Welcome to the Fear & Greed daily interview. I'm Sean Aylmer. Semiconductors are in almost everything these days from computers to new cars. So it makes sense that the opportunities for investors in this space are growing. According to Global Investment Manager, Munro Partners, the rise of artificial intelligence could see semiconductors become the new oil. Remember, this is general information only. You should seek professional advice before making any investment decisions. Nick Griffin is Munro Partner's founding partner and chief investment Officer. Nick, welcome to Fair & Greed.

Welcome to the Fear & Greed daily interview. I'm Sean Aylmer. Semiconductors are in almost everything these days from computers to new cars. So it makes sense that the opportunities for investors in this space are growing. According to Global Investment Manager, Munro Partners, the rise of artificial intelligence could see semiconductors become the new oil. Remember, this is general information only. You should seek professional advice before making any investment decisions. Nick Griffin is Munro Partner's founding partner and chief investment Officer. Nick, welcome to Fair & Greed.

Thanks very much for having me, Sean.

Thanks very much for having me, Sean.

I tell you, I've realized how important semiconductors are only in recent days when suddenly there's this flashpoint between the US and China because the Taiwanese president is visiting and they want a tax treaty on semiconductors, and it just hit home how important the producer of a semiconductor chip has become in 2023.

I tell you, I've realized how important semiconductors are only in recent days when suddenly there's this flashpoint between the US and China because the Taiwanese president is visiting and they want a tax treaty on semiconductors, and it just hit home how important the producer of a semiconductor chip has become in 2023.

Yeah, it's been going on for a little while, but yes, you're right. This is how the world's going to be for a while now. Taiwan makes 80% of what we call high performance semiconductors, or i. e., the best semiconductors, the fastest semiconductors in the world, and 80% of them are made in Taiwan and it's been that way for a while and people have suddenly realized how important these things are. And so now we sort of jostle around Taiwan the way we used to sort of worry about Saudi Arabia. Hence, the comm said that semiconductors are the new oil.

Yeah, it's been going on for a little while, but yes, you're right. This is how the world's going to be for a while now. Taiwan makes 80% of what we call high performance semiconductors, or i. e., the best semiconductors, the fastest semiconductors in the world, and 80% of them are made in Taiwan and it's been that way for a while and people have suddenly realized how important these things are. And so now we sort of jostle around Taiwan the way we used to sort of worry about Saudi Arabia. Hence, the comm said that semiconductors are the new oil.

Okay, so for the people like me basically, I talk about semiconductor chips as if I know exactly what they are. Everyone needs a chip in everything they've got. But what are they? They're actually, it's something that allows electrical currents, is that what they are?

Okay, so for the people like me basically, I talk about semiconductor chips as if I know exactly what they are. Everyone needs a chip in everything they've got. But what are they? They're actually, it's something that allows electrical currents, is that what they are?

Yeah. So basically if you think about computers, it's effectively, most of it's sort of binary code and they control the way the binary code flows on a semiconductor effectively. So they drive really simple things like your fridge to driving high- end hyperscale data centers that are effectively processing these AI applications like ChatGPT. And so depending on what you want to get processed, there's very simple, cheap ones that can cost as much as 10 cents to very complicated ones like the H- 100, which is the Nvidia product that they're using to power ChatGPT. And that costs roughly $35,000.

Yeah. So basically if you think about computers, it's effectively, most of it's sort of binary code and they control the way the binary code flows on a semiconductor effectively. So they drive really simple things like your fridge to driving high- end hyperscale data centers that are effectively processing these AI applications like ChatGPT. And so depending on what you want to get processed, there's very simple, cheap ones that can cost as much as 10 cents to very complicated ones like the H- 100, which is the Nvidia product that they're using to power ChatGPT. And that costs roughly $35,000.

Okay. Where do they come from? As you said, 80% of the high end chips come from Taiwan. Who else produces them?

Okay. Where do they come from? As you said, 80% of the high end chips come from Taiwan. Who else produces them?

