Turning Point: The Transformative Potential of AI

Audio Description

AI may prove to be an iPhone-level disruptor across industries. We’re still early in its product cycle, but things are moving rapidly.


This transcript has been generated by an A.I. tool. Please excuse any typos. 

Stacie Jacobsen: [00:00:00] Thanks so much for joining us today on the Pulse by Bernstein, where we bring you insights on the economy, global markets, and all [00:00:15] the complexities of wealth management. I'm your host, Stacie Jacobsen. If I sound strange, that's because I'm an A.I. trained on Stacie's voice. And now back to the real Stacie. On today's show, we're discussing the transformative potential of A.I.

Recently, the [00:00:30] language processing tool Chat GPT has captured the imagination of the public and highlighted how far A.I. technology has advanced. I'm pleased to welcome as my guest, Lei Qiu, Senior Vice President and portfolio manager of the AllianceBernstein International Technology [00:00:45] Fund and AB Disruptor's ETF.

First, let's take a pulse of the market. US equity markets are off to a very strong start this year blowing through 2023 analyst estimates. Now, this is in large part due to the exceptional strength in the [00:01:00] stocks of just a few companies at the forefront of artificial intelligence, which is the main topic of our agenda today.

So, what's in store for the second half of the year? Well, we think the US equity market is already pricing in or assuming a soft landing for the economy. [00:01:15] This shouldn't be too surprising given the continued strength in the labor market and consumers’ willingness to just keep opening up their wallets.

But given the relatively rosy scenario, we are generally cautious on stocks in the near term while continuing to look for pockets of value. [00:01:30] Now, as for fixed income markets, we think taking on some interest rate risk will benefit investors' portfolio, especially when rates eventually decline. For a more in-depth view, check out the quarterly letter from Alex Chaloff, Bernstein's CIO, on our website.

AI [00:01:45] is not a new field. Tech companies have been innovating in this space for decades, but chat GPT represents an inflection point. For the first time, the general public has access to a user-friendly version of AI that can answer complex questions, generate [00:02:00] language that sounds convincingly human and automate time consuming tasks.

As a result, chat GPT attracted more than a hundred million users in just the first two months. Suddenly people are not only enjoying the benefits of ai, but they're also [00:02:15] concerned about negative impacts for investors. AI presents challenges and opportunities such as when is the optimal time to invest in companies that might benefit from AI?

As with any disruptive technology, AI will likely bring [00:02:30] about major changes that we can't yet imagine. So, we'll explore all these issues and more with my guest when we come back. Stay with us.

Clare Golla: I'm Clare Golla, host of Bernstein's Inspired Investing, a [00:02:45] podcast for those engaged in the nonprofit, philanthropy, and broader social sectors. Tune into our next episode as we challenge the conventional wisdom surrounding this year's Giving USA Report. Listen and subscribe to Inspired Investing on your favorite podcast [00:03:00] platform.

Stacie Jacobsen: Welcome back to The Pulse by Bernstein. I'm here with Lei Qiu, portfolio manager for the AllianceBernstein International Technology Fund and AB Disruptors ETF lei. Thanks so much for joining us today. [00:03:15]

Lei Qiu: Oh, thank you for having me. Glad to be here.

Stacie Jacobsen: Now, look, we are still very early in the product cycle for AI, but it is moving rapidly.

Can you talk to us about how it's disrupted the companies you cover thus far?

Lei Qiu: I think to your point, we are [00:03:30] still in the very early stage of AI. I do think it's a transformational change that we are seeing in innovation in the marketplace that we see today, and that many people compare it to sort of the iPhone moment that we are seeing in terms of productivity.

I actually wholeheartedly agree [00:03:45] with that, but I also would acknowledge that we are still in the very early stage of that, a lot of people making a lot of predictions, and I would say with many of the big technological innovation that we have seen, you tend to overestimate it [00:04:00] in terms of the impact in the short term, but underestimate the impact in the long term.

So, I would say as we stand today, I think every company is. Evaluating its business model and how they can deploy ai, whether AI is a friend or foe, [00:04:15] but it's still too early to tell in terms of the ultimate impact that AI will have.

Stacie Jacobsen: Got it. So, let's talk about some of those short term and longer-term impacts.

So, if you were to look out over the next, call it 12 to 18 months, what do you think some of those shorter-term impacts of AI [00:04:30] will be?

