For the last year, Iβve 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 βsovereigntyβ look like when itβs 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 thereβs state capacity, which is critical to industrial policy going well. What will it take for SovAI, the governmentβs 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 Europeβs first dedicated semiconductor fund, Cloudberry. Heβs 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, Europeβs first dedicated semiconductor fund. He also writes the State of the Future substack, which researches frontier technology analysis.
You just launched Europeβs first semiconductor VC fund. Why on earth would you do that?
[00:01:37] Lawrence Lundy-Bryan: The truth is Iβve jumped on the bandwagon here. Like Veera and Rene, my partners, did all the hard work. thereβs a VC bet that Iβm making, and then thereβs a macro bet.
The VC bet is, thereβs only gonna be two types of VC funds in a decade:
the capital agglomerators, the AUM, the Andreessenβs $15bn four, five funds or whatever. Sequoia, Benchmark, those guys that just raise all the money.And then specialists,
Iβm 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, thatβs still quite broad.
Yeah.
[00:02:21] Lawrence Lundy-Bryan: I mean what is, deep tech? Itβs 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.
Weβll 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 βadd valueβ in a way that isnβt 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 weβve invested, weβll 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 NVIDIAβs price, potentially, but thatβs irrelevant.
just from a VC perspective, itβs like a huge gap in semiconductors. And I think over the next decade weβll start to see, a way in which we havenβt seen in the past 20 years, chips be made much more specialist.
broadly speaking, thereβs only two types of chips that exist CPUs, for a very long time, GPUs, and really thereβs very few other types of chips that exist, at the margins. the bet over the next decade and beyond is that weβre 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 β in terms of the agglomerators versus the small specialist funds β because I think itβs 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, letβs just go deeper on the semiconductors thesis. Like, youβve gone way deeper into this than so many people. If you are a lay person, youβve 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, thatβs it.
Whatβs missing from that story? People may know Intel and NVIDIA, but thereβs so much more of the story here? Just talk us through the story of semiconductors, like where weβve 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. Itβs surprising to me that itβs 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.
Itβs not so much, itβs not been important. Itβs just been under the media radar or the average personβs radar.
But itβs 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 thereβs this $500 billion industry, maybe larger now, probably a trillion by 2030 Itβs 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 itβs reached into public consciousness for two reasons.
One is, COVID and the automotive example, people might have heard of that. Itβs oh, we canβt make cars because, oh, thereβs this one component that we canβt 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 itβs 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 itβs really interesting now is weβre still really at the beginning. Regardless of if you think itβs 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 isnβt 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?Itβs funny. First principles is never the best way to think about how things are adopted.
Itβs mainly path dependency, but the truth is, we are using the same thing that ran the SEGA Dreamcast to run large language models. Itβs just these GPUs, right? Itβs remarkable, frankly. And thatβs not quite true.
Whatβs, wrong with that?
[00:08:05] Lawrence Lundy-Bryan: Yeah, exactly. Well, path dependency, and itβs the same with lithium ion batteries. We can come up with a quote unquote βbetter chemistryβ.
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.
itβs not quite true because theyβre not really GPUs now, they have little accelerators that accelerate certain parts of the operation β like matrix multiplications really fast. so they are bespoke to the tasks of running AI training and AI inference.
But thereβs 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, weβre gonna have lots and lots of specialised things out in the world.And thatβs for two reasons. One is that we just canβt make enough GPUs, like we had actually canβt make enough and
Taiwan just not working hard enough.
[00:09:10] Lawrence Lundy-Bryan: the Taiwanese donβt work hard enough, clearly.
whatβs funny about that supply chain, itβs not really the GPU β I wrote about this a while ago β it was never, GPUs arenβt really the problem we can make enough GPUs. Itβs the memory.
Memory.
[00:09:22] Lawrence Lundy-Bryan: itβs actually the high bandwidth memory that you need. which are only made by three companies globally.
itβs funny when you look at bottlenecks. You always find a good example is, as I say, itβs one of the most globalised, industries in the world.