Korea. So again, let's be really specific here. So semiconductors are made in many places all over the world. It's effectively a commoditized product, has been a commoditized product for a very long time. But at the high end or the bleeding edge of semiconductor development, when you're trying to process things very quickly, the real trick is to get more and more transistors or more and more ability to process code onto the one semiconductor chip. And so this is this concept of Moore's law. And unfortunately Gordon Moore died last week, but he was the CEO of Intel at the time when he pointed out that it appeared to him that every two years you could double the amount of transistors on an integrated circuit. And so what would happen back then in the '70s, you got roughly 2, 000 transistors on integrated circuit for the best, fastest one you could find in the world. And every two years they double it. The 2, 000 went to 4,000, the 4,000 went to 8,000, the 8,000 went to 16,000, 16 went to 32, and this year, Jensen Huang and Nvidia, which is now the premier semiconductor company in the world, put 84 billion transistors on the one integrated circuit. And so what's happening at the bleeding edge, at the bleeding edge, at the really high performance end, they are using very, very complicated nanotechnology, which basically allows you to fit more and more transistors onto the same integrated circuit, which makes your computer faster. Faster your computer is, more things it can do. More things it can do, more valuable it is. And so that's what we're talking about when we talk about the bleeding edge.

Korea. So again, let's be really specific here. So semiconductors are made in many places all over the world. It's effectively a commoditized product, has been a commoditized product for a very long time. But at the high end or the bleeding edge of semiconductor development, when you're trying to process things very quickly, the real trick is to get more and more transistors or more and more ability to process code onto the one semiconductor chip. And so this is this concept of Moore's law. And unfortunately Gordon Moore died last week, but he was the CEO of Intel at the time when he pointed out that it appeared to him that every two years you could double the amount of transistors on an integrated circuit. And so what would happen back then in the '70s, you got roughly 2, 000 transistors on integrated circuit for the best, fastest one you could find in the world. And every two years they double it. The 2, 000 went to 4,000, the 4,000 went to 8,000, the 8,000 went to 16,000, 16 went to 32, and this year, Jensen Huang and Nvidia, which is now the premier semiconductor company in the world, put 84 billion transistors on the one integrated circuit. And so what's happening at the bleeding edge, at the bleeding edge, at the really high performance end, they are using very, very complicated nanotechnology, which basically allows you to fit more and more transistors onto the same integrated circuit, which makes your computer faster. Faster your computer is, more things it can do. More things it can do, more valuable it is. And so that's what we're talking about when we talk about the bleeding edge.

Let's introduce artificial intelligence into this. I would imagine, given what we've seen in the last few months, or at least the general public has seen in the last few months around artificial intelligence, the ChatGPTs of the world, et cetera, that this is kind of a major step forward for that industry, but also in the need for chips.

Let's introduce artificial intelligence into this. I would imagine, given what we've seen in the last few months, or at least the general public has seen in the last few months around artificial intelligence, the ChatGPTs of the world, et cetera, that this is kind of a major step forward for that industry, but also in the need for chips.

Correct, yeah. So the other way to think about this, okay, so if Moore's law's been going since 1970 and it's still going today, as we've gone through this ability for computers to get faster, they can do more things and they hence create more value. So if you go back in time, you probably remember your first personal computer and you go, " Wow, that's pretty cool." Before that, there was just a mainframe computer. I remember my Apple IIe, that's how old I am. And then about 15, 20 years later, they got that computer onto a telephone called an iPhone. And that was your iPhone moment. You went, " Holy cow, I can get the internet on a telephone now." That can do more things and that creates Apple. And then on that phone, over time, Moore's law continued. We can share pictures and that creates social media and Facebook. And then over time, Moore's law continues, packet sizes get smaller, we can do more things, we can stream video. That creates Netflix. And then they create the cloud, and then software goes to the cloud, which reinvigorates Microsoft. And then suddenly, as I always joke about, my kids are tracking Ubers to their house to pick up food, and that's how we order food. And so all of this progress is happening because of Moore's laws continuing and computers are getting faster. So AI is just the next development in this, if that makes sense. So suddenly you've had, again, one of these iPhone moments, ChatGPTs come out and you're like, " Wow, this is really cool. I can do stuff with this." And now everyone's running around trying to work out, well, who's going to be the big winner here, who's going to be the Apple of AI?

