David Lebovitz: Welcome to the Center for Investment Excellence, a production of JPMorgan Asset Management. The Center for Investment Excellence is an audio podcast that provides educational insights across asset classes and investment themes. Today's episode is on artificial intelligence and the power of disruption, and has been recorded for institutional and professional investors.
I'm David Lebovitz, Global Market Strategist and host of the Center for Investment Excellence. With me today is Joe Wilson, Portfolio Manager on the JPMorgan US technology strategy. Hi Joe, welcome to the Center for Investment Excellence.
Joe Wilson: Great to be here.
David Lebovitz: Well, it's going to be a pretty interesting and obviously relevant conversation here over the next 10 to 15 minutes. So, what I thought I would do is just talk a little bit about what we're seeing from a macro perspective, and then would love to bring you into the conversation and talk about AI broadly, and particularly what you're seeing as an investor.
And I think what's been so interesting about this year so far is that we came into 2023 with a view that economic growth was going to be more challenged in the first half of the year. Europe was going into recession, China was still locked down under zero COVID policy.
And in the event, growth during the first half of 2023 has been far more robust than expected, as Europe dodged recession, China reopened, and the US benefited from just better activity data globally, which effectively acted as a rising tide that has lifted all ships.
Meanwhile, inflation has been persistent. We got some good news yesterday about headline CPI coming down to 3%, but for those of us that look at the core figure, that's obviously remained a bit stickier, near 5%. And what I find so interesting about this backdrop is that the Federal Reserve has come out and said, look, we're not done. We think we've got one, maybe even two more hikes in us before the end of the year.
And meanwhile, risk assets, US equities, and large-cap technology stocks in particular, have been on an absolute tear, with a lot of that rally, in our view, driven by enthusiasm around AI. So, again, really excited to have this conversation. Let's start with the basics. How do you define artificial intelligence, and help us understand what a large language model actually is?
Joe Wilson: Right. So, like a lot of people, I used ChatGPT as soon as it came out. It was released November of '22, and my initial reaction was, this is magic. And it was actually close enough to that time of year when you write your holiday letter to your colleagues and thanking them for everything that they've done. So, of course, I used ChatGPT.
I prompted with one sentence. I said, congratulate my investment team for good performance in a difficult year in the stock market, and write something inspirational about the next year. And the output was four paragraphs, written way more eloquent than I ever could, but I wasn't quite happy with it, right?
So, I prompted again. I said, make it a little bit longer and make me sound more intelligent. And so, I had five paragraphs, and the words that came out had more syllables. And I signed it, happy holiday, and I put my name, and then in parentheses, I put ChatGPT. And what was more incredible than the content was the responses I got from the team that really didn't see that ChatGPT reference.
The emails I got back were, thanks so much, Joe. Love working with you. Can't wait till next year. We're going to crush it. And the magic here was how the technology had really just humanized the task I gave it. And to me, that's what AI is. You asked about what is the large language model. The easy definition is that it's a language model that's been trained on a huge corpus of data, really to create a probability distribution of language.
And the temptation here is to kind of reduce this down to it being a statistical trick. But what is more radical about the technology is that in pursuing the accuracy of next-word prediction, large language models really exhibit a deeper understanding of reality. And the way that this manifests today is that with the most advanced large language models, even though they haven't really been trained to be an expert in any particular one field, they have a strong proficiency across multiple fields.
David Lebovitz: And I think that's really interesting and really helpful to just kind of frame the broader conversation. Clearly, these are incredibly powerful tools that we increasingly have at our disposal, but Steve Jobs once described the computer as a bicycle for the mind, and I've heard others describe AI as a motorcycle for the mind.
Obviously, servicing a bicycle requires far fewer tools than servicing a motorcycle. So, the amount of computing power that's going to be needed here is clearly quite profound. So, when you look at the existing infrastructure you have to support these technologies, do we have enough? Is it the right kind? And how do you think about adoption of this technology increasing or decreasing as the technology required and the price that we have to pay for that technology changes over time?
Joe Wilson: I think the easy answer is no, we don't have enough of the right type of compute. In 2022, major hyperscale competitors, whether it's Microsoft, Google, Amazon, Meta, spent collectively over $160 billion in CapEx. And that's up incredibly from 10 years ago, where they spent close to $16 billion.
So, like in our thought, we think about things that can become much larger than what is expected. I think it's going to be that CapEx number. To imagine that being $1 trillion within the next five to 10 years might seem like a huge amount to spend, especially on this future compute architecture, but the reality is, is like we're already kind of on that trajectory.
