DeepSeek: an AI industry upstart

Not too long ago, the term artificial intelligence (AI) was found only in the realm of science fiction novels. It was featured prominently in works such as Phillip K. Dick's "Do Androids Dream of Electric Sheep?" which the cult movie classic "Blade Runner" was based on, and Isaac Asimov's "I, Robot", which also inspired a movie of the same name. Fast forward to today, and the term has since become synonymous with all things digital. It encompasses everything from the smart robot vacuum cleaner assiduously hoovering up all the dirt on your home floor, to the virtual assistant on your smartphone answering all the queries you throw at it.

Looking at the multibillion-dollar industry that has coalesced to allow these applications to proliferate in all aspects of daily life, we would assume that massive capital expenditure and time are needed to develop infrastructure and train AI programmes. However, a small, independent research laboratory based in Hangzhou, China, appears to be challenging this conventional wisdom. Founded by entrepreneur Liang Wenfeng, the AI startup's DeepSeek chatbot has roiled the tech world. DeepSeek has performed nearly as well, if not better, than AI models from Microsoft-backed OpenAI's ChatGPT, Meta's Llama and Amazon-backed Anthropic's Claude. What is truly surprising, however, is that the company claimed to have spent less than US dollar (USD) 6 million to build its AI model--approximately ten times less than the amount Meta spent on its product--and achieved this feat in just two short months.

Conventional wisdom dictates that companies use Nvidia's expensive, cutting edge H200 or B200 graphical processing units (GPUs) to train their AI models for optimal results. Prevailing sanctions prohibit US companies from selling advanced computer chips to mainland China; however, the programmers of DeepSeek were apparently able to produce results with the older H800 GPUs by wringing out every last bit of performance from them. The revelation shocked the tech industry and sparked a selloff in the shares of semiconductor firms including Nvidia, Broadcom and Micron.

In our view, these developments could lead to changes in the way AI models are trained, particularly from a cost and efficiency perspective. DeepSeek's innovation in the field has established that the "mixture of experts" ¹ (MoE) approach, which requires less computing power and time, coupled with the "reward system" ² are as effective as the more resource-intensive chain-of-thought ³ reasoning approach.

Falling costs will mean lower barriers to entry, allowing more companies to partake in AI development and grow the ecosystem at a more rapid pace. Additionally, open source AI models, like DeepSeek's, which make the programme's source code available for public use and modification, have now been proven to perform just as well, if not better, to proprietary models from Big Tech. We believe the trend towards using open source inference models with narrower parameters will persist. As a result, we expect to see broader adoption and implementation of AI applications across both corporate and government sectors in the days ahead. We had previously touched on the subject of AI models improving in terms of efficiency and cost-effectiveness in our article A Fundamental Change for AI?

Although semiconductor firms such as Nvidia were sold down on fears that their chips might face lower demand, we believe it would be premature to write them off. DeepSeek's AI model training is still based on Nvidia's GPUs and their CUDA software, albeit on older hardware. Hence, we still expect healthy demand for such chips as the training of AI models continues to intensify.

China's underrated tech sector

From our perspective, the markets may have been discounting China's tech sector, represented by Baidu, Alibaba and Tencent (BAT), in comparison to the broader US industry represented by Facebook, Amazon, Apple, Netflix and Google (FAANG). It is only recently that the markets have started to recognise the potential value of Chinese tech startups, like DeepSeek, which have the prowess to compete on the global stage. Valuation-wise, we have observed that US FAANG firms are approximately twice as expensive as their BAT Chinese counterparts.

Chart 1: BAT stocks at a significant discount compared to FAANG stocks

Source: Goldman Sachs, February 2025

Meanwhile, competition within China's domestic market is already intensifying as AI models from Chinese firms such as Baidu, Zhipu and Bytedance's Doubao are being launched. Tech giant Alibaba is even claiming that its Qwen 2.5 version AI model is superior to DeepSeek's V3 AI model. We expect these developments to eventually enable users to switch models in their applications at a low cost. As a case in point, we are now seeing international firms like Perplexity, a San Francisco-based developer of a conversational search engine, incorporate and offer DeepSeek's AI models on their platforms.