If you ever think that we canβt make enough of something, and you look all the way down the supply chain, it probably, it wasnβt really even, we couldnβt 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 didnβt have the right, it wasnβt large enough. So theyβd have to build another fab to be able to... so the capacity is always growing and shrinking and, if youβre TSMC you donβt just want to ramp up because youβve got demand now, because what about demand in two or three years?
So the point there is that itβs this very orchestrated machine.
But you, ask, why canβt 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 weβll live in a world of heterogeneous compute is because everyoneβs chasing server chips β bigger data centres, power them with nuclear power plants, and just stick these really powerful chips with loads of memory in it. But thatβs 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 thatβs 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 canβt 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, youβll want as much as possible to happen on the device. Whether thatβs a robot a car a smartphone or whatever. Right now we donβt have the applications that require super low latency, but we will.
Privacy being another reason as to why I think, weβll, have a lot of local devices running models so we donβt 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...whatβs the build out? A hundred billion, theyβll probably exceed that. That was last year or this coming year. Weβre 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 itβs cheaper to run a local device on a smartphone, just from an infrastructure cost, and also the user pays for it. The userβs paying for the electricity bill. The userβs paying for the phone. So thereβll be a point from a cost of serving customersβ perspective, where soon we will start to see as much as possible, be offloaded locally.
And it wonβt just be data centre and edge. Itβll 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.
Thatβll 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, everythingβs 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 youβve 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 weβre gonna be able to fix our grid infrastructure, fix our planning system,
[00:13:26] Lawrence Lundy-Bryan: Iβm sure we will.
β¦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 orβ¦thereβs this company, Emerald AI, which is doing like compute workload orchestration so that, youβre doing model training runs, at the right time based on grid requirements thatβs 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 havenβt just talked about yet, like youβre focused on Europe, like youβre not investing globally, youβre focused on Europe. What are the companies that you think will come out of Europe? How much do they relate to these factors that youβre talking about?
[00:14:11] Lawrence Lundy-Bryan: I think that we donβt have a, okay. Thereβs an investment perspective, then thereβs Europe and UK perspective, I would say
Yeah. Obviously, youβre bullish on Europe in public, and then in privateβ¦
[00:14:19] Lawrence Lundy-Bryan: No, because we have to do something. We might as well try it. I think thatwe canβt play the CapEx game. We, havenβt grown in decades.
So thereβs there, okay. Iβm a vc, so you play the probability I can get 20 shots on, goal, so Iβm wrong, 17 times, thatβs fine.
So Iβm used to being wrong. thatβs fine. But also I think in, probability. And thinking in, in, in bets 50% of all AI inference,
take place at the edge. I, donβt 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 canβt spend as much as the US the Gulf, and China.
we know that. So letβs 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 havenβt lost the game. And of course itβs in the USβs interest and OpenAI and othersβ interest to, to just go all in on data centre. Because they can, itβs easy, for them
to raise money. But letβs not play that game then. And, we have,
Do you not think thereβs at least a minimum viable domestic capacity thatβs 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.
Youβve 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 weβre 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. Iβve said I think that itβs close to impossible to truly have a sovereign stack. So sovereign technology
I think thatβs coming from a semiconductor perspective. thatβs really telling, because as I mentioned earlier, this is complex orchestration of thousands of component suppliers.
So the first order you go, letβs have our own AI chip and letβs have our own data centres. sure. But, okay,
Isnβt 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 canβt leverage it because they donβt control their defence or asml are themselves dependent on suppliers based in the us. So itβs 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 itβs harder to leverage. Itβs not quite so physical. But like, there is surely, sovereignty is a spectrum, not a binary. Like we donβt have to go full autarky.
[00:17:54] Lawrence Lundy-Bryan: Brexit. we donβt have to go all in.
No. Iβm not saying we should be self-sufficient. Iβd 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 donβt 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
thatβs important
and beyond that itβs, 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 Chinaβs 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. Isnβt this next three years, we need to make sure weβve got a 20 year roadmap. And if you really want to do this and build out capacity, itβs gonna cost money for 20 years.
you canβt just suddenly get FOMOβd 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, whoβs your neon guy? Where you getting your neon from? And theyβre like, yeah. and itβs,
Thereβs interdependency all the way down.
