[Editor’s Note: Do not read the following ideas as theme or stock recommendations. Do further research of your own or talk to an adviser before acting on ideas in this article].
The big disruptive issues facing investors in the next year are likely to be found in five key areas:
For perspective, the major disruptive issues of the past 20 years have been digital disruption, first around data (which includes movies, banking, media and advertising) and then the application of data tools to the physical world, enabling physical fulfilment (e.g., browse and pay on-line, track delivery of goods).
The one that is big right now is decarbonisation. Pioneered by Elon Musk through the car and battery company Tesla, Musk wasn't the first person to build an electric car (they were commercialised by the company the O. P. Fritchle Garage Company, among others, in 1905) but the first to commercialise at scale.
As large as the global car industry is (it is estimated to be worth more than US$2 trillion with the inclusion of Tesla), it is dwarfed by the disruption that it implies. Because electric cars don't need fossil fuel for power, they may spell the end of the practice of burning things for heat and transport.
No matter what commitments and actions were agreed at the recently concluded COP26 in Glasgow, energy companies globally are racing to develop alternative clean sources of power.
Wind/solar/hydro (which are the largest share of renewables) with some biofuel and others, accounted for 23% of global electricity generation in 2019, according to the peak body, the International Energy Agency.
But of course, whatever source works best, the central issue of renewables power at scale is how to store it for use when the sun stops shining and wind stops blowing.
Hydroelectricity is one answer: use the solar/wind power to pump water up into a dam, and then release it to spin the turbines for instant juice. This is effectively a water battery. Bio-fuels are also a real storage solution, but it is not that clean - Prince Charles's 50-year-old Aston Martin runs on wine and cheese, he says. There are various battery storage technologies, with lithium-ion the most important by far.
This brings us to hydrogen. The technology is not new, but it is clean. Burning hydrogen in a combustion engine or using it in a fuel cell that powers an electric motor generates power with the only by-product being water. If the hydrogen is generated by electrolysing water using sustainable energy sources such as wind and solar - "green" hydrogen - there is virtually no carbon let loose in the process. In November, the CEO of Airbus has touted hydrogen as the future of fuel for the global aircraft maker.
AI is here and Loftus Peak invests in many elements of the artificial intelligence thematic.
There are already a huge number of AI interactions in the daily activity of millions of people. Google searches are running at around 67,000 per second, and the company fields these queries using AI without human intervention on the basis of probability-weighted answers. Ditto for photo-tagging in Facebook, route calculation for Uber and so on.
While the means by which this is done involves very complex maths, the process can be understood at a high level, and because autonomous cars are a familiar concept, it is worth considering as an example.
For example, a front-facing video camera on a car “sees” a shape 200 metres ahead. The AI in-car unit contains the smarts, i.e., graphics processor units (GPUs) and central processor units (CPUs) among others. The car also “knows” a number of things, such as the speed at which it is travelling, its location and direction and so on.
As it processes multiple images, it is able to tell if the target shape is moving, and even the direction and speed. It fuses all these data together. None of the above is really AI – it’s just a data-gathering exercise, though done at lightning speed, and constantly.
Now, the artificial intelligence part. All these data are fed to the AI image and data bank, which determines what the shape is, based on probability. Perhaps if it is small and moving slowly, it is a child, or if it is large, livestock.
If the speed at which it moves is high, it could be a pushbike, or motor bike – or a car. If there are two headlights, could it be two motorbikes travelling abreast? As each millisecond passes, the AI re-evaluates the possibilities and discards them one by one – and then does so again, and again.
This is a convolutional neural network in action, and it will generate a probability-weighted set of outcomes which it refines, thousands of times. The aim is to eliminate all the low-probability things the moving shape isn’t in order to arrive at the one that it (most likely) is.
Only then does the AI take steps to deal with the shape (which could involve flagging to the driver a course of action – ie stopping, swerving, or ignoring it (say if it was a large plastic bag blowing across the highway).
The cars in the above example are connected devices - just one use-case in the internet of things. Cars on a collision course may have knowledge of one another and take intervention measures, such as slowing down or changing course. This can happen with or without driver action, because the cars are connected through a network, separate from the drivers’ networks.
Use cases for connected “things” are virtually limitless, from sports teams seeking granular detail on the performance of their athletes as they move, to remote weather stations, to vital sign tracking for older folk requiring careful monitoring, or port operations for moving containers. ARM, the company under offer from Nvidia, has credibly forecast that the number of connected devices will grow from 150 billion currently to over 1 trillion by 2035.
US agricultural equipment manufacturer John Deere is fitting technology to its farm machinery to capture soil quality, moisture, paddock topography and other data. The data capture is down to the individual seed, which is mapped as it is planted, to produce granular insight enabling targeted application of fertilisers, water and so on to maximise yields.
This has come to be known as precision agriculture and enables literally millions of seeds to be tracked from plant to harvest.
The data produced by all this disruption – in genetics, agriculture, AI and the internet of things - is a part of the disruption itself, as well as the mechanism by which the new business models work.
To illustrate, it was not immediately understood that 4G technology was a company maker for Netflix, which could then offer movies over a cellular phone, and Uber, which was able to provide granular data on the transportation services it offered.
We do not yet understand all the businesses which will come out of a ubiquitous 5G network, but we do know that the speeds and bandwidth offered will mean that surgeons will increasingly be able to operate on patients remotely (as regional hospitals upgrade broadband networks) and power grids will better understand peak loads and how to deal with them.
Loftus Peak has invested in Qualcomm (a US semiconductor company) to take advantage of this, and the company has been a strong performer for our investors. The company’s research and development has pushed the telecommunications industry towards a 5G standard, which will benefit consumers through increased speeds and bandwidth with lower latency.
We expect 2022 be a strong growth year for 5G as phones and applications proliferate. We do not see a 5G world where Qualcomm isn’t a key driver and beneficiary – it is the single most important company for the delivery of 5g services in the world, in Loftus Peak’s opinion.
Last, but certainly not least, is the revolution currently taking place in the human genome. CRISPR (Clustered Regularly Interspersed Short Palindromic Repeats) technology allows precise editing of the 3 billion genetic base pairs every human has. CRISPR has taken off during the past half-decade, after scientists discovered that a known function of certain bacteria could be harnessed to cut out and, in some cases, replace individual genes.
The CRISPR system is an adaptation of the natural gene editing method used by bacteria to protect against viruses. Bacteria cuts snippets of DNA from a virus to save, and “remember” for future attacks, while also disabling the virus.
It works by cutting out part of a strand of DNA and then allowing the cell to stitch that strand back together, either without the removed segment or with a new gene in its place.
There is ample evidence that this technology can cure some diseases – for example, a small number of patients suffering from sickle cell anaemia have been successfully treated, with the damaged genetic material substituted for genes which produce foetal haemoglobin.