the age in which things are moving faster because of software on the internet.So the first thing you’d have to do if you were with soft AI or you wanted to do anything is to, understand that you have high degrees of uncertainty. You don’t know all the answers when you set out.
how do you address that? you have two things. One is velocity and one is adaptability.
If you don’t know what the answers are and everything moves fast, you have to move fast. And the second thing is, for SovAI for anyone else is adaptability. That is to say, if you take bets, you will be wrong. So it’s not about the taking the bet, it’s about the process. It’s about understanding what did we get wrong in the process, that we could improve. But still aware that the bet might be wrong.
So I’ll give a good example. Quantum computing.
If you’re gonna have a discussion about strategic autonomy, you’re gonna have a discussion about what’s gonna be important in five, 10 years. The obvious candidate will be, let’s invest in quantum computing because that’s the next thing. if you own your own quantum computer… Autonomy dot profit, the dots are doing a lot of heavy lifting. Maybe.
It’s a bet. But the point is, we don’t know. and, more than that, it’s which type of quantum computer Yeah. Are we talking about trapped ions, superconducting? There’s no answer.
I remember — I’m a fan of industrial strategy, done well I should say — but I remember having conversations with policy people a few years ago saying oh, we need to invest in they would pick up themes. But no, you can only invest in assets. You can only invest in companies. And that is the sort of top down, “we need to invest in themes”.
[00:33:27] Lawrence Lundy-Bryan: Mea Culpa. That’s what I was bad at.
Interesting.
[00:33:29] Lawrence Lundy-Bryan: So that’s the learning, right? For me, over however many years I’ve been investing in a decade or so, my title was always Head of Research. If you do enough research, you could be super smart and you could pick the right themes before anyone else, and ... profit.
And, okay, there’s a part of that. Part of it is understanding, what a quantum computer is. And okay, how do you trap these ions or whatever, what is super conducted logic? You might understand it fine, but I, think a good learning, was with a nuclear fusion company that we were looking at.
And maybe the hubristic approach is, I’m gonna go and speak to 20 people in nuclear fusion, and I’m gonna understand, is this the right bet?
It’s not to say all 20 gave a different answer, but all 20 gave a different answer.
And so venture is a great example of where you go, okay, we’re happy with, lots of degrees of uncertainty. So we’re happy to take the bet regardless. But I think a top down industrial strategy and coming up with a theme is the idea that you can somehow predict the, future you bet on these themes and you win. My learning, having done research and done all those themes is, that’s probably the wrong way to do it.
Actually, really good founders will sniff out opportunities. If you are in touch with the ecosystem enough. Ideas, themes will bubble up or companies will bubble up. And if you are, bottom up, which is why the BBB maybe you touched on ‘cause you’ve really underutilized resource because if anyone has access to the entire ecosystem bubbling up, you could understand on the one hand, okay, we think quantum, on the other hand, let’s just speak to everybody in ecosystem.
The BBB is the UK’s largest LP I think it’s invested in nearly a fifth of funds in the UK. And therefore it gets costly report from every one of those funds with it’s not perfect information, but like it is sitting on like the best data set of the early stage venture ecosystem.
[00:35:29] Lawrence Lundy-Bryan: Can we, in the, can can’t we connect that to Claude code like now yesterday. And then we’d all get the answer.
Exactly. I literally used to fill in the quarterly reports, right? And I’d be like, this is how the company’s doing. These are the commercial bottlenecks. These are things that they’re doing well. Here are some policy and regulatory things that could be relevant to them. And we have that information and then we don’t do anything with it. Part of this is about capability, but can I just ask you, I just wanna go down a rabbit hole a little bit on what you said before about: you can be looking at something like fusion, you can speak to 20 different experts, they each say something different.
[00:35:55] Lawrence Lundy-Bryan: Yeah.
And I really, relate to this point. There’s a thing I’ve been trying to articulate, which I’m gonna roughly call “domain elasticity”.
[00:36:04] Lawrence Lundy-Bryan: Sure, you are
If you look at founders who have basically been incredibly successful in one domain. How do they switch from that domain to another domain and still be successful? Elon Musk is a good example.