[00:19:27] Lawrence Lundy-Bryan: Interdependent. Yeah. Turtles all the way down. Exactly. so letβs 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 doesnβt exist now, thatβs 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 Iβve 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 canβt 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 donβt think China? Were thinking about that 10 years ago. yeah,
and so thatβs just like example.
but we do have very good,
compound semiconductor capacity in uk.
Weβre 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 Iβve 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, doesnβt seem like this developer tool company around the corner thatβs growing a hundred percent year over year.
itβs 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, youβve just launched a semiconductor fund, where do you see for the companies that youβre speaking to or the ones that youβve already invested in, who are the bigger customers that are buying their products?
Thereβs 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 thereβll 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 thatβs pretty tricky for silicon chips to deal with.
we can stick,
more chips into space. Thatβs not to talk about this idea of
So
This is specifically for for the compute of space operations rather thanβ¦Iβm 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, thatβs 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 spaceβ¦
[00:22:48] Lawrence Lundy-Bryan: Exactly. thatβs interesting. Iβm 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 β I mentioned latency β the round trip to a data centre.
The roundtrip up to space is costly. You donβt want, you donβt wanna send, much up there. So thereβs 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, youβd send all of that back for processing, and then youβd 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 thatβs just like one example of we donβt 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 weβre 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.
itβs still hard to do.
Itβs 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. Itβs 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 youβre wearing an Apple watch Youβve 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 theyβre just two examples and you can think about autonomous cars or robots as other places for which,
weβre probably not gonna stick GPUs in the next five or 10 years. Thatβs 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. Iβm interested inβ¦if Iβm 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 havenβt have, we, this is the truth. Maybe thatβs the question. Itβs not for lack of desire, ambition or, willing. Itβs 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. Thatβs the best way to think about this. itβs not right sized.
itβs too small. a good data point recently, is
Thereβs 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. βWe are serious.β But also some of those signals are weβre 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.
thereβs 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 doesnβt the fab cost a hundred million? Itβs 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 weβre specialist, we can go earlier than the average fund. Because youβd like to think we roughly understand the markets weβre 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 Β£50m fund or a Β£100m, I donβt know. But we do have strategic investors that we can introduce to our portfolio where we can give them services that wouldnβt 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, youβd have to raise Β£5 million, with us you raise Β£2.5m. We could be more capital efficient, but Iβm not here to say thatβs anywhere near enough especially for these frontier AI chips. Now weβve 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 donβt need a hundred million. you are talking much more sensible, deep techy type numbers. We still need millions, but you donβt 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 weβre not, and thereβs loads of other spaces that are small, will grow.
And you can invest Β£1m.
I think itβs interesting βcause you maybe to go back to the point you started with explaining the fund, explaining the specialist kind of focus and structure. Thereβs 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.
Weβll see. But when you think about that context, if thatβs one trend and then another trend that youβve definitely thought about quite a lot is the increasingly close relationship between governments and particularlylarger capital allocators.
Itβs interesting if youβre 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 itβs not just investing in AI chips, itβs, 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 governmentβs side of things as well? What does it, you talked about
with, industrial strategy, youβve gotta be thinking five years ahead.
And Made in China 2025. Itβs this long running strategy and itβs not impossible to do industrial strategy. I think thereβs 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.Itβs define the specific things that everybody agrees are important.
and then allocate money to that. And that is sort of if youβre talking about manufacturing, agriculture. we want our own domestic food supply Because itβs relatively slow moving, space and industry. So this idea of top down, βthis is importantβ, βthis is importantβ 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 donβt 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, Thatβs 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 youβd 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 donβt 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 donβt 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 itβs not about the taking the bet, itβs about the process. Itβs about understanding what did we get wrong in the process, that we could improve. But still aware that the bet might be wrong.
So Iβll give a good example. Quantum computing.
If youβre gonna have a discussion about strategic autonomy, youβre gonna have a discussion about whatβs gonna be important in five, 10 years. The obvious candidate will be, letβs invest in quantum computing because thatβs the next thing. if you own your own quantum computerβ¦ Autonomy dot profit, the dots are doing a lot of heavy lifting. Maybe.