These events are in line with what we had discussed in the Asian equity outlook 2025, where we explored the implications of generative AI transitioning to the next level of development following massive capital expenditure.

Roadblocks to further AI adoption

A major obstacle standing in the way of broader AI usage in light of DeepSeek's claimed breakthrough is the escalation of US-China geopolitical tensions. A technological arms race between the world's two largest economies will certainly hinder any progress in building an ecosystem that would propel AI applications to the forefront of worldwide adoption. There are already news reports that US officials are investigating how DeepSeek was able to procure Nvidia-made AI chips in spite of the ban, and US government workers are prohibited from using the application due to national security concerns.

Should the US further tighten export controls to stem the flow of AI chips and technology to China, we believe that it would affect the speed of future AI model training there as domestic supply is currently unable to make up the shortfall. We therefore believe that chip independence should remain a priority for China in order for the country to continue its advancements in the AI field.

Data privacy is another significant concern. The integration of AI into all aspects of the internet makes it even more challenging to regulate the personal information we allow to be collected online, given the data-intensive nature of such systems.

Then, there is the issue of AI "hallucinations" where generative AI chatbots produce misleading or entirely wrong information due to incorrect or skewed data that the AI model is trained on. This problem reflects an old adage from Computer Science 101: "garbage in, garbage out". However, as AI technology matures, this risk is decreasing as improved data, better architecture, reinforced learning and guardrail filters improve the user experience.

Finally, there is the million-dollar question of how AI can be monetised to help enterprises address business pain points. We believe that companies engaged in content production, autonomous driving, robotics and industry-specific SaaS stand to benefit the most from the greater adoption of AI models. Beyond the monetisation question, AI-enhanced efficiency in areas such as automation, robotics, inventory management, cyber security and targeted advertising are significant benefits that no CEOs of large corporations can afford to ignore. In our view, the fields highlighted here have the most potential for robust, sustainable returns.

Full steam ahead for AI

The speed at which AI applications are becoming part and parcel of daily life is breathtaking, with DeepSeek's apparent breakthrough merely accelerating an inevitable, fundamental change in the field. We firmly believe these breakthroughs are the key components needed for sustainable, long-term returns.

We also are firm believers in the Jevons Paradox, an economic theory that suggests that as technological advancements increase the efficiency with which a resource is used, the overall consumption of that resource actually increases rather than decreases. We have seen this with improvements in fuel efficiency resulting in more people driving, in turn increasing total global fuel consumption. A similar phenomenon was seen during the Industrial Revolution as an improvement in the efficiency of steam engines did not reduce coal consumption but led to a boom in coal demand. We believe that the AI industry is highly likely to follow a similar pattern, leading to even greater long-term demand for AI-related applications.

Any reference to a particular security is purely for illustrative purpose only and does not constitute a recommendation to buy, sell or hold any security. Nor should it be relied upon as financial advice in any way.

¹ A machine learning approach that divides an AI model into separate sub-networks (or "experts").

² A method in which AI algorithms are trained to make decisions by being rewarded or punished for their actions.

³ An approach allowing models to break down complex problems into simpler steps that can be solved individually.

Important disclaimer information

Please note that much of the content which appears on this page is intended for the use of professional investors only.

How Political Bias Can Undermine Investment Decisions - and Why a Rules-Based Approach Wins

The past several months have been a case study in how politics can divide not just a nation, but also its investors. The transition of power in the United States has reignited debates, strengthened ideological loyalties, and--perhaps most significantly for markets--shaped investor behaviour. A recent study, Political Climate, Optimism, and Investment Decisions by Bonaparte, Kumar, and Page (2009), sheds light on an often-overlooked aspect of this intersection: how political preference influences risk-taking in financial markets.

The findings are striking but not entirely surprising. Investors tend to be more optimistic about the domestic economy and take on riskier exposures when their preferred political party is in power. Conversely, when their party is out of office, their outlook becomes more pessimistic, and they reduce risk exposure. This behavioural shift has real consequences, leading investors to make decisions that are influenced more by personal ideology than by market fundamentals.

At ECCM, we appreciate the importance of political discourse and the broader role it plays in shaping economic policy. However, we also recognise that politics and profitable investing don't always mix well. Allowing political biases to dictate investment decisions can be costly, especially in a world where market trends move independently of electoral cycles.