And the architecture that's needed, whether it's parallel processing, GPUs, NVIDIA, obviously the market leader there, but also so much work that's being done across hyperscalers and emerging private companies to discover like what's that next computer chip that's going to be able to run more efficiently, drives this huge spend on custom silicon solutions as well too.
I think right now it's really an interesting time to realize that maybe the compute architecture that we've had for the last two decades isn't the one that's going to solve for the next decade. And that's going to be a struggle as hyperscalers change the architecture pretty dramatically. And then in terms of pricing, I think right now pricing isn't really advantageous on the buying side because there's just way more demand than there is supply.
And I think naturally prices will come down. We'll find new ways to improve models to become more efficient. But as that happens, just like so many other technologies that have come before, usage increases. We find ways and new ways as prices come down that drives demand much higher than what was expected.
David Lebovitz: And I think that that's key. When we look back over time, this is usually the way that it plays out, where when a new technology first becomes available, it's oftentimes out of reach from a pricing perspective, but as more and more players enter the space, that competitive pressure allows for lower and more reasonable prices, which historically has then driven greater adoption.
And I think what's particularly interesting, listening to what you're talking about in terms of the infrastructure, the increasing use of things like the cloud is, not only is this something that the private sector is going to be focused on, but as we've seen, kind of fiscal forces have been unleashed, and there could arguably be a tailwind from the public sector as well.
And so, a lot of moving parts here, and I want to switch gears and talk a little bit about what this means for you as an investor. So, can you help us understand how early or late are we in this adoption process more broadly? And there are clearly some very big names out there that are playing in the space.
You know, given who you're talking to and what you're seeing, is this an instance where the big are going to get bigger or newer players are going to come in and begin to take more market share?
Joe Wilson: You know, there's so much change happening just so quickly that I think this is a time to have views and conviction, but have them loosely held, right? And so, I have these debates with people on my team and with my inner dialogue as well, too, is like, is this time different where the big do get bigger? Or is this like every other era that's come before where the disruption comes from an emerging player that we've never heard about, right?
Like these white papers that we have written before we published this diagram that just shows one era to the next, whether it was mainframe to PC, to internet, to mobile cloud. And in each of those decades, the leadership and market cap changes dramatically. It's very rare to hold onto that.
And I lean towards that being the same as well as we go into the AI race, but it's just still, we don't have enough information. It's really hard to imagine what it's going to look like in 2030, but I do have a strong feeling that the list of market cap leaders in 2030 is going to look dramatically different.
David Lebovitz: So, it sounds like we're arguably pretty early on in this broader process, and I think that it's a really important point. And I love that diagram in the paper that you guys published back in 2020 that clearly illustrates how the key players have changed over the course of the various technology cycles that we've seen.
It sounds like there may not be winners and losers in the AI race, but rather winners and mega winners. And so, what types of businesses are you seeing that you think will be successful in this environment? And then what types of businesses are you seeing that really might even go beyond that and really capitalize on the opportunity they've been presented?
Joe Wilson: You know, there's excitement across all the different segments of technology today in terms of who is capturing the biggest opportunity or who's most well positioned. But I think what is so obvious that AI is the next platform is that you have like every company acknowledging this and incorporating it into their business, whether it's a tool or a feature or whether it's a platform.
And we've yet to see really what the next platform is. And maybe it's open AI or companies that look like open AI that have already built these large language models. But there is also that other side of thinking like maybe the big winners are those companies that have harnessed and have large collections of federated data that is maybe very wide and has a large breadth across many different verticals and expertise, but also very niche as well.
And in making these large language models smarter, using that specific data to help inform and give voice to an enterprise is going to be very powerful. That's yet to be seen on who's going to dominate in the future, if that's going to be an emerging company that develops that and understands that customization is going to be extremely important in the enterprise, or if it's one of the existing players, which I guarantee all large enterprises are going to rely on at least right now at this timeframe for advice on how to navigate AI.
David Lebovitz: Well, certainly a lot of moving parts here. This has been a fantastic conversation. Thank you for helping us better understand AI, large language models, and give us a little bit of a glimpse into what you're seeing from your seat as an investor. Maybe I'll give you the last word here. Anything else you would want to leave our listeners with before we call it a day?
Joe Wilson: You asked before just about the investment implications. And I think having that open mind and that flexibility to rethink even what you had the strongest conviction in yesterday is really important. And to imagine what this world's going to look like in 2030 when we do the look-back is that there will be disruption.