Itβs a bet. But the point is, we donβt know. and, more than that, itβs which type of quantum computer Yeah. Are we talking about trapped ions, superconducting? Thereβs no answer.
I remember β Iβm a fan of industrial strategy, done well I should say β 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, βwe need to invest in themesβ.
[00:33:27] Lawrence Lundy-Bryan: Mea Culpa. Thatβs what I was bad at.
Interesting.
[00:33:29] Lawrence Lundy-Bryan: So thatβs the learning, right? For me, over however many years Iβve 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, thereβs 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, Iβm gonna go and speak to 20 people in nuclear fusion, and Iβm gonna understand, is this the right bet?
Itβs 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, weβre happy with, lots of degrees of uncertainty. So weβre 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, thatβs 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 βcause youβve 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, letβs just speak to everybody in ecosystem.
The BBB is the UKβs largest LP I think itβs invested in nearly a fifth of funds in the UK. And therefore it gets costly report from every one of those funds with itβs 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 canβt we connect that to Claude code like now yesterday. And then weβd all get the answer.
Exactly. I literally used to fill in the quarterly reports, right? And Iβd be like, this is how the companyβs doing. These are the commercial bottlenecks. These are things that theyβre doing well. Here are some policy and regulatory things that could be relevant to them. And we have that information and then we donβt 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. Thereβs a thing Iβve been trying to articulate, which Iβm gonna roughly call βdomain elasticityβ.
[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: Thereβs very few that do, is the answer. I think.
Well, yeah. Okay. thatβs, thatβs 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. itβs interesting. What is it about that person?
Itβs 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 theyβre 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, thereβs 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, Iβm 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. Theyβll have different approaches or theyβll go later stage and try and wait theyβll have it derisked in other ways.
Part of what Iβm 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 donβt have the brand recognition, they donβt have the reputation, et cetera. quite a lot of other people, very reasonably will go, I know nothing about what youβre building, so I dunno why I should believe you when you tell me that, the nuclear fusion company youβre building is actually real.
[00:37:49] Lawrence Lundy-Bryan: yeah.
Iβve 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, theyβre like, can I see one please? Iβve never seen one. They just keep being promised to meβ¦blah, blah, blahβ¦
[00:38:01] Lawrence Lundy-Bryan: fascinating,
So itβs really hard for them to overcome this sense of why would I believe that the constraints which youβre telling me are gonna change will ever be broken? So all thatβs 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 thereβs a WhatsApp group and someone shared a term sheet and said, whoβs in? Iβm 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 itβs a venture backable company, theyβre coming with a contrarian hypothesis.
You speak to all the existing experts and they go, that, that wonβt work.
[00:39:58] Lawrence Lundy-Bryan: Yes, okay..You are, Iβm not, an expert, but I can tell you something about something you donβt know, which might be relevant.
This is all around how you commercialize an innovation.
Yeah.
[00:40:06] Lawrence Lundy-Bryan: Itβs not so much about the specific innovation and some of the market challenges, consolidation of the market, or how many buyers are there, theyβre 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 Iβve 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 itβs probably not plausible. So this is, the exact game. And which is why VCs can often look stupid βcause you back stupid, potentially stupid things. So number one,
All the experts told you it wouldnβt work and it didnβt work.
[00:40:52] Lawrence Lundy-Bryan: Sure. And it didnβt work. Great. Yeah. of course not. Exactly. So, I think, thereβs, yeah.
Whatβs the like Nat Friedman thing? Pessimists are right, optimists to make money?
[00:41:02] Lawrence Lundy-Bryan: Yeah, exactly. And, I think thatβs a good one. How we do that is, is just I like to think itβs the trade.
If youβve been doing it for 10 years, speaking to, 10 founders, 10 founders a week.
Youβve 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 itβs will this work?
It depends when youβre investing. At our stage, βwill this work? Maybe.β βIs the market big enough if it works, yes or no? If yes, okay.β And then you, proceed down that route. And this is what I mean about taking bets. If youβre 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 taxpayersβ 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 youβve heard of, and they said it will never work.
Yeah.
