DeepSeek: A Sputnik Moment

C WorldWide has been in a strategic partnership with Harbor Capital, Inc. for almost three years. C WorldWide has published thought leadership on several relevant topics, including this piece focusing on the recent DeepSeek news and what it may mean with how we think about Artificial Intelligence, AI, in the future. Harbor is pleased to share C WorldWide’s thinking for your portfolio construction consideration.

Equity markets globally reacted abruptly on January 27, due to the introduction of the DeepSeek language model.

The model’s reception has been impressive. At the end of January, it became the number one most-downloaded app in Apple’s U.S. App Store, sending shock waves through Silicon Valley and causing the share price of major tech stocks to plummet. DeepSeek R1’s benchmark surpassed OpenAI’s o1 model on multiple fronts. In the context of AI models, a benchmark refers to a standardized test or set of evaluations designed to measure and compare the performance of different models across specific tasks. These benchmarks assess various capabilities, such as reasoning, mathematical problem-solving, coding proficiency, and language understanding. According to DeepSeek, they only spent $5.6mn on training the model, which is less than 10% of OpenAI’s GPT4o.

The true disruption of this news event is the cost reduction, on the back of market concerns that the hardware Total Addressable Market, or revenue opportunity available to a product or service, for model training might shrink to a fraction of prior expectations, and investment in AI might become biased towards software, thereby opening the playing field.

Never before have we seen a technology evolve as quickly as GenAI, or General Artificial Intelligence. The latest iteration of advancement from DeepSeek comes on top of another major innovation from September 2024, namely Chat GPT o1, where compute moved from training (the model) to inference (use of the model). This was a major event that, over the longer term, in our view, may impact and shift market shares amongst chip manufacturers (in a relative sense away from GPUs, or graphics processing units).

DeepSeek now presents smaller, more nimble models than o1 built on open source and a mixture of expert models (MoE) that prove to be much cheaper to build and use for inference, which will most likely further influence the chips market.

Open-source models can potentially democratize AI, threatening Big Tech’s ability to dominate it. We view the open-source methodology as positive for a broader tech ecosystem, which ultimately may be positive for all AI users and AI end demand.

DeepSeek adopted an MoE architecture for their model. LLM, or language learning model, and MoE are two different approaches to AI development. LLM is designed for general-purpose training. MoE is a sparse architecture where the model is divided into different experts (i.e., submodels). The MoE architecture brings a significant cost advantage to model inference and requires much less hardware.

While most cloud service providers are scaling up their computing clusters, DeepSeek is training their model under a constrained budget and using hardware resources to optimize performance. We believe this trend, because of the downsizing of the models, has the potential to benefit edge AI, or the deployment of AI directly on edge devices, devices.

As demand for inference is expected to increase massively, costs become critical. In other words, without serious cost decreases, inference will likely not ramp up as expected. According to news reports and our research, DeepSeek is 10-20 times less expensive for inference than existing models from, for example, OpenAI. For the maturation of AI, this is a great development.

Necessity is the Mother of Invention

We believe this proves that LLMs are commoditizing, and cost and scale are likely to be vital for commercial success. Several other Chinese model developers are about to introduce simpler and more optimized models. As they say, necessity is the mother of invention. The U.S. ban on exports of advanced semiconductor technology to China has forced China to innovate in model design and train on older versions of Nvidia GPU. It will be interesting to see whether the U.S. model developers change tactics by shifting away from brute force models and beginning to focus on model optimization. We think this may happen; in that sense, this is a small Sputnik moment.

The market price movements are telling us that it’s negative for the demand for leading-edge GPU/ASICs, or application-specific integrated circuits — at least in the short term. In the longer term, it’s more uncertain because of what is known as the Jevons Paradox. Jevons Paradox occurs when technological progress increases the efficiency with which a resource is used (reducing the amount necessary for any one use). Still, the falling cost of use induces increases in demand enough that resource use is increased rather than reduced.

This has historically been the case in computing and software. DeepSeek is just another downward shift in costs. This will likely amplify the demand for computing in the long term.

Also, these smaller models open the market for edge AI, where the models will reside on devices. This would not be possible with the large brute-force models.

While still early days, we believe preliminary investment conclusions are:

1. Aggressive growth expectations for leading-edge computing for training models will likely be questioned.
2. Longer-term demand for computing may increase because lower costs drive demand (Jevons Paradox).
3. Lower costs have the potential to accelerate the roadmap for edge AI. Advanced scaled-down models will run locally on devices.
4. Demand for computing and silicon has an opportunity to increase in totality.

China is an Innovative and Deflationary Force

Finally, considering DeepSeek’s sudden and unexpected geopolitical and economic impact, there are important parallels to other advances in Chinese industrial might, like EVs, or electric vehicles, renewables, robotics, etc. China is an innovative and deflationary force, which is a significant challenge for advanced technology and manufacturing in the West.

The U.S. chose AI as the arena for competition and confrontation. Have the U.S. sanctions in the name of national security backfired? Have the restrictions unintentionally made Chinese engineers more creative and resourceful? Could DeepSeek have come this far if the Chinese race for AI supremacy had happened on U.S. terms of brute force? What could be the next step for the U.S. to assert its leadership in AI supremacy? More sanctions? Discussions about banning or restricting DeepSeek in Western markets have not yet been explicitly reported. Still, its rapid rise could potentially lead to regulatory actions or calls for restrictions in the future. However, no matter what happens explicitly to Chinese models, the genie is out of the bottle in the sense that model development and resource use will change dramatically also for Western-developed models.

Therefore, this is a positive supply shock to the economy and, as such, positive for productivity and growth. It is good for every consumer and company that utilizes the technology. The value has the potential to migrate to the technology users.

Also, the fact that a relatively small outfit in China has managed to force itself into the top of the league table of GenAI should question the “exceptionalism” of certain U.S. tech companies. The premise that massive value will be extracted from excessive investments in model training and compute clusters should also be questioned. In that way, DeepSeek can also be seen as a term of Trade shock, which could have macroeconomic implications in the form of capital flows into the U.S. equity market and then into dollar assets. The U.S. technology sector is not the only game in town.

Important Information

This information has been provided by C WorldWide and was published in February 2025 for informational purposes only. It does not constitute or form part of any offer to issue or sell, or any solicitation of any offer to subscribe or to purchase, shares, units or other interests in investments that may be referred to herein and must not be construed as investment or financial product advice. Harbor nor C WorldWide has not considered any reader’s financial situation, objective or needs in providing the relevant information.

Investing entails risks and there can be no assurance that any investment will achieve profits or avoid incurring losses. Past performance is not necessarily a guide to future performance or returns. C WorldWide has taken all reasonable care to ensure that the information contained in this material is accurate at the time of its distribution, no representation or warranty, express or implied, is made as to the accuracy, reliability or completeness of such information.

The views expressed herein may not be reflective of current opinions, are subject to change without prior notice. This material does not constitute investment advice and should not be viewed as a current or past recommendation or a solicitation of an offer to buy or sell any securities or to adopt any investment strategy.

This material may contain forward-looking information that is not purely historical in nature. Such information may include, among other things, projections and forecasts. There is no guarantee that any of these views will come to pass.

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