Artificial Intelligence Investment Opportunities

Posted on
This is an AI-generated image depicting a man conducting research to explore investment opportunities in the AI industry

New technologies have the potential to bring about revolutionary changes, such as the emergence of the internet and smartphones, which created a group of companies with market capitalizations exceeding billions or even trillions of dollars. In recent months, the most talked-about topic has undoubtedly been “Generative Artificial Intelligence” (GAI), including OpenAI’s ChatGPT, Google’s Bard, and Baidu’s Ernie, among others. Readers who have tried GAI can attest to its capabilities, which have surpassed expectations, and its impact on various industries is becoming apparent.

In early May this year, the stock price of the online learning platform Chegg, targeted at university students, plummeted almost overnight. The management attributed this decline to the significant increase in students’ interest in using ChatGPT since March, raising concerns about its potential impact on the company’s future growth prospects.

The GAI industry is still in its early stages, making it challenging for investors to accurately grasp investment opportunities. However, two crucial questions come to mind: where does the competitive threshold lie in the GAI field, and which companies currently stand to benefit from GAI?

The GAI industry can be divided into three main parts: the middle, upstream, and downstream. The middle segment consists of GAI neural network model owners, who are responsible for building and training models, such as the three GAI companies mentioned above. The upstream segment consists of infrastructure providers, including hardware graphics processing unit (GPU) suppliers and cloud platform companies. Cloud platform companies purchase GPUs and use them to create systems for neural network model owners. Lastly, the downstream segment includes companies that cater to end customers. They obtain data from model owners and use it to create software and apps that serve users, such as GitHub CoPilot, which assists programmers in writing code.

While many people believe that intellectual property rights may be the most critical competitive threshold, there are currently numerous open-source “large language models” available for use. Additionally, many AI experts request permission from employers to publish research reports in professional journals, fostering a strong atmosphere of mutual learning. In fact, even the core structure of ChatGPT is based on Google’s Transformer model, first introduced in 2017. The “T” in ChatGPT stands for Transformer.

Industry insiders point out that the most crucial competitive thresholds are data quality and computing power, both of which essentially come down to financial resources. Although there is an abundance of free data on the internet, it requires significant investment to clean and prepare the data for use. If GAI is trained using biased data, it may generate a GAI imbued with discrimination and hatred.

As for computing thresholds, Google has stated that training Bard using only one GPU would take approximately 355 years. The price of a project-grade GPU is around 10,000 USD, which implies that the hardware investment alone would be astronomical if one wants to shorten the training time to a reasonable level. Industry insiders estimate that training a large-scale language model can cost up to hundreds of millions of USD. Moreover, training cannot be accomplished in a single step; it requires constant experimentation and failure. How many companies can afford such financial resources to successfully train GAI?

Not only are hardware investments and training costs expensive, but the operational costs of running GAI are also much higher compared to running search engines. Investment banks have calculated that the cost of each GAI response is ten times higher than that of a regular search. GAI model owners are still in the exploratory stage of how to create profitable business models using GAI. In the long run, if companies holding GAI models can eventually transform GAI into a platform similar to Microsoft’s Windows or Apple’s iOS, allowing different software to run on it, generating economies of scale and locking in customers, it would create a difficult-to-exit business model and greatly expand development opportunities.

As for client-side software, since the industry is still young, it seems that no business models with competitive advantages have emerged yet. Apps that use AI to help students with tutoring or assist programmers in coding, for example, currently lack the ability to retain customers in the long term.

In summary, the GAI industry is still a money-burning industry, and large companies have a competitive advantage due to their financial resources. In the short term, upstream companies seem to have more investment opportunities: a significant portion of the expenses for training GAI will be spent on purchasing services from cloud companies, and since GAI requires GPUs for operation, cloud service companies and GPU manufacturers will benefit from this.

Disclaimer

This document is based on management forecasts and reflects prevailing conditions and our views as of this date, all of which are accordingly subject to change. In preparing this document, we have relied upon and assumed without independent verification, the accuracy and completeness of all information available from public sources. All opinions or estimates contained in this document are entirely Zeal Asset Management Limited’s judgment as of the date of this document and are subject to change without notice.

Investments involve risks. Past performance is not indicative of future performance. You may lose part or all of your investment. You should not make an investment decision solely based on this information. Each Fund may have different underlying investments and be exposed to a number of different risk, prior to investing, please read the offering documents of the respective funds for details, including risk factors. If you have any queries, please contact your financial advisor and seek professional advice. This material is issued by Zeal Asset Management Limited and has not been reviewed by the Securities and Futures Commission in Hong Kong.

There can be no assurance that any estimates of future performance of any industry, security or security class discussed in this presentation can be achieved. The portfolio may or may not have current investments in the industry, security or security class discussed. Any reference or inference to a specific industry or company listed herein does not constitute a recommendation to buy, sell, or hold securities of such industry or company. Please be advised that any estimates of future performance of any industry, security or security class discussed are subject to change at any time and are current as of the date of this presentation only. Targets are objectives only and should not be construed as providing any assurance or guarantee as to the results that may be realized in the future from investments in any industry, asset or asset class described herein.

