Transcript
Speaker: Welcome to HSBC Global Viewpoint, the podcast series that brings together business leaders and industry experts to explore the latest global insights, trends, and opportunities.
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Speaker: Thanks for listening.
Speaker: And now onto today's show.
Speaker: The following podcast was recorded on the 18th of January 2024 by HSBC Global Research.
Speaker: All the disclosures and disclaimers associated with it must be viewed on the link attached to your media player.
Speaker: And don't forget that you can subscribe to this weekly podcast on Apple and Spotify, or wherever you get your podcasts, by searching for The Macro Brief.
Speaker: Hello and welcome to the Macrobrief.
Speaker: I'm your host, Piers Butler in London.
Speaker: Venture capital, or VC, has been an important source of funding for potentially transformative technologies and businesses for more than a quarter of a century.
Speaker: But what are VC investors focusing on today?
Speaker: From generative AI to gene therapy,
Speaker: and from cloud to clean tech.
Speaker: This week, we're taking a look at some of the sectors in the VC spotlight.
Speaker: I'm joined in the studio by Mark McDonald, head of data science and analytics.
Speaker: Mark, welcome back onto the podcast.
Speaker: Thanks for having me on again.
Speaker: So you've just published the second edition of Funding the Future.
Speaker: Firstly, remind us what this publication aims to do.
Speaker: Funding the Future is a publication in which we track data on venture capital investments and the rationale for doing this is kind of twofold.
Speaker: One is that the companies that are funded by venture capitalists, these are often companies that are inventing and deploying disruptive technologies.
Speaker: And so these companies often end up growing to be either big public companies themselves or competitors to big public companies.
Speaker: So that what's happening there is important from a disruptive tech space anyway.
Speaker: And I think also it's something where these companies that are being funded, the activities that they're doing can end up influencing the overall economy.
Speaker: A great example being OpenAI.
Speaker: It's a private company, it's received a lot of venture capital funding, so have many other generative AI companies.
Speaker: Generative AI has had a massive impact on public markets, so it's important for investors in the public markets too.
Speaker: So the more you know about what's going on in the VC world, the better you're equipped at highlighting what's going to happen in the public markets.
Speaker: And in fact, you've developed a tracking tool, is that right?
Speaker: Yes, we've got the HSBC VEN-T measure.
Speaker: This is really something which allows us to track the current level of venture capital investments relative to recent history.
Speaker: And the rationale for that is, if you look at the pattern of capital being deployed in VC investments, we saw a significant increase in 2020 and 2021.
Speaker: And then that's now had two years of sequential declines.
Speaker: It was lower in 2022 and 2023.
Speaker: And it's now back to levels that sort of typical for pre-COVID.
Speaker: And so one way to look at that would be to say, okay, this was an anomaly and we're now back to normal.
Speaker: But in reality, humans and financial markets don't work like that.
Speaker: People make decisions based on, you know, what's happening right now.
Speaker: And so companies that were receiving venture capital investments and VC investors themselves
Speaker: will have been making decisions in 2021 based on a continuation of that surge of easy money.
Speaker: And so the sequential declines over the last two years will have felt like a fairly significant crunch.
Speaker: And the Venti allows us to kind of track current levels relative to recent history.
Speaker: And so what we were seeing, say, maybe six months ago, was that level was very depressed.
Speaker: It was sort of trading at about 60%.
Speaker: What we're seeing now is that the Venti has gone back up.
Speaker: So it's still suggesting that current levels are low relative to recent history, a bit lower than 80%, but it's moving in the right direction.
Speaker: I think that is a cause for some optimism, particularly because VC returns are often related to the level of interest rates.
Speaker: And so the lower rate environment is likely to help there too.
Speaker: And what, in this second edition, were the sort of key takeaways?
Speaker: Well, as always, there are some areas that are receiving a lot of excitement and a lot of investor interest, you know, these kind of emerging spaces.
Speaker: One very notable one was AI generally, and specifically generative AI.
Speaker: This has been a huge focus on
Speaker: for most investors at the moment.
Speaker: Two other areas where we're seeing a lot of excitement are in the sort of biopharma space.
Speaker: There's a lot of biotech investments and also sustainability, particularly in Asia.
Speaker: We're seeing a lot of investments into sort of clean tech.
Speaker: So talking about Asia, some of your colleagues in Asia have also written about AI and their implications.
Speaker: Can you just maybe give us an overall highlight on that?
Speaker: Yes, I think the generative AI tools, they are general purpose technology.
Speaker: And there is the possibility for these tools to be used for wide scale productivity improvements across the economy.
Speaker: So at some point, analysts in all sectors will probably have to start considering the impact of AI on the companies that they cover.
Speaker: But at the moment, the area where it's being most cleanly manifested is in tech companies.
Speaker: So our analysts that cover individual tech companies have been writing about this factor quite significantly, particularly in Asia.
Speaker: Yes, I would highlight Charlene Liu, who's published on Generative AI in China in particular.
Speaker: And coming back to your area, how are you applying AI and other tools in your work?
Speaker: So we've been using machine learning and AI tools for many years now.
Speaker: I think the area that's most close to the current area of AI excitement is our work on natural language processing.
Speaker: So for many years now we've been performing natural language processing analysis of earnings call transcripts.
Speaker: We have our own proprietary sentiment model that we've trained by us and other analysts at HSBC teaching a machine learning model how to interpret sentences that
Speaker: company management say on an earnings call and decide are they positive, are they negative, are they neutral, or are they just irrelevant.
