Motley Fool Money - Tech's Past and Future

Episode Date: March 29, 2023

Gordon Moore and Moore's Law helped define a transformational period in technology. We reflect on his legacy and look at how the next chapter of tech leaders are trying to shape the future and the development of AI.  (00:21) Tim Beyers discusses: - Moore's Law and Gordon Moore's mark on the tech industry and the world - How semiconductors became such a critical industry - Intel's disciplined approach to capital allocation AI Open Letter: https://futureoflife.org/open-letter/ai-open-letter/  (15:46) Nick Sciple and Tim Beyers go head to head in our Market Madness Championship. Who will cut down the nets?  Companies discussed: INTC, MDNY, BWXT  Host: Dylan Lewis  Guests: Tim Beyers, Nick Sciple  Producer: Ricky Mulvey  Engineers: Dan Boyd, Tim Sparks Learn more about your ad choices. Visit megaphone.fm/adchoices

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I'm Dylan Lewis sitting in for Chris Hill, and I'm joined by Tim Byers. Tim, how's it going? Fully caffeinated, ready to go, Dylan? Let's hit it. Love it. Tim, sometimes when things happen on a Friday or over the weekend, it can take us a little while to get to it because the news machine starts right back up on Monday. And because I was having you on today, I wanted to rewind.

and talk about something that happened on Friday, the passing of Gordon Moore. He was the co-founder of Intel, and his name sounds familiar to listeners because he is the Moore of Moore's Law. And, Tim, I don't think it's a stretch to say he is kind of a singular character in the technology landscape. Oh, no doubt. No doubt. And for those who don't know what Moore's law is, Gordon Moore wrote this paper in 1965,

in which he articulated a thesis that, the density of a microchip. And at that time, in 1965, what was considered a microchip then was pretty macro, but the components of a microchip, the diode, the resistors, capacitors, and transistors, like the density of a chip would double. And effectively, its compute power would double every year for the next 10 years.

And then in 1975, he sort of expanded this definition, to say roughly every two years. And I think in recent years, Moore's Law has been maybe stretched beyond its usefulness because now we are manufacturing chips at the, you know, five nanometer level, which is just, you know, microscopic upon microscopic levels and just incredible densities on a single dye of silicon. It's, it really is amazing. But for a lot of, long time. This really did govern the economics of what we came to know as the computer industry. Gordon Moore was a pioneer in this era. Certainly, he's best known for Intel, but he goes back to some of the early days of Silicon Valley, which we can get into a little bit as well, Dylan.

Yeah, I was going to say, Tim, there is no Silicon Valley without Gordon Moore. I think it's just the Valley at that point, right? Yeah. I mean, it's Orange Grove. Groves, to some degree. I mean, it's not literally just Orange Groves, but in 1957, Moore is one of eight that are colloquially in history known as the Traderis 8 who left Shockley semiconductor laboratories. William Shockley is the inventor of the transistor. And back at that time, that was such a breakthrough, and it came out of Bell Labs where Shockley worked. He was well-known as a brilliant scientist and recruited a bunch of PhDs, including Gordon Moore, to work for him in 1955 for Shockley, you know, Semiconductor Labs within two years, you know, just the authoritarian nature of Shockley. It just essentially turned these, these eight, you know, brilliant scientists against him. And Moore is a chemist by training,

as his Ph.D. out of Caltech, did postdoctrine work at Johns Hopkins. And they go off to form Fairchild Semiconductor, and they form it out in Silicon Valley. What we now know as Silicon Valley, Moore is out from that part of the country. He is from Northern California. And so within 11 years of the forming of Fairchild Semiconductor, Moore and Bob Noyce go off to co-found Intel, and the chip race is on. And I mean, really, the entire innovative culture of Silicon Valley, I think, can trace back to those early days of Fairchild and then the spinoffs out of what we, you know, in those of us who follow technology history, we call Fair Children. And Intel is one of those fair children because of Nois and more. But, I mean, really just that idea of meritorious achieve.