[00:36:15] Lawrence Lundy-Bryan: There’s very few that do, is the answer. I think.
Well, yeah. Okay. that’s, that’s interesting. But like the, if the job of a VC is to find the people who are capable of doing it, you look at the Boom Supersonic, CEO. He goes from Groupon to founding a supersonic flight company. it’s interesting. What is it about that person?
It’s not necessarily that like while he was at Groupon he was actually a supersonic like physics PhD. But he just had some other skillset.
[00:36:39] Lawrence Lundy-Bryan: Yeah.
And then the flip like the, just to go and couple that with, as a VC, you are speaking to founders across a whole range of different domains every day, who in theory should probably know more about what they’re building than you will, you might have the breadth, but each one of them will have more, specificity.
[00:36:55] Lawrence Lundy-Bryan: Yeah.
And so you have to, there’s always gonna be some gap in knowledge of how do I build conviction in this person to go and build this thing? And you more than most people have gone deep onto the research to be like, I’m gonna get as far as close as I can to understanding the products and technical hypotheses that this person is coming to.
[00:37:13] Lawrence Lundy-Bryan: Yeah.
But not every VC will have that approach. They’ll have different approaches or they’ll go later stage and try and wait they’ll have it derisked in other ways.
Part of what I’m trying to do with these podcasts, particularly when we have more founders on, is to try and help policy makers and other people in and around this sphere understand why some companies are credible and legitimate. And basically I think startups are always playing on hard mode. they don’t have the brand recognition, they don’t have the reputation, et cetera. quite a lot of other people, very reasonably will go, I know nothing about what you’re building, so I dunno why I should believe you when you tell me that, the nuclear fusion company you’re building is actually real.
[00:37:49] Lawrence Lundy-Bryan: yeah.
I’ve been in meetings with very senior foreign policy people who would love us to fix our energy policy. But then whenever anyone mentions an SMR, they’re like, can I see one please? I’ve never seen one. They just keep being promised to me…blah, blah, blah…
[00:38:01] Lawrence Lundy-Bryan: fascinating,
So it’s really hard for them to overcome this sense of why would I believe that the constraints which you’re telling me are gonna change will ever be broken? So all that’s to say when you are thinking about new classes of problems, new founders who are like some, I dunno, step beyond where you are on something. Like how are you building conviction in someone and understanding them to be credible and legitimate in a way that like maybe other people can learn from too.
[00:38:29] Lawrence Lundy-Bryan: Yeah. I did the project probably five years ago called State of the Future, which is still the name of the newsletter.
The conceit behind that, and this was before, LLMs, which rendered it pointless. we looked at 150 technologies, which actually retrospectively the wrong way to look at, innovation.
You speak to an academic about how innovation happens, but the truth is like there’s a WhatsApp group and someone shared a term sheet and said, who’s in? I’m not sure that matches how we think this is done.
We should be looking at problem statements.
But regardless, whatever, looked at the technology.
So everything from brain computing interfaces to, chips to these little Lego blocks of how you make chips to, mRNA vaccines. So like really, broad.
And the idea was to, try and identify a couple of things within each. So I would look at the technical maturity of some of these things.
Was there a market catalyst? Was there something changing in the market? Whether it would be technical? on the, supply side or on the demand side, like consumer behavior change. clean meat would be another example of where the consumer behaviour changed.
Look at how different the technology is to what already exists. So novelty and then impact. how impactful could this technology be? Is this a $1 billion market? Is it a $10bn? Is it a $100bn? Is it a trillion?
[00:39:49] Andrew Bennett: The founder is necessarily almost, if it’s a venture backable company, they’re coming with a contrarian hypothesis.
You speak to all the existing experts and they go, that, that won’t work.
[00:39:58] Lawrence Lundy-Bryan: Yes, okay..You are, I’m not, an expert, but I can tell you something about something you don’t know, which might be relevant.
This is all around how you commercialize an innovation.
Yeah.