Correct, yeah. So the other way to think about this, okay, so if Moore's law's been going since 1970 and it's still going today, as we've gone through this ability for computers to get faster, they can do more things and they hence create more value. So if you go back in time, you probably remember your first personal computer and you go, " Wow, that's pretty cool." Before that, there was just a mainframe computer. I remember my Apple IIe, that's how old I am. And then about 15, 20 years later, they got that computer onto a telephone called an iPhone. And that was your iPhone moment. You went, " Holy cow, I can get the internet on a telephone now." That can do more things and that creates Apple. And then on that phone, over time, Moore's law continued. We can share pictures and that creates social media and Facebook. And then over time, Moore's law continues, packet sizes get smaller, we can do more things, we can stream video. That creates Netflix. And then they create the cloud, and then software goes to the cloud, which reinvigorates Microsoft. And then suddenly, as I always joke about, my kids are tracking Ubers to their house to pick up food, and that's how we order food. And so all of this progress is happening because of Moore's laws continuing and computers are getting faster. So AI is just the next development in this, if that makes sense. So suddenly you've had, again, one of these iPhone moments, ChatGPTs come out and you're like, " Wow, this is really cool. I can do stuff with this." And now everyone's running around trying to work out, well, who's going to be the big winner here, who's going to be the Apple of AI?

Stay with me, Nick, we'll be back in a minute. My guest this morning is Nick Griffin, founding partner and chief investment officer at Munro Partners. So let's bring it a little bit more towards that and towards investing opportunities. Should we be thinking about specific companies in this space? Do we actually go to, I don't know, resources company that suddenly is better at adapting this sort of technology? As an investor, how do you think about it?

Stay with me, Nick, we'll be back in a minute. My guest this morning is Nick Griffin, founding partner and chief investment officer at Munro Partners. So let's bring it a little bit more towards that and towards investing opportunities. Should we be thinking about specific companies in this space? Do we actually go to, I don't know, resources company that suddenly is better at adapting this sort of technology? As an investor, how do you think about it?

Yeah, so from my point of view, there's a couple of ways you can think about it. There's one, there's the simple, what we would call the weapons manufacturers in the war, or the shovels in the boom and the shovels in the mining boom. And the shovels in the mining boom for this company are those high end semiconductors. So that bleeding edge semiconductors, because the people who control the technology that allows you to get another 160 billion transistors onto an integrated circuit, they're the most important people in the world here because whoever's got the fastest semiconductors is going to win in AI. Why? Because you're basically processing reams and reams of data really, really quickly to create generative outcomes or predictive outcomes. So the shovels in that boom are companies like Nvidia that design the chips that a lot of this stuff runs on, or companies like, in our opinion, companies like TSMC, the foundries that make these chips. So that's where Taiwan comes in. Or companies like ASML in lithography, the Dutch company that actually builds the machines that allows us to get more and more transistors onto the integrated circuit. So that's the shovel, so to speak.

Yeah, so from my point of view, there's a couple of ways you can think about it. There's one, there's the simple, what we would call the weapons manufacturers in the war, or the shovels in the boom and the shovels in the mining boom. And the shovels in the mining boom for this company are those high end semiconductors. So that bleeding edge semiconductors, because the people who control the technology that allows you to get another 160 billion transistors onto an integrated circuit, they're the most important people in the world here because whoever's got the fastest semiconductors is going to win in AI. Why? Because you're basically processing reams and reams of data really, really quickly to create generative outcomes or predictive outcomes. So the shovels in that boom are companies like Nvidia that design the chips that a lot of this stuff runs on, or companies like, in our opinion, companies like TSMC, the foundries that make these chips. So that's where Taiwan comes in. Or companies like ASML in lithography, the Dutch company that actually builds the machines that allows us to get more and more transistors onto the integrated circuit. So that's the shovel, so to speak.

And just before we leave the shovel, so it's not like that last one you talked about ASML, the Dutch company. So it's not even necessarily specifically the person who is manufacturing the chips, it's actually the person who is manufacturing the infrastructure for the chips to work.

And just before we leave the shovel, so it's not like that last one you talked about ASML, the Dutch company. So it's not even necessarily specifically the person who is manufacturing the chips, it's actually the person who is manufacturing the infrastructure for the chips to work.