that goes back to the Eulet Packer days. Intel is part of that, this idea of meritocracy of like, best idea wins. We are trying to build the future out here in Silicon Valley. And Gordon Moore is such a huge part of that, Dylan. I think that's one of the things that is maybe most surprising if you're learning about him late is he's known so specifically for his technological foresight. But really, he was transformational in the way that companies worked in the culture of companies,

and also the way that management teams thought about capital and thought about their balance sheets. Right. And I mean, I think he continued some of the pioneering work of Bill Ullett and David Packard, who really did start the idea of the garage startup in Silicon Valley. So, I said Orange Groves originally. It's really not fair to say that because Eulet Packard goes back beyond that. But there is a real blossoming of an innovative subculture that crops up out of the defense industry in Northern California in the late 1960s and early 1970s.

And Intel is a huge part of that. But more kind of, he does something. something really interesting that continued through successors at Intel up through Andy Grove, who was famous as an Intel CEO who wrote a book called Only the Paranoid Survive. And the real basis of that is if you look at the data that we have, the publicly available data we have, for 25 years, 1991 to 2015, Intel ran a surplus on its balance sheet, always had more cash than debt, always had a surplus of cash. Because the semiconductor industry for such a long time, Dylan, and just technology in general, ran in cycles. And there was

really nothing more cyclical than the semiconductor industry. And so Gordon Moore, as CEO, and then Andy Grove later on, were famously frugal, deliberate, disciplined in running Intel, not just as a monopoly, because let's be fair, it did grow up as a monopoly in the semiconductor, particularly the personal computing, you know, personal computing chips, part of the business. They did build a natural monopoly, but they were also very disciplined about it and ran one of the strongest balance sheets in the history of Silicon Valley for a really long period of time. That's no longer true, sadly. I'm hoping that in the the wake of Gordon Moore leaving this world, that we're going to recapture some of that discipline

that really was a big part of Silicon Valley for a long period of time, Dylan. And I think we need it again. So here's hoping that would be a great tribute to Gordon Moore, I think. Speaking of technology and discipline, Tim, our second story today switches gears a little bit from the technology and the leaders that got us here to the technology of the future. And I wanted to talk about the story of tech leaders, including Elon Musk, researchers at Deep Mind, academics from universities across the globe, asking for a pause in the training of AI systems that are more powerful than GPT4. A note is making its way around the internet now. It's called Pause Giant AI Experiments in Open Letter. Tim, it characterizes the current state of AI as an

out-of-control race to develop and deploy ever more powerful digital. minds that no one, not even their creators, can understand, predict, or reliably control. And this letter is really asking for discipline and a bit of a pause in this space that feels like it's kind of running away a little bit from its creators. Yeah. I am annoyed that I agree with Elon Musk. I really am. I'm annoyed that I agree with him, but I fully agree with this. Because there's, I have some. good faith disagreements with Musk in some of the ways he's running companies he's in control of but on this point I think he and his peers who have penned this letter have

a point because there is a truism about exponential growth Dylan and this has been true in the technology industry for a very long period of time when you introduce exponential growth, you also introduce the possibility of exponential errors that lead to catastrophic results. Anytime exponential growth is introduced into any system, unforeseen outcomes can be a part of the process. So that's in nature, that's in technology. That's really in anything. And so, the caution here about let's be careful before we just get drunk on exponential growth. That is exactly right because one of my fears with AI, Dylan, is we're going to think up new and more efficient ways to train AIs. And one of the most popular ways to think about this is, you know what,

let's train up AI machines to train our AI machines. And my catastrophizing, anxious brain goes back to 2008 and 2009, Dylan, and the idea of bankers saying, you know what, these collateralized debt obligations where we're just going to throw a bunch of mortgages together and securitize them and just kind of throw them out there and say like, hey, let's just sell these things. We'll just throw the mortgages together. And it'll be fine because we're reducing the risk because we're putting a lot of mortgages together. And they were like, yeah, you know what that works? But let's up the game a little bit.

