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China’s DeepSeek AI scores important victory against US tech hegemony

We republish below three articles about the recent release of DeepSeek R1, an artificial intelligence (AI) model that performs as well as – or better than – its major US-based competitors, but at a fraction of the cost and using relatively low-grade semiconductors.

The first article, by Marxist economist Michael Roberts, notes that DeepSeek R1 is fully open source, meaning that the code behind it is fully visible to programmers around the world and can be freely used and adapted. “This is a real blow to the ‘proprietary’ secrets that OpenAI or Google’s Gemini lock away in a ‘black box’ in order to maximise profits. The analogy here is with branded and generic pharmaceuticals.” Indeed, the whole orientation of DeepSeek is towards scientific research and the production of social goods, rather than the relentless pursuit of profit at all costs.

Michael observes that DeepSeek has caused unprecedented losses to US technology stocks – “chipmaker Nvidia and so-called ‘hyperscalers’ Alphabet, Amazon, Microsoft and Meta Platforms collectively shed almost $750bn of their stock market value in one day” – as it became apparent that the tech giants’ spending of billions of dollars on scaling their computing power is essentially unnecessary. These companies have put all their eggs in the hardware basket, but a small team of researchers in China have shown that the mathematical/algorithmic component is at least as important.

Meanwhile, the DeepSeek phenomenon is a powerful demonstration that the US “chip wars” are not having the desired effect:

What must enrage the tech oligarchs sucking up to Trump is that US sanctions on Chinese companies and bans on chip exports have not stopped China making yet more advances in the tech and chip war with the US. China is managing to make technological leaps in AI despite export controls introduced by the Biden administration intended to deprive it of both the most powerful chips and the advanced tools needed to make them.

Michael further points to the political economy of the situation, noting that “state-led planned investment into technology and tech skills by China works so much better than relying on huge private tech giants led by moguls.” He quotes billionaire tech investor Ray Dalio: “In our system, by and large, we are moving to a more industrial-complex- type of policy in which there is going to be government-mandated and government-influenced activity, because it is so important… Capitalism alone — the profit motive alone — cannot win this battle.”

The second article, by Gary Wilson in Struggle La Lucha, provides a broad overview of the geopolitics of the “chip wars” and the significance of DeepSeek’s success.

DeepSeek’s model outperformed OpenAI’s best, using less data, less computing power, and a fraction of the cost. Even more remarkable, DeepSeek’s model is open-source, meaning anyone can use, modify, and build on it. This stands in stark contrast to OpenAI’s closed, profit-driven approach.

Gary’s article continues to contrast DeepSeek’s business model – and China’s overall approach to AI – with that of the US tech giants:

Corporate rulers want AI to monitor workers, lower wages, bust unions, or shift work to machines altogether, leading to cutbacks and layoffs. The World Economic Forum famously predicted that AI would replace millions of “useless” human workers by 2030. Unlike US tech companies seeking monopoly control, DeepSeek treats AI like electricity or the Internet — a basic tool that should be accessible to everyone… AI, as a public utility, can be used to complement human labor, improve safety, reduce drudgery, and create better-paying jobs rather than eliminate them.

This touches on the broader question of the role of technology in society. Under capitalism, AI is used to maximise profits, which often means replacing human labour with algorithms, thereby deepening unemployment and, ultimately, impacting the long-term viability of the entire system by reducing the rate of profit. Under working class leadership on the other hand, technology can be used to improve the quality of life for all.

An editorial in the Morning Star on 28 January reiterates the blowback effect of US’s tech sanctions on China. “In placing sanctions on microchip exports to China, it forced developers in that country to use their chips more efficiently.”

Furthermore, DeepSeek is indicative of China’s emergence as a technology superpower. “The days are gone when Chinese economic advance largely relied on technical innovations developed elsewhere.” As such, “this week’s events are a landmark in the decline of US hegemony, and in the development of global multipolarity. With all its contradictions and contestations, that can only be welcome.”