The tools that create the chips.

The tools that create the chips.

Yes, right.

Yes, right.

And so the tools to shrink more and moron involves very advanced lithography. This is some pretty, sorry, this is heavy duty stuff to get into 12 minutes. But yeah, essentially the lithography that creates the stencil to put the 81 billion chips, which you now need to go to 161 and eventually 320 billion. So that's ASML for tools, TSMC is the foundry, Nvidia is the designer. Those are the three players we're talking about there.

And so the tools to shrink more and moron involves very advanced lithography. This is some pretty, sorry, this is heavy duty stuff to get into 12 minutes. But yeah, essentially the lithography that creates the stencil to put the 81 billion chips, which you now need to go to 161 and eventually 320 billion. So that's ASML for tools, TSMC is the foundry, Nvidia is the designer. Those are the three players we're talking about there.

Can I just make a comment here, given how high- tech we're talking, lithography is an ancient art.

Can I just make a comment here, given how high- tech we're talking, lithography is an ancient art.

Yes, it is.

Yes, it is.

So that's pretty cool. Okay, so we can invest in that way. Then what about beyond, so the next way of investing?

So that's pretty cool. Okay, so we can invest in that way. Then what about beyond, so the next way of investing?

Okay, so that's the shovels. And we've looked at those companies for a long time and we've owned them in the fund for a long time. And as you said at the start, to be clear, this is not personal advice. These are things we like and hold. The second way to think about it is who's going to be able to harness this technology and use it? And the obvious recent winner here is Microsoft, in our opinion. Microsoft has the ability, has the data, has its partnership with OpenAI or the people who created ChatGPT, and they're going to create these products like Copilot, and they've already shown you these. And so AI to date has been a bit like autopilot. So you've actually been living with AI for at least seven or eight years now already. It's the recommendations that come up in your Amazon shopping feed. It's what Netflix thinks you should watch next, it's how they park your car, how you land your drone, but now it goes from autopilot, i. e., it's giving you stuff that you didn't ask for to copilot. And so the simple way Microsoft describes this is they could record this recording. So say we did this over Teams, Microsoft would record it and at the end it would summarize the meeting. It would say, Nick said this, Sean said that, et cetera. We could then get it to compose an email to do the follow- ups. We can now ask our office applications to search our previous emails to find summaries of certain things where we've discussed this, if that makes sense. So think about ChatGPT, but in office. So that's a great way to monetize it because I would probably pay an extra $ 10 for my Teams subscription if it summarized all my meetings for me.

Okay, so that's the shovels. And we've looked at those companies for a long time and we've owned them in the fund for a long time. And as you said at the start, to be clear, this is not personal advice. These are things we like and hold. The second way to think about it is who's going to be able to harness this technology and use it? And the obvious recent winner here is Microsoft, in our opinion. Microsoft has the ability, has the data, has its partnership with OpenAI or the people who created ChatGPT, and they're going to create these products like Copilot, and they've already shown you these. And so AI to date has been a bit like autopilot. So you've actually been living with AI for at least seven or eight years now already. It's the recommendations that come up in your Amazon shopping feed. It's what Netflix thinks you should watch next, it's how they park your car, how you land your drone, but now it goes from autopilot, i. e., it's giving you stuff that you didn't ask for to copilot. And so the simple way Microsoft describes this is they could record this recording. So say we did this over Teams, Microsoft would record it and at the end it would summarize the meeting. It would say, Nick said this, Sean said that, et cetera. We could then get it to compose an email to do the follow- ups. We can now ask our office applications to search our previous emails to find summaries of certain things where we've discussed this, if that makes sense. So think about ChatGPT, but in office. So that's a great way to monetize it because I would probably pay an extra $ 10 for my Teams subscription if it summarized all my meetings for me.

Absolutely.

Absolutely.

Other winners here are other software companies who can do this, but they'll potentially be software losers. Google's probably a winner here because they've got the most data and they've got the best AI, but they probably don't know how to monetize it. But most importantly, I think it's a bit like your iPhone moment. It's just one of these great things that's going to come along that's going to make us all a bit more productive. And that's a good thing.