In respect of any discrepancy between the English and Chinese version, the English version shall prevail.

Investing Beyond the Short-term: The Changing Landscape of Inflation

Posted on

Most investors only focus on short-term factors and ignore the importance of long-term trends. However, if one understands long-term economic changes, the effectiveness of stock selection and asset allocation may double.

For example, in the 1980s, the two most important structural changes were that former Federal Reserve Chairman Volcker raised interest rates significantly to 18% and brought emerging market productivity into the global market. These led to a decrease in inflation, a long-term decline in interest rates, and soaring asset prices. If investors had been steadfast in holding long-term bonds, stocks, and real estate since the mid-1980s, they would have easily achieved good returns.

The past is gone, what about the future? Investors may need to be prepared mentally: the era of low inflation has passed. While a return to the extremely high inflation rates of the late 1970s is unlikely, it is also unlikely that inflation will remain at the low level of around 2%. This is due to three main reasons.

First, the global age dependency ratio has reached a turning point. This ratio has been declining for the past half century or so, indicating that the population of dependents (those under 15 and over 65) is decreasing compared to the working-age population. Dependents represent the demand side of the economy, while working-age people represent the supply side. When the supply of goods and services increases while the demand for them decreases, it becomes difficult for prices to rise. This partly explains why inflation has been relatively low over the past 30 years.

According to the United Nations World Population Prospects study, the dependency ratio stopped falling about 10 years ago and entered a stable period. And it is projected that from 2027 onwards, the world population dependency ratio will rise. High-income countries and China have already seen an upward trend of this ratio since the global financial crisis in 2008.

At the global trade level, companies can still migrate their supply chains from China to Southeast Asian countries for cheaper labors and lands, but it can be foreseen that controlling costs will become increasingly difficult in the future. The shortage of manpower has put pressure on costs in the service industry in Western countries. In the past few years, Western countries have continuously postponed retirement age, not only because of insufficient pensions, but also because of manpower shortages.

Second, the costs associated with environmental protection will continue to rise. For example, China plans to achieve peak carbon dioxide emissions by 2030 and carbon neutralization by 2060. Either installing emission reduction equipment or purchasing carbon emission rights in the market will increase corporate costs, which will eventually be reflected in prices.

Third, the political differences between China and the West will intensify, leading to deglobalization and increasing production costs. The benefit of globalization is that each country can maximize its strengths, be responsible for producing its lowest-cost products, and then sell them to other countries through trade. This process naturally helps to suppress inflation. In the past few years, the trade war between China and the United States has intensified, and the Covid-19 pandemic has also exacerbated the situation. Therefore, the trend of deglobalization will continue, which will push up production costs.

Investors need to consider how the above assumptions would affect global investment markets, including China. Over the past few decades, many people have complained that while the economy is strong, only the top 1% of people benefit, and most people’s actual wages have not changed much. However, if labor shortages worsen, employees’ bargaining power will also improve, which means that income distribution within companies will gradually shift from shareholders to employees, and profit growth may be slower than economic growth.

So what industries may benefit in the new era of relatively high inflation? When the labor force decreases relative to the dependent population, companies may need to invest more in equipment to remain competitive, which should benefit equipment manufacturers. Inflation and rising interest rates are typically advantageous for banks.

However, artificial intelligence is developing rapidly, and if it can replace part of the jobs, the problem of rising dependency ratios may be delayed, which may elevate the inflation pressure.

Disclaimer

This document is based on management forecasts and reflects prevailing conditions and our views as of this date, all of which are accordingly subject to change. In preparing this document, we have relied upon and assumed without independent verification, the accuracy and completeness of all information available from public sources. All opinions or estimates contained in this document are entirely Zeal Asset Management Limited’s judgment as of the date of this document and are subject to change without notice.

Investments involve risks. Past performance is not indicative of future performance. You may lose part or all of your investment. You should not make an investment decision solely based on this information. Each Fund may have different underlying investments and be exposed to a number of different risk, prior to investing, please read the offering documents of the respective funds for details, including risk factors. If you have any queries, please contact your financial advisor and seek professional advice. This material is issued by Zeal Asset Management Limited and has not been reviewed by the Securities and Futures Commission in Hong Kong.

There can be no assurance that any estimates of future performance of any industry, security or security class discussed in this presentation can be achieved. The portfolio may or may not have current investments in the industry, security or security class discussed. Any reference or inference to a specific industry or company listed herein does not constitute a recommendation to buy, sell, or hold securities of such industry or company. Please be advised that any estimates of future performance of any industry, security or security class discussed are subject to change at any time and are current as of the date of this presentation only. Targets are objectives only and should not be construed as providing any assurance or guarantee as to the results that may be realized in the future from investments in any industry, asset or asset class described herein.

In respect of any discrepancy between the English and Chinese version, the English version shall prevail.