[00:40:06] Lawrence Lundy-Bryan: It’s not so much about the specific innovation and some of the market challenges, consolidation of the market, or how many buyers are there, they’re all pretty standard things.
But, so you can tell them, so you can help them understand how they sit within the broader context, which I think is really useful as I’ve looked at lots of technologies, but I think the learning really to how you can sniff test is that most of the fund returners, most of the outliers say pretty outlandish things that if you are asking experts, the experts will say it’s probably not plausible. So this is, the exact game. And which is why VCs can often look stupid ‘cause you back stupid, potentially stupid things. So number one,
All the experts told you it wouldn’t work and it didn’t work.
[00:40:52] Lawrence Lundy-Bryan: Sure. And it didn’t work. Great. Yeah. of course not. Exactly. So, I think, there’s, yeah.
What’s the like Nat Friedman thing? Pessimists are right, optimists to make money?
[00:41:02] Lawrence Lundy-Bryan: Yeah, exactly. And, I think that’s a good one. How we do that is, is just I like to think it’s the trade.
If you’ve been doing it for 10 years, speaking to, 10 founders, 10 founders a week.
You’ve got a really large data set for which just right now, some intuitive view of is someone bullshitting, right?
Which is a reasonable, you can get yourself to some level of this person is bullshitting.And then below that, really it’s will this work?
It depends when you’re investing. At our stage, ‘will this work? Maybe.’ ‘Is the market big enough if it works, yes or no? If yes, okay.’ And then you, proceed down that route. And this is what I mean about taking bets. If you’re doing it early enough, you are almost certainly gonna find one or two people that say this will never work.
If you are used to risk mitigation, if you are used to not wasting taxpayers’ monies, if you are used to betting on certain things, then you can always find a reason not to make an investment.
And you can always seem smart because, I spoke with someone at X big company that you’ve heard of, and they said it will never work.
Yeah.
[00:42:04] Lawrence Lundy-Bryan: So I can feel good now. That’s the challenge. And I often find that’s the challenge in hiring people as well, like hiring people who are prepared to stick their neck out a little bit. It’s really high degrees of uncertainty and being very comfortable with being wrong a lot.
they’re not then, that’s not how we are taught in British education system, I would argue. Being wrong is hard.
And you also made this point before about if you are, protecting taxpayers’ money, like you, I think when you were writing about SovAI, you were saying there is always a reason for ask to ask for more data, more review, more like process. And that might go against the velocity that’s required for that particular institution to succeed.
[00:42:43] Lawrence Lundy-Bryan: I know I’m pretty radical about this, but also like I totally understand the incentives, because there are no incentives To be fast and be wrong.
That these incentives don’t exist and they barely exist in venture capital firms. The truth is some of this is just structural. Fund one, you’re investing in weird things for whatever reason. You have some alpha
[00:43:01] Andrew Bennett: You’ve got something to prove, yeah.
[00:43:02] Lawrence Lundy-Bryan: And then by fund two or three you’ve put processes in place, a bureaucracy to avoid failures. It’s, very much, a structural problem in all institutions. Interesting. So it’s no surprise in my view that, that this happens in institutions that have been around for centuries.
[00:43:17] Andrew Bennett: How did the three of you at Cloudberry make decisions?
[00:43:20] Lawrence Lundy-Bryan: I’ve got a, few different learnings from different funds, which I’m trying to take with me here.And many and I think there’s lots of way to make money, frankly. You could be consensual, you could be lone wolf. The key is having really different, like coming from different places.
By that I mean, if we are thinking about what our fund looks like, I’m the one that’s gonna, I dunno if this is right or it’d be interesting. I’m not sure if this is right, but I think I can put myself in the mind of other VCs.
[00:43:52] Andrew Bennett: Invest in things that will get markups ‘cause other people like them.
[00:43:55] Lawrence Lundy-Bryan: Maybe.
[00:43:56] Andrew Bennett: Yeah.
[00:43:57] Lawrence Lundy-Bryan: but it’s one way to play the game, I think.
[00:43:58] Andrew Bennett: I’m just quoting your substack,
[00:43:59] Lawrence Lundy-Bryan: Quoting my own substack quote me back at me.Which I think could be helpful. You might end up, converging on the same things. Yeah.
