Intelligence Inside

I think people tend to overestimate what they [robots] can do over the short term – and they probably underestimate what they can do over the long term.

Robots have been dramatically expanding the scope of physical tasks performed and have also started to do more and more cognitive ones. The pace of advancements is sustainable – and it will not be linear growth, it will be exponential.

There’s a network effect, too. So, if you have one AI system learning a new task, it can be shared with and benefit all the other AI systems or robots through the cloud and connectivity. What one robot can achieve in eight hours can suddenly be performed in one hour by eight different robots.

I think the real question is what humans will do with all these devices. And it will very much depend on what we do as humans, collectively. Robots are very good at certain things; humans are very good at other things.

For me, the future will not be about ‘man versus the machine’ – rather, it will be defined by ‘man with a machine versus man without a machine’.

Well, the first thing is that it’s an appealing and accessible subject, which is part of our collective unconscious – everyone’s watched sci-fi movies or read books about robots taking over the world. So there’s plenty of curiosity about the theme and what it is all about. Second, you have large data sets available thanks to ever-increasing connected devices, and the ‘Moore’s Law-powered’ necessary computing power to deal with these data sets. In terms of AI techniques, especially neural network systems, you can uncover the insights based on the data. There’s also the fact that costs are coming down quite significantly for these technologies. And when you have this combination of technological advancements and costs coming down, you are at an inflection point – especially when this relates to a general-purpose technology that’s applicable to a number of different industries and sectors. In terms of how it has evolved, you’ve seen more technologies being embedded into these robotic devices, be they sensors, machine vision systems, natural language understanding or generation, and contextual awareness systems, to name but a few. So, from basic mechatronic devices used for performing the very repetitive tasks on mass- manufacturing floors – what we call the four Ds: dull, demanding, dirty and dangerous – robots have suddenly become smaller, smarter, safer and cheaper. Moreover, they have made leaps forward in terms of versatility, adaptability, flexibility, user-friendliness and mobility, allowing them to become ubiquitous.

I’m co-manager of the AI & Robotics strategy with Nolan Hoffmeyer. We cover it end-to-end, from the theme drivers and boundaries to the identification of the investible universe, as well as to the bottom-up company analysis and stock picking, position sizing, portfolio activity and monitoring.

We have an active management investment style and aim to run a concentrated portfolio expressing our strongest convictions. At the same time we diversify through exposure to different drivers and different verticals of the economy. As we manage the strategy in an unconstrained manner, we select the best opportunities within the theme, irrespective of any geographic, sector or market capitalisation considerations.

That said, given our focus and expertise built over many years on the theme, we believe our edge lies in the small and midcap space, where we can uncover attractive long-term compounders to generate alpha, which is typically under-researched and perhaps not as well understood by the broader market.

One very attractive area is healthcare. It combines two compelling characteristics: an already large addressable market of about $80 billion a year, and an expected compounded annual growth rate of 35% over the next five years. In this segment, you have surgical robots, for instance, used in an expanding set of operations. Some companies active in this space are appealing as, beyond the sale of the robot, most of their revenues are recurring, and therefore visible, as they are based on maintenance and the regular sale of instruments. However, it is in the area of ‘intelligent diagnosis’ that a significant potential lies. These companies, based on the large data sets they have now available, can train algorithms on millions of X-rays, MRIs or scans to come up with the right diagnosis of a patient disease, much earlier on and in a much more accurate way than a human doctor or radiotherapist could. So that's where we see a lot of growth and a significant and clearly addressable market. Another area is driverless vehicles. ‘Don’t mine for gold when you can sell shovels instead’ is the maxim we've used to approach this segment, meaning we don't want to bet on which car manufacturer is going to be first to come up with a driverless car. Rather, we're looking for the technologies and the companies providing them that will be absolutely necessary for any autonomous vehicle: cameras, radars, lidars, sonars and so on. Essentially, everything that is necessary for these cars to navigate safely on our roads.

We decided to combine the two because it is obvious to us that there has been a clear convergence between the technology and the hardware. It's increasingly difficult to make a distinction between AI and robotic devices. The lines are blurring.

You don't have a company that is developing AI algorithms and selling them to external competitors. It's something that is done by the companies themselves, with the AI usually embedded in their products.

And from the perspective of managing the strategy, it is also very beneficial. Although robots and automated processes have been making inroads in many new applications and business fields, most of the addressable market is still in the industrial automation space, which is very sensitive to economic cycles, industrial production and capex cycles. And most of its growth is currently driven by China and the smartphone industry.

Therefore, by including AI in the overall theme we’re adding different drivers, as well as exposure to other verticals and business models. The AI companies have a different visibility in terms of revenue generation, cash regeneration and differences in cyclicality as well.

So, as a manager of a portfolio, that enables you to be more or less defensive or aggressive, depending on the scenario, and to be more flexible and agile to navigate the market cycle, to deliver the performance and protect performance.

My experience with wholesale investors in thematic equity is that they really understand what it is that they are investing in, and thematics also gives them a sense of purpose to their investment. When they invest in water, for example, it’s not only a financial investment, it's also something that contributes to the greater good of society. Over the past few years, we’ve also seen institutional investors increasingly interested in investing in global equites using the thematic lens. And my feeling on this is that they have acknowledged that when they were buying a US equity fund, for example, it was very difficult to understand exactly what they were buying, and what end market risk they were gaining exposure to. Was it US companies exposed to the US market or US listed companies offering exposure and associated risks to many more regions? End markets and revenue generation become so diversified that it is unclear what exactly one invests in using a regional approach. The same applies with a sector fund, for instance, as these classifications are fairly arbitrary. Not so long ago, Alphabet/ Google was in the consumer discretionary Category, but it could just as easily have been categorised as an IT, industrial or communication services company. So institutional investors have started to realise, if we're not really grasping the reality of our investments using the traditional classifications, then maybe using the value chain of a theme helps us to have a better understanding of the drivers of this theme and what we're investing in. These used to be very niche investments for them, even five years ago. We’d meet them and they’d say they were convinced by thematic investing but couldn’t figure out where to position us in terms of portfolio allocation. They started to make satellite allocations to thematics and, for many, this has now shifted to become the core part of their portfolio. For some, it has become central in their global equity allocation.

Insurance companies are clearly looking for secular growth and compounders that can provide attractive returns over the long term. They also have this willingness to protect the downside.

And in this respect, thematics provides some safety – it gives them exposure to global equities supported by secular growth tailwinds. From an asset liabilitymanagement perspective, the long-term horizon of our investments matches nicely with that of their liabilities. Insurers are also quite familiar with a specific form of duration risk that thematic investing looks to capture. The compounders we invest in tend to sustain superior growth and profitability longer than the market gives them credit for.

The market tends to price a reversal to the mean too rapidly, presuming market forces will play out, ignoring the secular forces supporting their operations. It therefore misprices these stocks, due to this shorter investment horizon. With our unique standpoint, we try to capture this duration premium.

This interview took place in June 2019