This is why our trend-following strategies remain politically agnostic. They are designed to remove cognitive bias from investment decision-making, ensuring that capital is allocated based on market price movements rather than sentiment or political affiliation. By following a systematic, rules-based approach, we aim to capture significant market trends--whether they emerge in times of political stability or uncertainty.

Markets have historically moved higher under both Republican and Democratic administrations in the U.S., and similar trends hold true across different political environments globally. The key to long-term success isn't aligning investments with a preferred political ideology; it's having a disciplined approach that adapts to market conditions, no matter who is in office.

Conclusion

As we continue to observe political shifts and the narratives they inspire, we are reminded of the importance of staying focused on what truly drives returns. A rules-based investment process helps protect against the risks of letting short-term political sentiment dictate long-term financial outcomes. By remaining politically neutral in our investment strategies, we ensure that our clients' capital is positioned to benefit from opportunities wherever and whenever they arise.

At ECCM, our educational foundations are in finance and psychology. With extensive trading experience and long-term dedication to quantitative trading systems, we seek to provide our clients with our carefully developed approach to navigating the complexities and vagaries of markets.

Wholesale clients can find more information on ECCM and our flagship ECCM Systematic Trend Fund at our website and Australian Fund Monitors.

Cyclical small companies may be among those most likely to outperform in an anticipated small cap recovery from the doldrums of the past few years.

Local small caps as a whole struggled last year as higher interest rates and slowing economic activity depressed demand for their goods and services, while simultaneously increasing their debt burden.

In fact, the S&P/ASX Small Ordinaries Accumulation Index has underperformed the top 100 companies by 30 per cent over the past three years as investors have instead focused on the stellar gains in the US sharemarket and a small number of growth companies more generally.

That trend is now expected to reverse and there's more to this recovery than just an anticipated reversion to the mean. Earnings growth from small companies could be around 10 per cent per annum over the next two years, compared to an average of just 2-3 per cent for the top 100 ASX stocks.

Cyclical small caps are primed to be among the standouts. The multiple rate cuts expected in Australia - potentially beginning as soon as February - will finally support a recovery in their customer demand and obviously reduce the cost of servicing debt.

To put the potential of this cohort into perspective: a tidy 8.5 per cent gain in the overall Small Ords in 2024 was driven by just the top 10 stocks in the index, only one of which was a cyclical company.

The top 10 included family tracking app Live360, Telix Pharmaceuticals and buy now, pay later provider Zip Co. The sole cyclical in the list was CSR - and its momentum was partly attributable to its $4.3 billion takeover by French building products giant Saint-Cobain.

Cyclical stocks best-placed to benefit from a more robust economic environment include companies that can increase earnings from more than just the economic cycle.

Management initiatives that boost market share or reduce operating costs, for instance, will play an equally critical role in their recovering fortunes.

Examples of companies in this category include construction materials and equipment services business Maas Group (ASX: MGH), steel distributor Vulcan Steel (ASX: VSL) and outdoor advertising company oOh! Media (ASX: OML). All are cyclical businesses with strong management teams and the potential for market share gains and margin expansion.

But it's the resources arena that we believe may deliver some of the best small cap performers of the year. A combination of the cyclical drivers above and structural tailwinds unique to the resources sector provide a solid foundation for potential gains.

Small resource companies have suffered over several years due to concerns about the prospects of economic growth in China. Their share price gains have been further stymied by the markets' short-term focus on lower-than-expected stimulus measures from the Chinese government and the prospect of tariffs being imposed by the new Trump administration.

Both the latter factors are likely overstated. The reality is that some of China's stimulus measures are already bearing fruit, and the Chinese government has sent strong signals that it would enact more measures if required to reignite the country's economy.

In terms of China's export trade, the potential blow of any tariffs implemented by the Trump administration would be softened by the fact that only 15 per cent of its exports are to the US. Tariffs on that market would not impact its exports to other major trading partners such as Europe, Japan and South Korea.

Beyond geopolitics, the long-term growth in demand for commodities required for decarbonisation is not reflected in the current valuation of small cap resource stocks.