Lei Qiu: In my mind, AI poses the ultimate question for every company, which is, what is your competitive mode, and will you survive AI? Because AI is such a transformational change that is such a [00:04:45] productivity game and knock down the entry barriers.

So, companies certainly cannot ignore it. And so, what we have seen is a lot of companies are rushing to adopt AI. We certainly have seen a lot of the large platform companies are spending tremendous amount of. [00:05:00] Uh, time, effort, and money on it. So, when we think about ai, it is something that's extremely compute intensive that we know for a fact.

So, it's a tremendous amount of data that's being generated. They need to be processed. And then [00:05:15] we are going to, uh, feed it into the training model and train the supercomputers. So, what is happening is that we have seen the rush to spend. So, when we think about the innovation S curve, if you will, and then we look through the past cycles where we are in the ai, [00:05:30] it's sort of

early stage in terms of the build out of the networks. So, when I say networks, we're thinking about the hyperscale data centers, the spend on the servers, and then where the training is happening. And then just generally speaking in terms of the increasing [00:05:45] compute intensity. What we’re seeing is, um, I expect to see greater demand for a lot of the enablers, whether it be the semiconductor company, the equipment companies, uh, whether it be the networking memory.

A lot of it in the hardware area that's happening [00:06:00] today. I could expect that change to continue and if anything will ramp rapidly in the next 12 to 18 months. Uh, we are also seeing some companies starting to roll out some applications, but it's still early. But ultimately, what shape or [00:06:15] form in terms of business model it takes, it remains to be seen.

Stacie Jacobsen: Got it. It sounds like the more immediate beneficiaries of AI are the hardware companies, you know, if we start to look out even further than that 18 months and longer terms, you mentioned the iPhone and you know, I [00:06:30] try and tell my kids what life was like before we had that device in our hands at all times, and it's very hard to actually comprehend.

So where do you think that AI might take us, and I, I admit this is very speculative at this point in time, but over the longer term,

Lei Qiu: AI itself has [00:06:45] been around for quite some time, and this current iteration of ai, the generative AI, is probably the most powerful, and it has reached an inflection point in terms of adoption, in terms of what it could do for us.

I've been around. You've been around, and then just think about the time before iPhone. So, it [00:07:00] took a while for iPhone, even if you had the iPhone, if you didn't have the network. And the broad built out network, it wouldn't work, and it would not build out a whole ecosystem after that. What we have seen is, you know, since the [00:07:15] pandemic, and it's been going on for some time now, but the pandemic itself certainly has accelerated the digitization of the society and the amount of data that we generated so that, you know, so much data is generated, we can feed it into the uh, model.

And then actually get. Output from it. [00:07:30] And the other thing is you kind of have to use your imagination, right? We had a network built out, then we had the devices. Then ultimately we have an entire mobile ecosystem that was built on top of that. In seven to 10 years, I could imagine there [00:07:45] will be a whole ecosystem that built on AI.

And it doesn't even have to be seven to 10 years, frankly. And the history has shown that. It could just be in the next three to five years, we can see an entire ecosystem built on AI, but as we stand today, I [00:08:00] would think a lot of it could be, uh, efficiency tools that enterprise can embrace. And then some of the mundane labor can be replaced by machines.

And then there are also other creative changes that we don't see today. And it will come with time [00:08:15] once, you know, the whole, uh, infrastructure layer is built out.

Stacie Jacobsen: All right. That's helpful. You know, we talked a little bit about some of the short-term impacts, but you know, specifically what are some of the responses that you're seeing from companies in the tech sector?

Really just more [00:08:30] across the industries, broadly.

Lei Qiu: We definitely have seen, you know, on the consumer side, you know, people are talking about the new way of interacting with machines, right? We can, for instead of getting sort of set response fed to us in the [00:08:45] machine language, we can actually have something that's a lot more interactive.

On the consumer side, people talk about search, you know, will be different and, uh, the way that we think about travel or. Just in general, the way that we plan our life will be different, and that's one aspect [00:09:00] to it. Uh, I think on the consumer side you can also see, you know, in terms of how we can come up with new mode of entertainment and using AI as a tool, that will be different as well.