[00:42:04] Lawrence Lundy-Bryan: So I can feel good now. Thatβs the challenge. And I often find thatβs the challenge in hiring people as well, like hiring people who are prepared to stick their neck out a little bit. Itβs really high degrees of uncertainty and being very comfortable with being wrong a lot.
theyβre not then, thatβs 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 taxpayersβ 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 thatβs required for that particular institution to succeed.
[00:42:43] Lawrence Lundy-Bryan: I know Iβm 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 donβt exist and they barely exist in venture capital firms. The truth is some of this is just structural. Fund one, youβre investing in weird things for whatever reason. You have some alpha
[00:43:01] Andrew Bennett: Youβve got something to prove, yeah.
[00:43:02] Lawrence Lundy-Bryan: And then by fund two or three youβve put processes in place, a bureaucracy to avoid failures. Itβs, very much, a structural problem in all institutions. Interesting. So itβs 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: Iβve got a, few different learnings from different funds, which Iβm trying to take with me here.And many and I think thereβs 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, Iβm the one thatβs gonna, I dunno if this is right or itβd be interesting. Iβm 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 βcause other people like them.
[00:43:55] Lawrence Lundy-Bryan: Maybe.
[00:43:56] Andrew Bennett: Yeah.
[00:43:57] Lawrence Lundy-Bryan: but itβs one way to play the game, I think.
[00:43:58] Andrew Bennett: Iβm 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 thatβs 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 donβt. I think
what I do at pre-seed is I invest X amount of money to get to Y milestone. Thatβs the key thing Iβm doing. identify what is X milestone. What does it take to get there? And once youβve 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 youβre 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, itβs
[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. βcause 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 itβs, 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 β itβs different. And I think we have to think about that as probably bifurcating in a way that it hasnβt 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 doesnβt materially move the dial for them in terms of whatβs 1 million in a 15 billion funds
[00:45:58] Andrew Bennett: Also just like as a founder youβre just like a tiny part of their portfolio. Yeah.
[00:46:02] Lawrence Lundy-Bryan: theyβre not gonna be on what side responding to your messages at midnight or whatever.
So I think thereβs, 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, youβve invested in the right theme at the right time.
And by the time they hit [Series] A, theyβve got Β£1m, Β£1.5m, Β£2m revenue and it hits. Thatβs the perfect world. And in most cases, thatβs never quite right. So you can de-risk it by speaking to the AUM aggregators, the later stage investors: getting a sense of whatβs interesting to them, what will move the dial for them? What are they interested in? And trying to match it up.
Iβm reluctant. to go all in on that as the game.
[00:47:09] Andrew Bennett: Yeah.
[00:47:09] Lawrence Lundy-Bryan: Because itβs the sales game. You hand it off to someone else, you get markups.
I donβt think thatβs how you build a sustaining fund. If Cloudberry becomes fund five, fund six, I donβt think itβs because we did that well. I think itβs because we did back sort of unusual companies doing unusual things, outlier type people.
It wasnβt obvious who the next investor is. you have 20 bets and I donβt think you can take 20 bets on weird, funky, unusual people where you have no idea whoβs gonna invest next. Because I think thatβs probably too much risk to take.
[00:47:40] Andrew Bennett: Yeah. I think itβs pretty interesting that youβre doing this in Europe and that youβre 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.
Iβm terminally online. No, I donβt think itβs because Iβm too online, but,
[00:48:04] Andrew Bennett: Europe already has a strong semis ecosystem and it can be even stronger.
I think thereβs 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, Iβm, pretty radicalised to the fact that Europe needs to wake up and we are in an age of deglobalisation.
strategically, weβve 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 thereβs 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 itβs not, terminal.
Hopefully we can wake ourselves up again. But Iβm 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 weβve lacked,
and I think this is the bet Iβm making, what weβve lacked is enough ambitious founders that want to win globally. I donβt think thatβs because they donβt exist. I think thatβs 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 whereβs your P&L? yeah, at preseed. So number one, I thinkthe founders were there, but theyβve been slowly battered and so they asked for 800 k because thatβs 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 weβll back you, I think that means we can, enable people to return to their natural ambition, right?
We donβt need to create more founders, theyβre 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 donβt. So theyβre here unless give them the capital they need to build the businesses here.