I guarantee that the 10 leaders of today will not be the 10 leaders of 2030. And it's going to be companies that maybe we've heard of, but it's also those companies that are forming today. Like, this is such an exciting time from an entrepreneur and a startup community. And what we've seen over the last decade is that businesses are formed and scaled in a very, very quick way. And I think that's what I'm most excited about from the investment side as we go forward.
David Lebovitz: That all does sound very exciting. Clearly, the investment universe and landscape is going to continue to grow and evolve. And Joe, it sounds like we'll just have to have you back for another conversation here in a couple of months.
Joe Wilson: I look forward to it.
David Lebovitz: All right. Well, thanks again for joining us on the Center for Investment Excellence. Thank you for joining us today on JPMorgan's Center for Investment Excellence. If you found our insights useful, you can find more episodes anywhere you listen to podcasts and on our Web site. Recorded on July 13th, 2023.
Coordinator: Not for retail distribution. This communication has been prepared exclusively for institutional wholesale professional clients and qualified investors only, as defined by local laws and regulations. The views contained herein are not to be taken as advice or a recommendation to buy or sell any investment in any jurisdiction, nor is it a commitment from JPMorgan Asset Management or any of its subsidiaries, to participate in any of the transactions mentioned herein.
Any forecasts, figures, opinions, or investment techniques and strategies set out, are for informational purposes only based on certain assumptions and current market conditions, and are subject to change without prior notice. All information presented herein is considered to be accurate at the time of production. This material does not contain sufficient information to support an investment decision, and it should not be relied upon by you in evaluating the merits of investing in any securities or products.
In addition, users should make an independent assessment of the legal, regulatory, tax, credit, and accounting implications, and determine, together with their own financial professional, if any investment mentioned herein is believed to be appropriate to their personal goals. Investors should ensure that they obtain all available relevant information before making any investment.
It should be noted that investment involves risks. The value of investments and the income from them may fluctuate in accordance with market conditions and taxation agreements, and investors may not get back the full amount invested. Both past performance and yields are not reliable indicators of current and future results. JPMorgan Asset Management is the brand for the asset management business of JPMorgan Chase & Company and its affiliates worldwide.
To the extent permitted by applicable law, we may record telephone calls and monitor electronic communications to comply with our legal and regulatory obligations and internal policies. Personal data will be collected, stored, and processed by JPMorgan Asset Management in accordance with our privacy policies at https://am.jpMorgan.com/global privacy.
This communication is issued by the following entities. In the United States by JPMorgan Investment Management Inc., or JPMorgan Alternative Asset Management Inc., both regulated by the Securities and Exchange Commission, in Latin America for intended recipients use only by local JPMorgan entities, as the case may be, in Canada for institutional clients use only by JPMorgan Asset Management Canada Inc., which is a registered portfolio manager and exempt market dealer in all Canadian provinces and territories, except the Yukon, and is also registered as an investment fund manager in British Columbia, Ontario, Quebec, and Newfoundland and Labrador, in the United Kingdom by JPMorgan Asset Management UK Ltd, which is authorized and regulated by the Financial Conduct Authority, in other European jurisdictions by JPMorgan Asset Management Europe, S. r.l., in Asia Pacific, APAC, by the following issuing entities, and in the respective jurisdictions in which they are primarily regulated; JPMorgan Asset Management, Asia Pacific Ltd, or JPMorgan Funds Asia Ltd, or JPMorgan Asset Management Real Assets Asia Ltd., each of which is regulated by the Securities and Futures Commission of Hong Kong, JPMorgan Asset Management, Singapore Ltd, Company Reg number 197601586K.
This advertisement or publication has not been reviewed by the Monetary Authority of Singapore, JPMorgan Asset Management, Taiwan Ltd, JPMorgan Asset Management, Japan Ltd, which is a member of the Investment Trust Association Japan, the Japan Investment Advisors Association, Type II Financial Instruments Firms Association, and the Japan Securities Dealers Association, and is regulated by the Financial Services Agency, registration Number Kanto Local Finance Bureau Financial Instruments Firm number 330, in Australia, to wholesale clients only as defined in Section 761A, and 761G of the Corporations Act 2001 Commonwealth by JPMorgan Asset Management Australia Ltd, ABN 55143832080, AFSL 376919. For all other markets in APAC, to intended recipients only.
For US only, if you are a person with a disability and need additional support in viewing the material, please call us at 1-800-343-1113 for assistance. Copyright 2021, JPMorgan Chase & Company, all rights reserved.
LISTEN AND SUBSCRIBE