AI going DeepSeek

Most readers will know the news by now. DeepSeek, a Chinese AI company, released an AI model called R1 that is comparable in ability to the best models from companies such as OpenAI, Anthropic and Meta, but was trained at a radically lower cost and using less than state-of-the art GPU chips. DeepSeek also made public enough of the details of the model that others can run it on their own computers without charge.

DeepSeek is a torpedo that has hit the Magnificent Seven US hi-tech companies below the water line. DeepSeek did not use the latest and best Nvidia’s chips and software; it did not require huge spending on training its AI model unlike its American rivals; and it offers just as many useful applications.

DeepSeek built its R1 with Nvidia’s older, slower chips, which US sanctions had allowed to be exported to China. The US government and the tech titans thought they had a monopoly in AI development because of the huge costs involved in making better chips and AI models. But now DeepSeek’s R1 suggests that companies with less money can soon operate competitive AI models. R1 can be used on a shoestring budget and with much less computing power. Moreover, R1 is just as good as rivals at ‘inference’, the AI jargon for when users question the model and get answers. And it runs on servers for all sorts of companies so that they need not ‘rent’ at huge prices from the likes of OpenAI.

Most important, DeepSeek’s R1 is ‘open source’, namely that is coding and training methods are open to all to copy and develop. This is a real blow to the ‘proprietary’ secrets that OpenAI or Google’s Gemini lock away in a ‘black box’ in order to maximise profits. The analogy here is with branded and generic pharmaceuticals.

The big issue for the US AI companies and their investors is that it appears that building huge data centres to house multiples of expensive chips may not be necessary in order to achieve sufficiently successful outcomes. Up to now, the US companies have been ratcheting up huge spending plans and trying to raise mega amounts of funding to do so. Indeed, on the very Monday that DeepSeek’s R1 hit the news, Meta announced another $65bn of investment, and only days earlier President Trump announced government subsidies of $500bn to the tech giants as part of the so-called Stargate project. Ironically, Meta chief executive Mark Zuckerberg said he was investing because “We want the US to set the global AI standard, not China.” Oh dear.

Now investors are concerned that this spending is unnecessary and, more to the point, that it will hit the profitability of the American companies if DeepSeek can deliver AI applications at a tenth of the cost. Five of the biggest technology stocks geared to AI — chipmaker Nvidia and so-called ‘hyperscalers’ Alphabet, Amazon, Microsoft and Meta Platforms — collectively shed almost $750bn of their stock market value in one day.

And DeepSeek does threaten the profits of the data centre companies and the water and power operators which expect to benefit from the huge ‘scaling up’ by the Magnificent Seven. The US stock market boom is heavily concentrated in the ‘Magnificent Seven’.

So has DeepSeek punctured the massive stock market bubble in US tech stocks? Billionaire investor Ray Dalio thinks so. He told the Financial Times that 
“pricing has got to levels which are high at the same time as there’s an interest rate risk, and that combination could prick the bubble … Where we are in the cycle right now is very similar to where we were between 1998 or 1999,” Dalio said. “In other words, there’s a major new technology that certainly will change the world and be successful. But some people are confusing that with the investments being successful.”

But that may not be the case, at least not just yet. The AI chip company Nvidia’s stock price may have dived this week, but its ‘proprietary’ coding language, Cuda, is still the US industry standard. While its shares dropped nearly 17%, that only brings it back to the (very, very high) level of September.

Much will depend on other factors like the US Fed keeping interest rates high because of a reversal in the fall in inflation and on whether Trump proceeds big time with his tariff and immigration threats that will only fuel inflation.

What must enrage the tech oligarchs sucking up to Trump is that US sanctions on Chinese companies and bans on chip exports have not stopped China making yet more advances in the tech and chip war with the US. China is managing to make technological leaps in AI despite export controls introduced by the Biden administration intended to deprive it of both the most powerful chips and the advanced tools needed to make them.

Chinese tech champion Huawei has emerged as Nvidia’s primary competitor in China for ‘inference’ chips. And it has been working with AI companies, including DeepSeek, to adapt models trained on Nvidia GPUs to run inference on its Ascend chips. “Huawei is getting better. They have an opening as the government is telling the big tech companies that they need to buy their chips and use them for inference,” said one semiconductor investor in Beijing.