But I think the bigger impact we expect to see would be the efficiency gain. [00:09:15] So we are seeing a lot more companies today that actually is embedding AI in the tools that they're offering to enterprises. Actually, made companies far more efficient. One of the greatest challenges that we have faced in recent years, frankly, is the labor shortage, the [00:09:30] rising inflation as a result of that.

And I think AI will be a solution to that because it actually makes some of these really maintain tasks obsolete because the machine can do it in a far efficient manner, and we're seeing company use that. We’re seeing it [00:09:45] in the early stage as part of the tool set that's being offered to enterprises, we're also seeing companies, larger companies to date, certainly, uh, embedding AI in the offerings that they're providing and making their tool more effective or powerful.

Stacie Jacobsen: Chat GPT [00:10:00] is what we hear about the most. How is that really driving innovation?

Lei Qiu: So chat GPT is, it's really exciting. It's one of the apps that's the fastest app to reach a hundred million users, and that also gives you a sign of, uh, gives you a sign of the [00:10:15] time we live in, which is, we all live in a connected world.

So, you know, it may take a little while for another app or you know, a, a channel to get to that many listeners, but we certainly got to a hundred million users really quickly. So that does show you [00:10:30] that. We've reached a point where people are very excited about it. We've always talked to machines, but the machine talked back to us, and we are always reminded that we are simply.

Talking to a machine, but chat GBT is one where we could actually imagine that the machines [00:10:45] interacting with us in a human-like form through open AI and generative ai. It's very exciting. But I would also say though it could be so much more, so it's not really lost on some of us that you know, it just.

It's still in its [00:11:00] very primitive form. It's still pretty standard, and it's not as personalized as we would like it to be. And then in the future it could be so much more, but that's my point, which is we're still in such early stage of adoption. You know, it's interesting. The [00:11:15] feedback from the machine is only as good.

As how much data you feed into it. The more data you give it, the more people use it, the smarter it gets. Right. It's an iterative model, so you know, it's not a dissimilar from, you know, the early stage of cell phone when it was. [00:11:30] I remember in Pretty Woman, Richard Gere had that big cell phone. It's as big as a brick.

And then, you know, 20 years later, look, we have, and all the changes that it has made in our lives. I would say chat, G P D is a starting [00:11:45] point. It got a lot of excitement, but it marks an inflection point of what AI could be. But ultimately what. What is going to be something that adds a lot of productivity and then make our life easier, it remains to be seen.

[00:12:00] So yes, it's a good starting point. It's a very exciting starting point in terms of how big the AI could be, but it's definitely far from what it could be.

Stacie Jacobsen: Yeah, and sometimes the answers that you get from chat GPT are very convincing, but when you read through them, there's [00:12:15] actually that concept of hallucinations, right?

That is actually is not the right answer. So can you tell us a little bit about that? Why does that actually happen?

Lei Qiu: It's, it's sort of like I said, you know, it's like things go through iterations, right? It's just so early still, [00:12:30] and then it has to personalize it. It sounds convincing because it's giving you a set of answers that it knows, but.

It's the reason that we are excited about this generation of AI is because it is dynamic, and that's why it's so compute, [00:12:45] intensive error. It's taking all these different data and then constantly iterating. And then that's what we call, like, you know, the computers being trained to give you a set of answers, but then ultimately there's the inferencing part, and then it's going to give you things that's actually tailored to you.

And [00:13:00] that could take time for it to learn and then to actually adapt. And so, it looks very convincing today, but it may not be the right answer actually, so it's going to learn. It's not that different from, you know, in the early days of search, right? Search got better [00:13:15] and better because it learned. It takes time for that knowledge base to build, and the more people use it, the more intelligent it gets.

So that's why everything takes time.

Stacie Jacobsen: Yeah, for now, you still definitely have to have that human touch to make sure that the [00:13:30] responses or the summary that it's giving, uh, makes sense. Caution to all those college kids who are using it to write their essays, right.

Lei Qiu: Yes, definitely.

Stacie Jacobsen: All right. I'm going make a comparison to, um, the ESG world and greenwashing, which occurs when companies [00:13:45] try to project an image of being environmentally responsible, but yet they're not.

I'm wondering if you see the same thing happening with AI companies, really just paying lip service to the concept, but they're not really positioning their business to take advantage of AI [00:14:00] in a profitable way.