I think, the, Rene and Veera are better at understanding what other semi customers might want, semiconductor customers, what will a customer want?
[00:44:12] Andrew Bennett: Is that their background?
[00:44:13] Lawrence Lundy-Bryan: What will a CVC... Exactly, yeah. So that’s their background. What will a corporate venture capital firm be interested in within the ecosystem? Operationally, Rene has built a company and sold a company. So he understands lots of things that I don’t. I think
what I do at pre-seed is I invest X amount of money to get to Y milestone. That’s the key thing I’m doing. identify what is X milestone. What does it take to get there? And once you’ve hit X milestone, who will invest to get you to the next milestone?
if you can reduce. the complexity to that.
You can then think much more clearly about, okay,
two years, 3, 4, 5 years down the line, the uncertainty continues to go up. What can I really think about?
[00:44:49] Andrew Bennett: Do you think that relay race effectively as you’re describing it, like I invest so that they, the company will get to the next stage and then someone else will come in and help them get to the next stage.
Do you think that relay race breaks down when you have these, structural shifts going on between the smiling curve of the specialists and the agglomerators, it’s
[00:45:11] Andrew Bennett: are the agglomerates just gonna, are they gonna come in at the seed and then back them from there?
Is that how you
[00:45:15] Lawrence Lundy-Bryan: see the No. ‘cause if, think about if you think about, institutional bureaucracy
I think then, why not wait? Why not wait to [Series] A, we can de-risk it at [Series] A and then we can give them 50 million so it’s, I think, actually a better way of thinking about it: venture capital, investing in truly, unusual things, new markets is venture capital and anything, maybe post B is private equity growth capital — it’s different. And I think we have to think about that as probably bifurcating in a way that it hasn’t before.
[00:45:47] Andrew Bennett: Interesting.
[00:45:48] Lawrence Lundy-Bryan: And if it does bifurcate, then could they come further down and do seed?
Yes, but it doesn’t materially move the dial for them in terms of what’s 1 million in a 15 billion funds
[00:45:58] Andrew Bennett: Also just like as a founder you’re just like a tiny part of their portfolio. Yeah.
[00:46:02] Lawrence Lundy-Bryan: they’re not gonna be on what side responding to your messages at midnight or whatever.
So I think there’s, the specialists will always be there, but I do think if that theory of, structural change is right, the smiley curve. you really have to know the rest of the capital stack. the relay races may be a really good analogy because you really need to know who you are handing it off to.
And I think my previous view through investing in a theme,
[00:46:28] Lawrence Lundy-Bryan: of venture capital theory is in the theme. And you get the timing right and the market emerges. And of course, follow on investors will arrive because the markets arrive. in the perfect world, you’ve invested in the right theme at the right time.
And by the time they hit [Series] A, they’ve got £1m, £1.5m, £2m revenue and it hits. That’s the perfect world. And in most cases, that’s never quite right. So you can de-risk it by speaking to the AUM aggregators, the later stage investors: getting a sense of what’s interesting to them, what will move the dial for them? What are they interested in? And trying to match it up.
I’m reluctant. to go all in on that as the game.
[00:47:09] Andrew Bennett: Yeah.
[00:47:09] Lawrence Lundy-Bryan: Because it’s the sales game. You hand it off to someone else, you get markups.
I don’t think that’s how you build a sustaining fund. If Cloudberry becomes fund five, fund six, I don’t think it’s because we did that well. I think it’s because we did back sort of unusual companies doing unusual things, outlier type people.
It wasn’t obvious who the next investor is. you have 20 bets and I don’t think you can take 20 bets on weird, funky, unusual people where you have no idea who’s gonna invest next. Because I think that’s probably too much risk to take.
[00:47:40] Andrew Bennett: Yeah. I think it’s pretty interesting that you’re doing this in Europe and that you’re also bullish on the opportunity to do this in Europe.
Can you just say a little bit more about where that bullishness comes from?
