As artificial intelligence and large-scale language models continue to gain attention, with technology companies investing heavily in the technology, Luke Barrs, Global Head of Client Portfolios at Goldman Sachs Asset Management, joins Catalysts to discuss the outlook for this space.
Bars emphasized the huge impact of AI, calling it “transformational” and constantly changing the productivity and dynamics of various industries. He noted that some technology companies have committed significant resources to AI development, investing “every penny they can find” to stay competitive and “stay a step ahead of the pack.” But as more companies roll out AI capabilities and cost-effective solutions, Bars expects competition to intensify and market dynamics to change.
“I think the short answer is that we're still in the very early stages of this transformation, especially in the context of the stock market,” Barrs told Yahoo Finance.
To learn more about expert insights and the latest market trends, click here to watch this full episode of Catalysts.
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Video Transcript
Video continues to drive the market.
Rally companies are looking to jump on A. I train by reallocating capital to expenditures.
Not all are created equal.
Yahoo Finance spoke with Alex Karp.
He is P CEO talking about the challenges business owners face when it comes to spending.
Here's what he said:
I'm sure many of you watching this are familiar with the story that large language models have huge high cycles, and when you try to use them in the enterprise, you find that it's like self-flagellation, and you incur costs for no gain.
So how can investors evaluate I-spending and avoid slipping into that self-critical tirade that Alex Karp just talked about?
For more information on this, see Lukebar.
He is global head of fundamental equity portfolio management at Goldman Sachs Asset Management.
Luke, I'm glad you're here.
I just heard that soundbite.
But from your perspective, what's the right framework that investors should be using to look at capital expenditures and what really translates to growth on the research and development side as opposed to just things that get talked about on an earnings call?
Well, first of all, thank you, Shauna, for inviting me. First of all, I think we need to reflect on the fact that the “I” is something that changes.
It's changing the way we operate.
And the dynamics of some of the technology hardware businesses that we as investors value and evaluate are also changing rapidly.
Now, what I'm saying is, if you think about the timing and the sequence, we're at a point where Hyperscalar is investing all the money we can find to stay as far ahead of others as possible on the LLM development site.
So if you're a semiconductor company working to expand production capacity for servers or hypercars, you're in a very good position right now.
Going forward, I think we should expect competition.
There will likely be some changes in the industry trends.
Things are actually going to change a little bit as companies with capabilities in that space enter the market and also as we move from best-in-class, cutting-edge nanocapacitor semiconductors to something a little more cost-effective in the ASIC space.
But for now, we remain very bullish on the sector.
We have to be cautious about valuation, but we think there are a lot of opportunities.
Luke, you recently had the opportunity to be part of a small group of investors who were invited to spend a day with Microsoft's senior management team.
I'm curious what you've taken away from these conversations in terms of where we are in the AI cycle and how many opportunities lie ahead.
Yes. And it's actually interesting that our core investment team, both globally and on the U.S. side, met with about 20 companies this week on the West Coast, both public and private, as well as on the venture capital side.
So I think we have real-time information about what's going on in that space, and the short answer is, I think we're still in the very early stages of this transformation, especially in the public markets context.
We are still on the cutting edge of how we can leverage LLM and big data analytics tools in that I-framework and how we can apply that to real-world solutions.
So, I think right now we're seeing a clear cycle of accelerating revenues in foundational technologies.
In the medium to long term, there are no signs that this will have an impact on the software business.
And with the expected long-term adoption of AI technologies in productivity solutions, I think this will become even more favorable for software companies, especially the larger players at the forefront of this development.