Other winners here are other software companies who can do this, but they'll potentially be software losers. Google's probably a winner here because they've got the most data and they've got the best AI, but they probably don't know how to monetize it. But most importantly, I think it's a bit like your iPhone moment. It's just one of these great things that's going to come along that's going to make us all a bit more productive. And that's a good thing.

What about the risks? Where do you see, I'm sure we've got the normal risks, security, privacy and over time they will probably be addressed and hopefully adequately addressed, but where do you see the big risks for where we are going?

What about the risks? Where do you see, I'm sure we've got the normal risks, security, privacy and over time they will probably be addressed and hopefully adequately addressed, but where do you see the big risks for where we are going?

So there's probably two big risks I'd flag. One is the geopolitical risks you said at the start. So this technology's highly sought after and the Americans are trying to do a pretty good job of making sure the Chinese can't get access to it, and that I suspect will upset them at some point. So there's that risk without a doubt that could affect the shovel side of the equation. The second risk is really around copyright.

So there's probably two big risks I'd flag. One is the geopolitical risks you said at the start. So this technology's highly sought after and the Americans are trying to do a pretty good job of making sure the Chinese can't get access to it, and that I suspect will upset them at some point. So there's that risk without a doubt that could affect the shovel side of the equation. The second risk is really around copyright.

Yeah.

Yeah.

Yeah. And I think this is overcomable, but if you think about back when we didn't want to put our data in the cloud-

Yeah. And I think this is overcomable, but if you think about back when we didn't want to put our data in the cloud-

Sorry, hold on, Nick. Do you reckon that ChatGPT would use the word overcomeable?

Sorry, hold on, Nick. Do you reckon that ChatGPT would use the word overcomeable?

Overcomeable? Probably not. It's a good point.

Overcomeable? Probably not. It's a good point.

It's a copyright issue here, I think. Go on.

It's a copyright issue here, I think. Go on.

We're going to use the, that's my thesaurus right there. But it can be overcome. From our point of view, if you think about when we moved to the cloud, everyone was worried about putting their data in the cloud and now we all happily put our data in the cloud. ChatGPT and generative AI is effectively mining your own data to give you predictive outcomes. Some people won't like that. They're reading your emails and that will take a little while for people to overcome or overcomeable.

We're going to use the, that's my thesaurus right there. But it can be overcome. From our point of view, if you think about when we moved to the cloud, everyone was worried about putting their data in the cloud and now we all happily put our data in the cloud. ChatGPT and generative AI is effectively mining your own data to give you predictive outcomes. Some people won't like that. They're reading your emails and that will take a little while for people to overcome or overcomeable.

Yes. Look, we're out of time, but at some point we might come back and talk about some of those risks because that whole copyright where the information and the data comes from is going to be something we'll be talking about for years, I dare say. But we are out of time. So Nick, I can say genuinely this is one of the more interesting, well, probably the most interesting interview I've done all year, Nick. I say that genuinely because it's not an area I know much about and you explained it in language that I could understand. So thank you for being part of Fear & Greed this morning.

Yes. Look, we're out of time, but at some point we might come back and talk about some of those risks because that whole copyright where the information and the data comes from is going to be something we'll be talking about for years, I dare say. But we are out of time. So Nick, I can say genuinely this is one of the more interesting, well, probably the most interesting interview I've done all year, Nick. I say that genuinely because it's not an area I know much about and you explained it in language that I could understand. So thank you for being part of Fear & Greed this morning.

It is actually April, so hopefully I can hold that title for the rest of the year, but thanks very much for having me.

It is actually April, so hopefully I can hold that title for the rest of the year, but thanks very much for having me.

That was Nick Griffin, founding partner and chief investment officer at Munro Partners. This is the Fear & Greed daily interview. Remember, this is general information only and you should seek professional advice before making investment decisions. Join us every morning for the full episode of Fear & Greed, Australia's most popular business podcast. I'm Sean Aylmer, enjoy your day.

That was Nick Griffin, founding partner and chief investment officer at Munro Partners. This is the Fear & Greed daily interview. Remember, this is general information only and you should seek professional advice before making investment decisions. Join us every morning for the full episode of Fear & Greed, Australia's most popular business podcast. I'm Sean Aylmer, enjoy your day.