[00:47:53] Lawrence Lundy-Bryan: We have to do something, I dunno what to tell you.
honest, honestly.
because.
I’m terminally online. No, I don’t think it’s because I’m too online, but,
[00:48:04] Andrew Bennett: Europe already has a strong semis ecosystem and it can be even stronger.
I think there’s a very good case
[00:48:09] Lawrence Lundy-Bryan: I make the financial case. Yeah. that, I think
Europe has this huge, talent base. okay. number one, I’m, pretty radicalised to the fact that Europe needs to wake up and we are in an age of deglobalisation.
strategically, we’ve been reliant on the US for too long. Hopefully one day we can rely on the US again, but as it is today,
we need to, invest, in our own capabilities.
[00:48:31] Andrew Bennett: Would you call yourself a patriot?
[00:48:33] Lawrence Lundy-Bryan: Are you trying to think about how we can reclaim that word?
[00:48:35] Andrew Bennett: Yeah.
[00:48:36] Lawrence Lundy-Bryan: Yeah. Interesting.
I think there’s something interesting from a reclamation perspective how we can
[00:48:41] Andrew Bennett: Right.
[00:48:41] Lawrence Lundy-Bryan: Regain that from a, as liberals,
so yeah, for certain a patriot, which is why this. Europe, UK thing is interesting. Again, for me, now, first and foremost, I think of myself as a Brit.
Not European, but for sure our European partners and colleagues. And this is a Finnish fund.
for sure this is your European play, but from a UK perspective, I think we just sleeping for too long.
hopefully it’s not, terminal.
Hopefully we can wake ourselves up again. But I’m radicalised to the idea of we have unbelievable talent. R&D like number one, technical R&D talent. We have Eindhoven, we have Bristol, we have Southampton, Oxford, Cambridge,
Munich.
Lots and lots of really deep pools of talent.
what we’ve lacked,
and I think this is the bet I’m making, what we’ve lacked is enough ambitious founders that want to win globally. I don’t think that’s because they don’t exist. I think that’s because they were, I think their ambition, they were defanged.
I think their ambition has been reduced because they were too busy talking to EIS funds that were saying where’s your P&L? yeah, at preseed. So number one, I thinkthe founders were there, but they’ve been slowly battered and so they asked for 800 k because that’s all they think they can get.
I think, Cloudberry and others, Plural, namely, but there are plenty of others out there saying we can be more ambitious. Because we have ambitious investors too. So number one, I think the more we shout about the fact that think big and we’ll back you, I think that means we can, enable people to return to their natural ambition, right?
We don’t need to create more founders, they’re there. And number two, I think a lot of them went to the US quite rightly. That would be how I would de-risk my company two years ago and now they don’t. So they’re here unless give them the capital they need to build the businesses here.
[00:50:36] Andrew Bennett: I think there’s this concept in, evolutionary biology called niche construction.
a good example of this is a beaver building a dam.
it’s like there will be one organism that intervenes on their ecosystem and that intervention means that the ecosystem reshapes itself around them. And there’s something in, what you’re doing, Plural, and like a few others where there is a sort of like unreasonable belief and ambition relative to the, status quo that is creating value because there are founders that no longer have to go down these, slower paths and they can believe in themselves and go, down the ambitious path.
[00:51:13] Andrew Bennett: And there’s just something interesting there about
[00:51:16] Andrew Bennett: part of what we’re doing here is figuring out how to solve problems through company building, through capital allocation, and through policy and government,
understanding actually, like the craft of building a venture company is interesting in and of itself. A venture fund is, its, Cloudberry is itself a company.the journey that you’ve gone on to build it and the intervention that it can have in the ecosystem is interesting.
[00:51:40] Lawrence Lundy-Bryan: The thing that makes me think of is peculiarly a European and British thing, but maybe this is why people, head out to the, US which is, it’s not necessarily the tall poppy syndrome, but there’s definitely something in, our reflexive culture, which...
“i wanna build a trillion dollar company.” People will laugh at that.
[00:52:01] Andrew Bennett: Yeah.