[00:50:36] Andrew Bennett: I think thereβs this concept in, evolutionary biology called niche construction.
a good example of this is a beaver building a dam.
itβs like there will be one organism that intervenes on their ecosystem and that intervention means that the ecosystem reshapes itself around them. And thereβs something in, what youβre 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 thereβs just something interesting there about
[00:51:16] Andrew Bennett: part of what weβre 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 youβve 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, itβs not necessarily the tall poppy syndrome, but thereβs definitely something in, our reflexive culture, which...
βi wanna build a trillion dollar company.β People will laugh at that.
[00:52:01] Andrew Bennett: Yeah.
[00:52:02] Lawrence Lundy-Bryan: Thereβs some instinctive, skepticism in that somehow the and I think the, US do it, well. I think, Iβm not here to change culture because one person doesnβt 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 donβt 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 weβre gonna build a trillion dollar company. how are you gonna get all
the team? How are you gonna raise the money? yeah, weβll 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 Iβve come out the other end and Iβm thatβs why are we canβt just keep accepting this. thereβs 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 βgood day for Rachel Reevesβ. Good day. Good day. 0.1%. But thereβs 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. letβs say, 3%, letβs say 3% or 2.5%. crazy. Ask Dario at Anthropic, or letβs say we wanna aim for 3%.
Yeah.And that is the target theyβd get, youβd get laughed at. Yeah. But I think thereβs that sort of level of ambition, not just from politicians. Iβm 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.
Itβs a bit easier to say weβre gonna build a trillion dollar companies, wanna do it in the UK and weβre gonna invest in them. And weβre gonna help them be ambitious to do that.
[00:53:43] Andrew Bennett: I think, what youβre 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 donβt have that and governments have a lot of other things to, to think about and care about as well, but itβs really hard to believe that the future can be radically different
from the present day
thereβs a culture that youβre inculcated in that is, transferable is important for actually raising ambition.
there isnβt enough of it.
[00:54:18] Lawrence Lundy-Bryan: Yeah. Like how do we change a thought about this from a, political perspective,
which Iβm, 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. Thereβs an autonomous car on the street. Thatβs cool.
[00:54:47] Andrew Bennett: Yeah.
[00:54:48] Lawrence Lundy-Bryan: Thatβs interesting. That didnβt exist.
Yeah. Thatβs a new technology, a new enable. Itβs gonna bring lots of problems. Itβll run over cats. Itβll be on the Daily Mail headline. And everyoneβs gonna say, but
[00:54:55] Andrew Bennett: theyβre also safer than most cars.
exactly. The logic, doesnβt, weβll not win that argument. It does on this podcast.
[00:55:02] Lawrence Lundy-Bryan: Okay. Logic wins on this podcast. Itβs 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 thatβs the missing link. And I canβt 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. Letβs 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. thereβs tons of others. Clean meat in supermarkets,BV loss, drones that fly beyond visual line of sight do logistic and then thatβs, licensed.
Yeah. Yeah. Drone deliveries is a good one. thereβs a, whole chunk of things like AI medical devices that, that currently, like again, like thereβs 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 youβre 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 wonβt 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 thereβll be an immediate pushback on this isnβt cool for all these reasons.
[00:56:46] Andrew Bennett: Yeah. And itβs 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, weβll end up in this, weβll stay in this terminal valley nuclear fusion. Fix the train wifi.
[00:57:16] Lawrence Lundy-Bryan: Iβve set up a, silicon semiconductor fund, which I think is an important an element to it, but because a lot of what youβve described, is relying on semiconductors. Yeah.
Yeah. So if we wanna make peopleβs lives better, we want economic growth. Yeah. I think, yes. So also I think nuclear fusion could be part of it, but thatβs 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 weβll have energy and thatβs a problem, but then we need to turn it to intelligence. Both whether itβs in the data centre or in cars or whatever, but turning into intelligence, thatβs a silicon problem.
Thatβs 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: Iβll 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, Europeβs first dedicated semiconductor fund. And frankly, for the UK to win, weβre gonna need so much more of his energy. Over the course of this year, weβll be speaking to more founders, investors, policy makers, writers, artists, about how we can raise our collective ambition for who we are, where weβre 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.



