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So what is Artificial Intelligence (AI)?

Its early days, but a key maxim of investment is not to invest in what one does not understand.

So let’s add to the discussion.

AI is a shorthand for LLMs ie Large Language Models. ChatGPT is an LLM. How do LLMs differ from computer software programs we have had for many years?

Firstly they have the ability to scan large amounts of data, then to observe patterns & attributes of that data, to have algorithms & databases to help interpret the patterns & attributes, then finally to predict outcomes based on the foregoing.

So Google acquired Google DeepMind, a company originally established by a UK chess master to help solve solutions for the Japanese game of Go. This developed into an LLM which uses AI to correctly predict the shapes, structures and behaviours of proteins. A large database of discovered and mapped proteins was entered into the database. The AI software now known as Alphafold was able to predict the shapes, structures and behaviour of unmapped proteins was a high degree of accuracy. The professors and LLM were awarded a Nobel prize for this work.

Google also have an LLM known as ‘co-scientist’. A team of scientists at the Imperial College in the UK spent 10 years solving the mystery of antibiotic resistance. They decided to test co-scientist on how long it would take to solve the solution. Answer:48 hours. They didn’t give the LLM the answer - rather the inputs and the problem.

In another example an early AI model only beat 10% of students sitting the California bar exam. The upgraded version more recently was at the 70-80th percentile.

There are other LLMs that will take a book of data, summarise it and produce a podcast.

So returning to ChatGPT, it is a general all purpose LLM that answers a broad range of questions, not always correctly. Deepseek was released by China on Trump’s inauguration. Coincidence! There are those who think Deepseek downloaded data etc from ChatGPT. Deepseek was originally configured as a student asking a teacher questions. Many of these are commonly asked questions, so the computing power required is less. There is also the suggestion that Deepseek by turning parts of its intelligence on and off, Deepseek can deliver powerful AI at a fraction of the computing power required by other LLMs. This may be a major innovation. Our brains switch rapidly depending on what areas are required to deal with the environment. So a better mousetrap?

On the hardware side, Nvidia captured the imagination of the markets. Its IP is strong but others are looking for alternate solutions for their LLMs that don’t necessarily require Nvidia chips.

How will Business use AI?

ChatGPT has major issues for businesses re data security. One cannot load customer/client data onto ChatGPT. So business is faced with upgrading Microsoft from an earlier version to Microsoft 365. Then buying co-pilot. Then perhaps having to buy new hardware to cope with increased demands eg if several personnel initiate a complex AI data process at the one time, do the servers grind to a halt.

That raises the requirement for investment in data centres and electrical generation.

And then who has access and authority over what data? And who will teach businesses how to use it? The Nvidia ceo stated that for every $1 spent on chips, $20 would be spent on software and software providers to learn how to use it.

So we are at the early stages of this journey, but its capability is both enabling and scary. At Burrell we are looking to learn along with others and to make some investments along the way in AI themes.

How to Invest?

There are listed companies at each stage of the AI journey. Goodman for data centres, but most are overseas. Cisco for chassis and switches etc in the data centres. Microsoft for software upgrades and co-pilot. Google for LLMs, but is its search business affected? Accenture for IT consulting. Nvidia for chips - but is it too expensive.

Several of these companies are included in exchange traded funds (ETFs) and managed funds, many now listed in Australia. For those wanting direct international exposure, we have access to independent research. BWET is the Burrell World Equities Trust available to all clients (min$10,000) and the BWET28 template portfolio is available to clients seeking direct international shares.

Is it all overpriced?

A number of AI stocks have had strong returns, whilst others to date are more muted.

Capital Economics expect the AI theme to be positive for calendar 2025.

So some exposure is worthy of consideration, particularly given earnings growth in the US is predicted higher than Australia this calendar year. Capital Economics also have a target for the US S&P500 index of 7000, as compared to around 6100 currently.

Happy Investing

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