This is a further demonstration that state-led planned investment into technology and tech skills by China works so much better than relying on huge private tech giants led by moguls. As Ray Dallo said: “In our system, by and large, we are moving to a more industrial-complex- type of policy in which there is going to be government-mandated and government-influenced activity, because it is so important…Capitalism alone — the profit motive alone — cannot win this battle.”

Nevertheless, the AI titans are not yet the titanic. They are going ahead with ‘scaling up’ by ploughing yet more and more billions into data centres and more advanced chips. This eating up computer power exponentially.

And of course, there is no consideration of what mainstream economists politely like to call ‘externalities’. According to a report by Goldman Sachs, a ChatGPT query needs nearly 10 times as much electricity as a Google search query. Researcher Jesse Dodge did some back-of-the-napkin math on the amount of energy AI chatbots use. “One query to ChatGPT uses approximately as much electricity as could light one light bulb for about 20 minutes,” he says. “So, you can imagine with millions of people using something like that every day, that adds up to a really large amount of electricity.” More electricity consumption means more energy production and in particular more fossil-fuelled greenhouse gas emissions.

Google has the goal of reaching net-zero emissions by 2030. Since 2007, the company has said its company operations were carbon neutral because of the carbon offsets it buys to match its emissions. But, starting in 2023, Google wrote in its sustainability report that it was no longer “maintaining operational carbon neutrality.” The company says it’s still pushing for its net-zero goal in 2030. “Google’s real motivation here is to build the best AI systems that they can,” Dodge says. “And they’re willing to pour a ton of resources into that, including things like training AI systems on bigger and bigger data centers all the way up to supercomputers, which incurs a tremendous amount of electricity consumption and therefore CO2 emissions.”

Then there’s water. As the US faces droughts and wildfires, the AI companies are sucking up deep water to ‘cool’ their mega data centres to protect the chips. More than that, Silicon Valley companies are increasingly taking control of water supply infrastructure to meet their needs. Research suggests, for instance, that about 700,000 litres of water could have been used to cool the machines that trained ChatGPT-3 at Microsoft’s data facilities.
Training AI models consumes 6,000 times more energy than a European city. Furthermore, while minerals such as lithium and cobalt are most commonly associated with batteries in the motor sector, they are also crucial for the batteries used in datacentres. The extraction process often involves significant water usage and can lead to pollution, undermining water security.

Sam Altman, the previous non-profit hero of Open AI, but now out to maximise profits for Microsoft, argues that yes, unfortunately there are ‘trade-offs’ in the short term, but they’re necessary to reach so-called AGI; and AGI will then help us solve all these problems so the trade off of ‘externalities’ is worth it.

AGI? What’s this? Artifical generalised intelligence (AGI) is the holy grail of AI developers. It means that AI models would become ‘superintelligent’ way above human intelligence. When that is achieved, Altman promises, its AI won’t just be able to do a single worker’s job, it will be able to do all of their jobs: “AI can do the work of an organization.” This would be the ultimate in maximising profitability by doing away with workers in companies (even AI companies?) as AI machines take over operating, developing and marketing everything. This is the apocalyptic dream for capital (but a nightmare for labour: no job, no income).

That’s why Altman and the other AI moguls will not stop expanding their data centres and developing yet more advanced chips just because DeepSeek has undercut their current models. Research firm Rosenblatt forecast the response of the tech giants: “In general, we expect the bias to be on improved capability, sprinting faster towards artificial general intelligence, more than reduced spending.” Nothing must stop the objective of super-intelligent AI.

Some see the race to achieving AGI as a threat to humanity itself. Stuart Russell, professor of computer science at the University of California, Berkeley, said “Even the CEOs who are engaging in the race have stated that whoever wins has a significant probability of causing human extinction in the process, because we have no idea how to control systems more intelligent than ourselves,” he said. “In other words, the AGI race is a race towards the edge of a cliff.”

Maybe, but I continue to doubt that human ‘intelligence’ can be replaced by machine intelligence, mainly because they are different. Machines cannot think of potential and qualitative changes. New knowledge comes from such transformations (human), not from the extension of existing knowledge (machines). Only human intelligence is social and can see the potential for change, in particular social change, that leads to a better life for humanity and nature.