[00:52:02] Lawrence Lundy-Bryan: There’s some instinctive, skepticism in that somehow the and I think the, US do it, well. I think, I’m not here to change culture because one person doesn’t change it, but there is something in a small group of people, for which I think you are, collecting, pulling together small group of people that do shout it from the rooftops that say we don’t have to just accept declinism anymore.
[00:52:25] Andrew Bennett: Yeah.
[00:52:25] Lawrence Lundy-Bryan: We can build a new city in Cambridge. Why not? and actually think we’re gonna build a trillion dollar company. how are you gonna get all
the team? How are you gonna raise the money? yeah, we’ll figure it out. Like this sort of bullishness.
I thought that I would be more bullish in my twenties, and then slowly you become more conservative and less bullish. But for some reason I’ve come out the other end and I’m that’s why are we can’t just keep accepting this. there’s many more people like me.
Maybe my age or not, who are thinking like, why are we just accepting this declinism? We need to shake people out of this is the way it has to be. And a good example is all the stories, what did we get for GDP growth? 0.1%.
And it was written up like ‘good day for Rachel Reeves’. Good day. Good day. 0.1%. But there’s no context.
[00:53:07] Andrew Bennett: yeah.
[00:53:08] Lawrence Lundy-Bryan: Okay. If someone said we want to aim for seven, then 7% is ridiculous. let’s say, 3%, let’s say 3% or 2.5%. crazy. Ask Dario at Anthropic, or let’s say we wanna aim for 3%.
Yeah.And that is the target they’d get, you’d get laughed at. Yeah. But I think there’s that sort of level of ambition, not just from politicians. I’m sure politicians would like to say that, but they would
[00:53:31] Andrew Bennett: Yeah.
[00:53:31] Lawrence Lundy-Bryan: Get killed for doing so. I think you can do the same on the venture and ventures and yeah.
It’s a bit easier to say we’re gonna build a trillion dollar companies, wanna do it in the UK and we’re gonna invest in them. And we’re gonna help them be ambitious to do that.
[00:53:43] Andrew Bennett: I think, what you’re speaking to there is a really interesting cultural difference if you have a financial stake in being optimistic and experience with companies who are like, no one knows who they are, they have no reputation, and then over five years they become global winners.
You believe that things can change quickly. Whereas I think if you often don’t have that and governments have a lot of other things to, to think about and care about as well, but it’s really hard to believe that the future can be radically different
from the present day
there’s a culture that you’re inculcated in that is, transferable is important for actually raising ambition.
there isn’t enough of it.
[00:54:18] Lawrence Lundy-Bryan: Yeah. Like how do we change a thought about this from a, political perspective,
which I’m, treading dangerously outside my ream of competency, which is my job as a VC
[00:54:28] Andrew Bennett: Of course.
[00:54:28] Lawrence Lundy-Bryan: So I will continue. Of course. what, could I do before the next election? in the next two years. That the average person would feel like things are changing.
one idea is, everybody sees autonomous cars on their streets. And then we say, the taxi drivers are gonna revolt Sure. But things can change. There’s an autonomous car on the street. That’s cool.
[00:54:47] Andrew Bennett: Yeah.
[00:54:48] Lawrence Lundy-Bryan: That’s interesting. That didn’t exist.
Yeah. That’s a new technology, a new enable. It’s gonna bring lots of problems. It’ll run over cats. It’ll be on the Daily Mail headline. And everyone’s gonna say, but
[00:54:55] Andrew Bennett: they’re also safer than most cars.
exactly. The logic, doesn’t, we’ll not win that argument. It does on this podcast.
[00:55:02] Lawrence Lundy-Bryan: Okay. Logic wins on this podcast. It’s a safe space.
what could you do to say the future will be brighter?
[00:55:07] Andrew Bennett: Yeah.
[00:55:07] Lawrence Lundy-Bryan: How do we go back to the atomic age, the futurama, like the future. I think that’s the missing link. And I can’t do it from a semi fund, like a semiconductor fund is a part of it, but
[00:55:17] Andrew Bennett: Maybe you make train wifi possible.