Let's actually take those packages and package the packages and call them synthetic CDOs. And we know what kind of bomb that went off after that. That is an example of exponential growth going horribly wrong. So I do think the idea of recognizing that exponential growth in and of itself, is not inherently great is a pretty good take. I was going to say, Tim, I feel like a lot of AI anxiety really hinges on the black box element of things, where you simply don't know what's inside and things have kind of been abstracted away as you talked about in that parallel with collateralized mortgages.

And the letter here is asking AI labs to develop safety protocols for AI design and development to set up auditing and oversight from independent experts. And the discipline side of it, the wanting to make sure we are innovating in a way that makes sense, all of that makes sense to me as an unsophisticated user of technology. But I guess my question is, how realistic is this? Because every big company is shoveling money into AI right now. And I feel like game theory is on the side of the arms race, not on this six-year-old. month pause to help figure things out.

I think you're right. Sadly, I think you're right about that. I think the answer here is more humans in the process. Not fewer humans, more humans in the process. Like where AI is potentially incredibly interesting is in making humans more productive, more thoughtful, asking better questions. An AI is really good at automating. It provides speed.

Let's put it this way. What we have in terms of AI right now isn't actually all that intelligence. In fact, I call it dumb. There is no context. An AI can't give you context. And it only learns what you, you teach it. This is why exponential growth is a danger, because if you teach it bad things,

it will just do more bad things at a higher rate of speed, creating more errors and maybe security issues and so forth. But if you put humans and AIs together, where a human being can step in and say, actually, that's not right, you need context here that I have and you don't, like, that is a very interesting way to govern AIs and put in guardrails that makes some sense. But I do think you're right. There is this belief, and here's one of the dangers, is that if you have the largest trained data set, then you win, which makes that leads to the arms race argument, Dylan. So you have a lot of people who are saying, like, get me as much data as you can

and feed this machine with as much data as possible. And the danger there and why this pause makes so much sense is, shouldn't we ask what kind of data we want in the machine? Like, that is important. We really need to ask that question. So this is why I agree with this framework of like, let's breathe, let's ask what kind of data we really want in these machines and then make some decisions about how we get

that data in and then how we monitor it to make sure that the quality of that data is actually good. And we're not just introducing errors and bad faith ideas at exponential scale. Listeners, we will drop the link to the open letter into our show notes for today's episode until he's replaced by machine. Tim Byers, thank you so much for joining me today. Thanks, Dylan. Listeners, the Motley Fool's stock market madness Competition comes to a close right now. After fending off the competition, Nick Seiple and Tim Buyers meet in the finals and compete for one shining moment. To kick off the finals of Stock March Madness, Nick Seiple, you have two minutes to recap your stock.

Okay, yeah, happy to jump in here. My company, if for folks are not already familiar, is BWX Technologies. It's a leader in nuclear technology, both on the defense side, also in commercial nuclear power and healthcare. Over three quarters of the revenue comes from the defense side of the business where they've been a monopoly provider of reactors and fuels for U.S. nuclear propulsion submarines and aircraft carriers for over 50 years. Also a leader in a cutting edge nuclear development for the government going to build the first microreactor in the United States starting in 2024. Also new opportunities abroad as the Australia, U.S., U.S., U.K., military partnership begins to roll out, where Australia is now going to be able to

order up to five U.S. nuclear subs over the next decade. Another 15% of the company's sales comes from the commercial nuclear power business where they manufacture the Can Do nuclear fuel and components that power nuclear reactors across Canada. Also have a partnership with GE Hitachi. Actually, signed the engineering agreement last week to provide the reactor pressure vessel for their BWRX 300 small modular reactor. Also this week, the Canadian 2023 budget came out, includes a 15% tax credit for new nuclear, both, but, you know, small and large nuclear deployments, as well as existing nuclear plant refurbishments. That's a business that BWXD operates in. So lots of tailwinds behind that business.

Then lastly, they have a healthcare business that's been under development for the past five years. Now is about to reach commercialization here in the year of 2023. Going to be able to provide most of the nuclear isotope needs for healthcare applications across North America and really opening up a new opportunity for the business. All that, pulling all that together with the capital needs coming. down for the healthcare side of the business. Expect to see free cash flow increase. Forex this year from $50 million last year to $200 million this year. Free cash flow inflecting higher tailwinds pine to all sides of the business. It's a company worth backing.