Copper, in particular, is a commodity that will experience increased demand as the push towards net zero economies gathers pace.

The volume of copper per electric vehicle, for example, is up to four times more than required for an internal combustion engine car. It is also an essential component of both electrical transmission capacity and renewable energy infrastructure.

The wide range of applications for copper across different elements of the decarbonisation process, as well as the broader economy, mean this demand is unlikely to be impacted greatly by any uncertainty generated by the Trump administration's climate policies.

In fact, conservative forecasts from BHP suggest that copper demand will increase by 70 per cent by 2050 - but supply is highly constrained and new copper mines face significant hurdles to establish.

Companies such as Capstone Copper (ASX: CSC) may be well-placed to capitalise on the anticipated increased demand. The dual-listed company - which sits on the Australian and Canadian bourses - has diversified operations across the US, Mexico and South America. Its production volume is likely to increase by up to 100 per cent over the next five years and its costs are expected to fall as those volumes increase and new mines are brought online.

And it's not just resource companies themselves that could benefit from the above dynamics. Mining service companies will also be at an advantage if higher copper and gold prices lead to a cyclical recovery in exploration activity. Mining tech company Imdex (ASX: IMD) is one leading example in this category.

Author: Michael Steele, Co-Head of Small Cap Equities

As we enter 2025, investors are navigating a shifting landscape shaped by evolving central bank policies, economic uncertainty, and fiscal dynamics. While challenges remain, there are also opportunities on the horizon.

Charlie Jamieson, Chief Investment Officer, explores the key themes set to influence bond markets this year from interest rate movements to government spending and policy direction. Below is a brief summary.

Summary of key themes for bond markets in 2025

Recap of 2024: The bond market faced underwhelming performance despite global rate cuts. A key driver of this was a sell-off in long-dated bonds, spurred by expectations of continued US fiscal spending. In Australia, the Reserve Bank of Australia (RBA) held interest rates steady throughout 2024 but is expected to begin cutting in February 2025, which should provide support to bond markets given current valuations.

Global economic outlook: The outlook for 2025 remains divided, particularly with the Trump administration now in its second term. The US economy continues to perform well, spurred on by the "Trump effect" of strong business optimism. However, economic conditions in the rest of the world are weaker, with Europe, Canada, Australia, and New Zealand all expected to cut rates further.

Policy uncertainty: While markets had hoped for more clarity, there is still little certainty around economic policy direction. A major area of concern is the potential for increased tariffs, which could reintroduce inflationary pressures. Although not yet confirmed, the expectation is that tariffs will be implemented and may rise throughout the year. This, combined with Trump's stated preference for lower inflation and interest rates, creates a complex policy landscape that could have significant market implications.

Fixed Income performance^: For fixed income investors, returns are expected to be relatively solid. Cash returns should remain in the 3-4% range, while bond market performance could reach 5-6%, depending on yield movements.

Government spending and fiscal policy: In both the US and Australia, public sector spending has been a major driver of economic activity. However, with concerns over inflation and fiscal sustainability, there is increasing pressure to rein in spending.

As investors navigate 2025, market divergence, policy uncertainty, and fiscal decisions will be key factors shaping the bond market outlook.

^ Recipients should not rely on this information in making investment decisions. The information here is illustrative and shall not be relied upon as a promise or representation of past or future performance. All investments contain risk.

Charlie Jamieson, Chief Investment Officer

Globally, equity markets were positive in January. In the US, the S&P 500 rose +2.7%, the Nasdaq increased +1.6%, whilst in the UK, the FTSE was up strongly, rising +6.1%.

Domestically, the ASX All Ordinaries Accumulation index outperformed its US peers, rising +4.4%. On the ASX, the top performing sectors were gold and financials, whilst defensive sectors such as utilities and telecommunications underperformed. A subdued inflation data point in Australia released in late January boosted investor sentiment, increasing the likelihood of the Reserve Bank of Australia (RBA) cutting rates in the near term. Bond markets were relatively quiet in January. The US 10 year government bond yield was slightly up (~ +2 basis points) to close at 4.53%, whilst in Australia, the 10 year bond yield increased +6 bp to close at 4.43%.