[00:55:19] Lawrence Lundy-Bryan: Train wifi is a starting point. Then nuclear
[00:55:21] Andrew Bennett: fusion. Visible. Tangible, yeah. Nuclear fusion and train wifi. Let’s have both of those by 2029.
[00:55:26] Lawrence Lundy-Bryan: Fix the potholes. Yeah. And then, and, train wifi and then fusion on the other end. But these things should be
[00:55:31] Andrew Bennett: visible, tangible things.
[00:55:32] Lawrence Lundy-Bryan: Yeah. Visible. Exactly. The autonomous cars is the only one I could think of that could actually
[00:55:36] Andrew Bennett: happen. there’s tons of others. Clean meat in supermarkets,BV loss, drones that fly beyond visual line of sight do logistic and then that’s, licensed.
Yeah. Yeah. Drone deliveries is a good one. there’s a, whole chunk of things like AI medical devices that, that currently, like again, like there’s a whole lot stuff across our regulatory state that is like interesting, super important, these are markets that matter new technologies and companies can improve our lives in such a visible, tangible, visceral way.
[00:56:02] Lawrence Lundy-Bryan: Do you think
[00:56:03] Andrew Bennett: that drives a wedge between that and just like the social media giants that people have an aversion to
[00:56:08] Lawrence Lundy-Bryan: Yeah.
But you’re touching on it there, and AI.
People have, this is the question, and this is the pushback when I floated this to autonomous cars, people, the public won’t like that.
the extent here is the leadership take, like leading people into the bright future, the bright light of technology. things will be better. I think if you were to do that, many of those things, the drones, people complain about the noise, they complain about the risks.
I think it would be a negative view of it. Not necessarily a positive. So here I am and we are, as technologists saying, this would be so cool. I think there’ll be an immediate pushback on this isn’t cool for all these reasons.
[00:56:46] Andrew Bennett: Yeah. And it’s hard to know how to. Medical devices might be the one, get cancer diagnoses down by a hundred days or whatever. I think there probably are ways to make it much more positive, but the instant reaction would be a negative one.If we stay in this model of nothing ever changes and we never have any of the visible signs of progress that then give people a stake in, like things can get better.
Yeah. Then, we’ll end up in this, we’ll stay in this terminal valley nuclear fusion. Fix the train wifi.
[00:57:16] Lawrence Lundy-Bryan: I’ve set up a, silicon semiconductor fund, which I think is an important an element to it, but because a lot of what you’ve described, is relying on semiconductors. Yeah.
Yeah. So if we wanna make people’s lives better, we want economic growth. Yeah. I think, yes. So also I think nuclear fusion could be part of it, but that’s a longer term horizon. The core engine, of economic growth over the next decade will be how we turn energy into intelligence.
Again, I mean to summarise the whole thesis behind this is we’ll have energy and that’s a problem, but then we need to turn it to intelligence. Both whether it’s in the data centre or in cars or whatever, but turning into intelligence, that’s a silicon problem.
That’s actually how we make the chips.
But broadly speaking, how do we turn it into intelligence? And, that is the defining question of this decade for me and for the UK and for policymakers.
[00:58:01] Andrew Bennett: Good luck!
[00:58:02] Lawrence Lundy-Bryan: I’ll do my best.
[00:58:03] Andrew Bennett: Thanks so much for coming on, Lawrence.
[00:58:04] Lawrence Lundy-Bryan: Thanks.
[00:58:06] Andrew Bennett: That was Lawrence Lundy-Bryan, GP at Cloudberry VC, Europe’s first dedicated semiconductor fund. And frankly, for the UK to win, we’re gonna need so much more of his energy. Over the course of this year, we’ll be speaking to more founders, investors, policy makers, writers, artists, about how we can raise our collective ambition for who we are, where we’re going, how we get there. So please share your feedback, small or large. Help make this as good as possible. Like, subscribe, share, help me toil in the content mines. And as always, thank you to the Centre for British Progress for supporting Sovereign Albion, to Julia Willemyns, David Lawrence, and Alys Key for editorial support. And to Podcast House for production support. Until next time.