Five minutes. Tim Byers has to recap his stock and offer a rebuttal. Monday.com is the low-code productivity software leader. By low code, what I mean is you program the environment you want, but you don't have to write code to do it. It's very common to see this now. You might be using Airtable. Airtable is a low-code environment. So is Monday. And Monday happens to be an incredibly efficient business.

But I'm going to start by talking about valuation because a company like this, usually you don't want to lead with that. Feels like leading with your chin. Except in this case, it's not. Monday trades for about 11-time sales. And I want to focus on this only because I'd like to introduce something. When I do valuations around this, and I do valuations around these types of companies, if you're going to use the price to sales ratio, let me tell you how to use it in a productive way.

You can't use it in isolation. If you're going to use it, the thing that's worked best for me is when the growth of the company is at least three times greater than the price to sales ratio and margins are going up, and signs of free cash flow are already starting. All three of those things are present for most. Monday.com right now. So at an 11-time sales multiple, you should be expecting Monday to deliver at least 30%, really 33% or even 35% revenue growth. Over the last several quarters, 56.9%, 64.9%, 75.2%, 83.9% year-over-year revenue growth. That's what we've got in Monday.com.

while margins are going up. Operating margins now have come in under less than 10% now. It's still negative, but it's trending up in the latest quarter. They turned free cash flow positive. This is a business that has a large and expanding ecosystem of partners that are betting on the platform, and they're doing more work on top of Monday.com. So not only you have clients that are doing a lot more work. The net revenue retention rate is over 120%. So customers are spending 20% more every year on top of the product. So I've done my own work on this. I think it's cheap compared to what the long-term growth opportunity is. I think it trades at a pretty reasonable multiple. Last thing I'll say about this is you have a pretty reasonable compensation package for this particular company.

All of the major executives make less than $300,000 a year. They do give out a fair amount of stock-based compensation in 2022, $17.5 million, all of those options are well over $200 a share. They have huge incentives to lift this company, and they own collectively over 17% of the business. For me, Monday.com is an interesting business. It's a reasonably priced business when you consider its growth, and it has all six signs of a rule breaker. It's one I want to watch. Dick Cyple, three minutes for a rebuttal is yours if you want it. Sure. I think Tim lays out a good case for Monday.com, a really strong growth from the business. I think just kind of comparing and contrasting these two businesses.

You've got a monopoly on the case of BWXC and a lot of the industries they operate in Monday. Clearly, there's some advantage when you see lots of that growth, but they are not the only company that provides these services. Lots of growth happening, but you're seeing along with that growth, losses continuing to expand. We've got stock-based compensation for X cash flow from operations. So, you know, you're certainly, you need a lot more growth from Monday.com and, you know, the growth they've demonstrated in the past to start dropping to the bottom line for the company to work.

Certainly much less growth when you look at BWX technologies, but I would argue much more insulated from competition, just given that you're a monopoly player. Also, you know, Tim talked about, you know, some of the rule breaker frameworks. I think another rule breaker thought process we could throw out here is the snap test. I would argue that WXT, if you snapped your fingers and the monopoly provider of nuclear propulsion systems for the U.S. Navy disappear, the world would miss it very, very quickly. And I think it would take a lot. The world would adjust much more quickly to the loss of Monday.com.

I think both great businesses, both with strong prospects. But I would choose the monopoly with current free cash flow over the company that is growing very fast and certainly has some edge over its competition. but is yet to show a bottom-line profit. This segment originally aired on our member live stream. Members of any Motley Fool service can watch at live.fool.com. Members crown Nick Seiple, the champion, with 60% of the votes. But podcast listeners, we want to know what you think, too.

Write in to podcasts at Fool.com with the moments that made the montage for you and ideas for future segments for the show. That does it for this episode of Motley Fool Money. As always, people on the program may have interests in the stocks they talk about and The Motley Fool may have formal recommendations for or against. So don't buy or sell anything based solely on what you hear. I'm Dylan Lewis. Thanks for listening. We'll see you tomorrow.