Polar Capital Technology: best and worst AI stocks

Thanks for having me.

Well, it's always nice to be able to report on a very strong period of performance. And it has been, you know, the technology market's been strong and the trust has been stronger still. So I think, you know, over those two years, I think the trust NAV is up around 78%, and our index I think is more like 66%. But, you know, remarkable returns really over any given, you know, two-year time frame, reflecting really a strong backdrop for technology, but specifically for AI.

That's a good question, and I think, you know, what I probably should have said earlier on the return part of the question was, you know, we're really delighted with the returns we've delivered, not just because we've, you know, got the AI theme correct within the portfolios, but actually it's been a really difficult market for many growth investors. It's been a very narrow market, obviously in our world Mag 7 has dominated. You know, I think, you know, small caps have meaningfully underperformed, sort of only up 20% over that time frame in the US. So not been an easy market. So to your point, what's gone right, what's changed? And the answer really is that, you know, AI has really continued to make very significant progress, and it's done that on a number of different vectors. You know, the most important one of all is that models have got better. And so we've seen, you know, again if you go back to November 22, so outside of the two-year window, but really what started this was obviously ChatGPT. At that point you had this incredible quarter from Nvidia in May 2023 where the company just blew away numbers, but really the guidance they gave was record guidance. No one had ever seen an upside surprise like that, and that really marked a different market, and that's sort of mostly captured in those two-year things. So what happened? Yeah, the models got better. ChatGPT became GPT-4. We've had competition from lots of other companies at the frontier of AI. We've seen capex numbers, you know, the ultimate barometer really on how AI is doing and how do people feel that, you know, these hyperscalers, how do they feel about the progress that AI is likely to make beyond what we see today? And the answer is they, you know, it's in the spending numbers, and this year the industry is supposed to spend more than $370 billion on AI infrastructure, and those numbers are wildly different to where they would have stood two years ago. So, you know, we've got AI progress, more users, you know, we're up to 800 million weekly users of OpenAI, like all the vectors that would chart the progress of AI have been steeply up to the right, which has really created a backdrop which has been fabulous for AI-related assets, but actually pretty tricky if you're not on the right side of that trade.

When we first saw ChatGPT, we were pretty excited by it. I think there was quite a lot of skepticism in the market, and not just in the market but in the, you know, the wider world where, you know, in the end AI just makes stuff up, it's probabilistic, and, you know, some people described it as a Victorian parlor trick, and we felt very differently about it. And, you know, again just for background, you know, we launched our own dedicated AI fund nearly eight years ago, it was called an Automation and AI Fund when we first launched it, but I suppose you could argue we've had a head start, we've been looking at AI for a very long time. We were super excited about the transformer models that really are the underpinnings of ChatGPT, and Gemini and all of the leading models that you see today are built on transformers, and we felt that the trajectory of AI was going to be profoundly changed. We did some small stuff between the launch of ChatGPT and that Nvidia quarter that I referenced, but really after that we pivoted very hard. And, you know, the trust I've been running for a long time now, we've sort of built it over time as being a very diversified six to eight core themes, and, you know, trying to deliver more growth than the index, and actually that changed after that Nvidia quarter. We feel that AI is the next general purpose technology. We've felt that now for quite a while. Market's coming around to our view. General purpose technologies changed the world. Again, we may talk about that more as we go on, but how can you have a portfolio that doesn't want to capture moments like this? These are highly unusual moments of discontinuous technology change. And so we have meaningfully shifted the portfolio, really doing lots of work on the new AI infrastructure stack. One of the things I should probably mention is that, you know, we've just come off the back of a wonderful period for cloud. Cloud was about the commoditization, the homogenization of compute. No one cares what the server is, the PC that you use, because in the end it's all about the cloud delivery. That's not the world that we're in today, where hyperscalers and others are building performant compute that require the fastest chips, the densest clusters, the lowest latency. We're building a very different compute infrastructure stack than really almost anyone has seen in the market today. And so we've pivoted very hard towards that. We could talk about some individual names if you're interested. On the other side of the equation, we've been meaningfully reducing exposure really to the old tech. And for us that old tech really looks like software, which have been the most incredible conduits for supernormal profits for a very extended period of time. Most people, myself included, have been brought up on, you know, the primacy of software businesses, that those businesses feel at risk. And again, we can talk about that if you're interested. We've been reducing software, we've been reducing anything really that doesn't have AI exposure in order to give us a, you know, pretty good chance of capturing the upside of this new cycle.