Lei Qiu: I think this is actually a very interesting question. I think AI is probably the most mentioned word on any quarterly earnings call in the most recent quarter, and every company feels like if they mention the word AI, then they [00:14:15] are AI.

But that's actually definitely not true, and I would caution all investors or listeners to be careful because as I mentioned at the very beginning, this is the big question that it's posing to [00:14:30] everyone. Is AI going to change your competitive mode because it knocks down entry barriers. So just because you mentioned AI does not mean that you can actually survive ai.

Your business model is being challenged and it depends on how you embrace [00:14:45] it and how advanced AI is. And AI could, you know, it could. Challenge the very existence of some companies,

Stacie Jacobsen: and you are on the forefront of the lines of investing here on this cutting edge and disruptive technologies. Do you see any near-term use cases for AI that you [00:15:00] believe might lead to greater efficiencies or really just important changes in the way that we conduct business?

Lei Qiu: Companies such as Microsoft, you know, is already embedding AI in some of the tools that they, they are offering to their users. I think you will start to [00:15:15] see more and more companies, such as Microsoft, embedded in part of their product offerings to make their product actually more powerful and can actually, you know, do more things for the enterprise and they eliminate some of the inefficiencies that we see today.

I [00:15:30] do think you will start to see that, and that's the first step. Ai, it is probably one of the biggest productivity gains that we are going to see in our lifetime if deployed properly. We are still at the very early stage of that. And then Microsoft is not the only [00:15:45] company. We're starting to see other companies that touch the enterprise starting to embed that as well.

So definitely. We see AI on the back-office side as an efficiency gain tool, and AI could also be incorporated, if incorporated correctly. It can [00:16:00] also improve the revenue gain as well. So, um, that is something that we are still watching and it, so probably still early to call, but I definitely can see, you know, AI will allow you to understand your customer better and then provide more personalized solutions.

And there's [00:16:15] a lot of intelligence that we didn't have before that we can have today using the tools. We're early. But we're already seeing it in some of the enterprise solutions.

Stacie Jacobsen: Lei. From your perspective, is there anything that you are overly concerned with or actually really [00:16:30] excited to continue to see develop?

Lei Qiu: I think in the long term, I do feel like I always say, you know, we've been facing this market and then literally every day we wake up, we hear the talk about inflation. And I really believe that, uh, [00:16:45] innovation and change, uh, technological innovation in particular has always been a deflationary factor that is, we can talk about fed policies all day, but that is something that basically is, um, a short-term remedy but not a [00:17:00] long-term solution.

And I do believe AI will provide a long-term solution for that. So that's something I'm very excited about. And from an investment universe, I do think. You know, regardless we are an inflection point in history in terms of compute [00:17:15] paradigm, in terms of how much we're going to use in parallel processing and then just the amount of compute intensity that we're going to need.

Uh, that is something I actually have huge investment implications and we can really profit from. So that is something, and regardless of which app [00:17:30] wins or who adopted, that is the part I know for sure that you know, people are going to use. More and more of their memory of the processing power of, uh, the network and, uh, in a fully digitized society and AI is going to take us [00:17:45] there in a much faster way.

And so that is part of the investments that I, in the investment universe that I'm really excited about. There's the hype, but then ultimately, which company will benefit from it is remains too early to be seen. And then two, I do think. [00:18:00] AI is not ai. You cannot have the training or inferencing without having the data.

And ultimately who owns the data, the data privacy and security. That is going to be a huge concern is the ownership of data and the [00:18:15] permission of use data. And I think that is something that, you know, will get more and more attention. That is something that, you know, I think it's not talked about as much today, but certainly is going to be a point of contention, if you will, in the future.

I [00:18:30] see potential regulatory hurdles. That's probably one area that I, I see that is something that's going to get a lot of attention.

Stacie Jacobsen: All right, Lei, I think that's a great place to wrap. Thank you so much for joining us today and for sharing all of the wisdom that you have.

Lei Qiu: Thank you. [00:18:45]

Stacie Jacobsen: Thanks to everyone for tuning in.

Join us again in two weeks when we'll talk about marital agreements. You won't want to miss it. Don't forget to subscribe to The Pulse by Bernstein wherever you get your podcast. To ensure you never miss a beat. I'm your host, Stacie Jacobson, wishing you a great [00:19:00] rest of the week.

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