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ON Feb 16, we will say goodbye to the Year of the Wood Snake and hello to the Year of the Fire Horse. The Wood Snake has been a year of ups and downs, beginning with US President Donald Trump’s tariff shock in April. But since then, overall investments worldwide have been good for most investors. 

Based on a standard 60:40 equity/bond portfolio, returns have been from 12% to 15% in 2025, whereas stock markets like Singapore returned 22.5%. 

Bursa Malaysia returned 13.2%, with better performance towards the year end, while the ringgit appreciated against the US dollar by 10.2%. In terms of commodities, gold outperformed with 64.6%, silver 147.9%, but crude oil slid 20%. Bitcoin lost 6.3%, shaking confidence in its long-term store of value potential.

One should not believe in astrology to predict your investment performance, but the Wood Snake last appeared in 1929 (the US Great Crash) and 1941 (attack on Pearl Harbour and the US’ entry into World War II). 

Here is what one artificial intelligence (AI) astrologer says about the Year of the Fire Horse: “It promises to be a vibrant, fast-moving and potentially transformative period. It’s time to embrace courage, pursue your passions and channel all that fiery energy into positive action.”

These astrological predictions are so general and can mean anything to anyone, so one should not believe in such prognostications, other than for entertainment.

However, the world is in serious “rupture”, according to Canadian Prime Minister Mark Carney, or in transition to a new order or disorder. Hence, one’s fortunes could be disrupted by geopolitics, war or climate/natural disasters. 

The area that most people acknowledge as a serious disruptor is AI and technology, because since the arrival of ChatGPT in November 2022 and DeepSeek in January 2025, AI or generative AI, large learning models and faster chips for computing have propelled serious valuations to trillion-dollar levels, notably for Nvidia, Google, Meta, Apple and Broadcom.

How will the AI or agentic models play out in terms of diffusion, winners and investments? I have been playing with several models myself only in terms of usage for research and writing, but not yet for building my own models for specific purposes. 

However, the AI landscape seems to be highly open-ended, with deadly serious competition between US and Chinese models, as well as massive competition by the leading players, especially the hyperscalers like Google, Meta, Alibaba, Grok (Elon Musk’s chatbot) and Open AI (ChatGPT).

The US is going for the proprietary closed weight business model, where the income model is fee-based depending on usage, or incorporated inside other fee-paying services (such as Gemini bundled in Google services or Co-Pilot bundled with Microsoft products). 

The Chinese open weight business model is open source (like DeepSeek), which allows anyone to build their own learning models based on DeepSeek coding, and their funding is either through venture capital partners or funded by rich hyper-platforms like Alibaba, Baidu or Tencent.

Closed weight means closed source models where the weighting of numerical parameters to calculate and datasets used are not known to users. 

Open weight means disclosure of parameters, but not the datasets used to train such models. 

Chinese models are far cheaper to run than American ones, with DeepSeek at four US cents and Alibaba Qwen at three US cents per million tokens. The American ChatGPT-4o Mini costs 15 US cents while Gemini 2.5 Flash costs 10 US cents per million tokens.

In terms of scale, ChatGPT has 800 million weekly active users, roughly 65% of the standalone chatbot market, down from 90% in 2024. Gemini has gained market share the fastest, rising to 650 million monthly users, mainly because of Google’s billion-plus network reach and very user-friendly access. 

DeepSeek has 300 million monthly users and is popular with AI developers because of its open source. Perplexity (backed by Nvidia) has 4% to 7% of the market and Claude (Anthropic) has 2% to 3% market share.

It is unclear at this moment whether there will be any clear winners in the AI game, because leading depends on funding, computing power and research and development (R&D) costs. 

While the market leaders will always have headline advantages due to scale, there is little doubt in my mind that each country and individual users will use different models built on their own diverse datasets to create specific specialisation or market niches that will appeal to specialist users. 

AI is currently widely used in military/defence, healthcare and finance, which have deep pocket users willing to fund experiments and R&D.

The big question is the viability of OpenAI, which is currently unlisted and has the largest unlisted valuation at US$500 billion (RM1.9 trillion), based on recent funding raised by investors such as SoftBank. Many investors are sceptical whether the current cash flow revenue source of OpenAI (US$2 billion in 2023 to US$20 billion by end-2025) is sufficient to meet its commitments of over US$1 trillion in hardware (computing power) investments. 

Proponents think that the hardware commitments are funded by Nvidia, Oracle and others with deep pockets, these being circular funding (Nvidia investing in OpenAI to use its superfast chips). 

Latest financial projections suggest that OpenAI will only be at the break-even point by 2030, whereas it will float an IPO (raise public funding) in 2027. The risk is whether competitors like Gemini gain on ChatGPT’s market share or its business model is disrupted by a new breakthrough in using cheaper chips with similar or faster computing power.

The fact that Nvidia and other Magnificent Seven stock valuations gained only 27.5% in 2025, compared with 48.3% in 2024, may be a sign that the AI super-valuations are being reassessed more cautiously by serious investors. 

The bigger you grow, the slower the growth rate. However, the Magnificent Seven are so profitable so far that they can outinvest others in terms of R&D and know how different technologies can improve their supply chain and overall productivity.

There are so many new players in the AI field in the US and China (let alone in Europe, Japan and India) that we cannot say for sure that the big players (hyperscalers) will continue to dominate. My personal view is that AI diffusion through different countries, companies and industries will create new valuations, but also serious value destruction by the AI laggards. 

Retail investors are at a disadvantage in not knowing which start-ups are going to be the new winners, so the safer bet is to back the current hyperscalers.

This is where Trump’s policy gyrations may have significant disruption on markets. The Trump administration wants to have a buoyant market in order to win the mid-term elections in November.

It also wants lower interest rates to cut fiscal interest costs. But if inflation resurfaces, as the dollar depreciates, then markets will remain turbulent, even if the incoming US Federal Reserve chairman Kevin Warsh may be an experienced monetary economist.

In short, the Fire Horse could be fiery in terms of volatile transformations, so buckle up and enjoy the thrills or scares in 2026!

Tan Sri Andrew Sheng writes on global issues from an Asian perspective.

The views expressed here are the views of the writer and do not necessarily reflect those of the Daily Express. If you have something to share, write to us at: Forum@dailyexpress.com.my