Speaker: And it's from the very granular sentence by sentence data that this machine learning model produces that we're able to track sentiment of company management towards a whole host of themes.
Speaker: In your Data Matters series, I was looking at it ahead of the podcast, in the November one, you have this fantastic picture of what are the key words in U.S. earnings transcripts.
Speaker: And obviously, not surprisingly, AI features large.
Speaker: That's probably likely to sort of continue being the most sort of mentioned word.
Speaker: Can you give us a sense of the pace of development?
Speaker: The sort of things I hear and read is that it's been very rapid in the course of 2023, but it almost seems to be accelerating even more in 2024.
Speaker: Yes, I mean, it's an interesting one because the pace of change of AI and particularly generative AI, things have been moving very quickly.
Speaker: There's huge research interest there.
Speaker: and lots of funding moving into the space.
Speaker: Part of the pace of change, I would argue, is a little bit illusory in that for people who are not AI specialists or not involved in performing machine learning, if you go back before ChatGPT, probably most people didn't really know that generative AI was a thing.
Speaker: It wasn't a topic that people discussed.
Speaker: And so over quite a short period of time, you went from most people having...
Speaker: virtually no knowledge of and no access to generative AI to suddenly being able to have easy access to the most cutting-edge models on the planet.
Speaker: And that gives the perception of an unbelievable pace of change, although it's really a change in user experience.
Speaker: I think one thing that is leading to very rapid change is the fact that many of these models have moved recently from being what are basically scientific research problems into what are now engineering problems.
Speaker: And so you have the ability for people to really start to daisy chain different machine learning models together to produce quite incredible looking products.
Speaker: A great example would be recently on LinkedIn, I posted a video of myself appearing to speak fluent Mandarin.
Speaker: Don't you?
Speaker: Which I do not.
Speaker: And this was an AI tool put together by a startup where you upload a video of yourself speaking, in my case, in English, and it produces a video of you appearing to speak many other languages.
Speaker: And
Speaker: It looks like me, it sounds like me if I were indeed able to speak that language, and my lips are moving in sync with the movement.
Speaker: Now each step of that process from turning one video into another is something that is now a fairly well engineered process.
Speaker: So there's the speech to text part where it has to work out which English words I'm using,
Speaker: There's the language translation part where it needs to work out how to convert that into Chinese.
Speaker: And then there's the generative AI component where it takes video of me and the new text and produces the video where I appear to be speaking it.
Speaker: And each of those individually is not that remarkable.
Speaker: But when they're stitched together, it produces this really, like, staggeringly impressive product.
Speaker: And I think increasingly we're going to see people finding ways of using these tools to produce products that do things that, until recently, would have been science fiction.
Speaker: Are you worried or excited about the prospect of having a digital twin?
Speaker: I mean, I think these things are very exciting.
Speaker: Often people are scared of new technology because you can see the things that are likely to be taken away by technology.
Speaker: It will do things that you used to do.
Speaker: But also it will open up the possibility of doing things that were not possible before.
Speaker: And hopefully it will free up some time to spend on higher value activities that AI can't do yet.
Speaker: Yeah, I guess if you can rely on the digital twin, it'll be able to multiply your marketing capability.
Speaker: So the productivity implications are quite significant.
Speaker: I would think so, yes.
Speaker: I think there are many areas where AI can lead to quite significant productivity improvements.
Speaker: So by the end of 2024, we're likely to see some pretty major changes?
Speaker: Yeah, I would think so.
Speaker: I mean, generally when disruptive technologies come in, they tend to follow an S-curve where it's steep acceleration at the beginning and then at some point it tails off.
Speaker: But I think with this technology, we're still quite early in the acceleration phase.
Speaker: You know, this technology is so new for so many people that it's taking time for people to identify the most productive ways of using it.
Speaker: And I think we're still quite early in that process.
Speaker: Well, on that note, Mark, I'm sure we will be having you back on the podcast to talk about some of these developments.
Speaker: But for now, thank you very much for joining us.
Speaker: Thanks for having me.
Speaker: I look forward to you returning.
Speaker: Here's a roundup of some of the other reports published by Global Research over the past week.
Speaker: The latest data show that UK inflation ticked up unexpectedly from 3.9 to 4% in December.
Speaker: Our economics team say that some strength came via volatile components, ranging from computer games to theatre tickets.
Speaker: These numbers suggest that inflation stickiness has not been entirely banished.
Speaker: And they say this supports their view that UK rate cuts will not happen until the second half of the year.
Speaker: Our LATAM economists and strategists have just published a new multi-asset outlook.
Speaker: They see a two-speed region in 2024, with Brazil and Mexico ahead of the pack.
Speaker: The inflation picture has improved markedly across LATAM, central bank rate cuts will continue throughout the year, and there will be less political noise.
Speaker: The report assesses the implication of the currency, equity and rates markets.
Speaker: And it's the final call for our live insights.
Speaker: where I'll be putting your questions to our chief global economist, Janet Henry.
Speaker: The event is taking place on 19th of January at 3 p.m.
Speaker: UK time.
Speaker: For details on how to register and more on the reports mentioned in today's podcast, please email askresearch at hsbc.com.
Speaker: So that's it for this edition of The Macro Brief.
Speaker: Thanks very much for listening.
Speaker: We'll be back next week.
Speaker: Thank you for joining us at HSBC Global Viewpoint.
Speaker: We hope you enjoyed the discussion.
Speaker: Make sure you're subscribed to stay up to date with new episodes.