What DeepSeek’s emergence has shown is that AI can be developed to a level that can help humanity and its social needs. It’s free and open and available to the smallest user and developer. It has not been developed at a profit or to make a profit. As one commentator put it: “I want AI to do my laundry and dishes so that I can do art and writing, not for AI to do my art and writing so that I can do my laundry and dishes.” Managers are introducing AI to “make management problems easier at the cost of the stuff that many people don’t think AI should be used for, like creative work….. If AI is going to work, it needs to come from the bottom-up, or AI is going to be useless for the vast majority of people in the workplace”.

Rather than develop AI to make profits, reduce jobs and the livelihoods of humans, AI under common ownership and planning could reduce the hours of human labour for all and free humans from toil to concentrate on creative work that only human intelligence can deliver. Remember the ‘holy grail’ was a Victorian fiction and later a Dan Brown one as well.


Open source vs. closed doors: How China’s DeepSeek beat U.S. AI monopolies

China’s DeepSeek AI has just dropped a bombshell in the tech world. While U.S. tech giants like OpenAI have been building expensive, closed-source AI models, DeepSeek has released an open-source AI that matches or outperforms U.S. models, costs 97% less to operate, and can be downloaded and used freely by anyone.

While the U.S. tried to monopolize AI with economic sanctions on China and embargoes on semiconductor technology to China, China’s technologically adept workforce quietly worked around these barriers.

While the Trump administration was busy constructing a $500 billion AI boondoggle called Stargate, DeepSeek engineered a technological breakthrough that exposed the entire expensive Stargate charade as another giveaway to the wealthy.

DeepSeek’s model outperformed OpenAI’s best, using less data, less computing power, and a fraction of the cost. Even more remarkable, DeepSeek’s model is open-source, meaning anyone can use, modify, and build on it. This stands in stark contrast to OpenAI’s closed, profit-driven approach.

Corporate rulers want AI to monitor workers, lower wages, bust unions, or shift work to machines altogether, leading to cutbacks and layoffs. The World Economic Forum famously predicted that AI would replace millions of “useless” human workers by 2030.

Unlike U.S. tech companies seeking monopoly control, DeepSeek treats AI like electricity or the Internet — a basic tool that should be accessible to everyone.

The ability to offer a powerful AI system at such a low cost and with open access undermines the claim that AI must be restricted behind paywalls and controlled by corporations. In contrast to monopoly capitalism, this approach offers an alternative that fosters innovation and benefits society in general.

AI, as a public utility, can be used to complement human labor, improve safety, reduce drudgery, and create better-paying jobs rather than eliminate them.

Beyond mere manufacturing, China has methodically built technological ecosystems that now dominate global markets: Huawei’s telecommunications, BYD’s electric vehicles, CATL’s next-generation battery technologies, and Tongwei Solar’s advanced photovoltaic systems.

In just 15 years, the global technological landscape has been transformed. Between 2003 and 2007, the United States led in 60 out of 64 key technologies. By 2022, this dominance had reversed, with China leading in 52 technologies—a dramatic shift in global technological supremacy.


Chinese AI advance threatens US hegemony

History may have been made this week when, for the first time, a Chinese technological development had the effect of wiping at least a trillion dollars off corporate values on the US stock market.

Artificial intelligence firm DeepSeek caused the crash by showing that it can deliver the same results as US-originated AI monopolies at a fraction of the cost.

At least in part, this is a result of an own goal by the US government. In placing sanctions on microchip exports to China, it forced developers in that country to use their chips more efficiently.

That means it uses less memory to accomplish the same tasks as products developed by OpenAI, Meta, Google and other US businesses.

That is bad news for these monopolies as they seek investor backing to spend hundreds of billions of dollars on artificial intelligence development.

Chip-maker Nividia has been particularly badly hit in the stock market as the DeepSeek advance means that fewer of its products will be needed if the Chinese technology becomes the industry standard.

There is a wider lesson, however. The days are gone when Chinese economic advance largely relied on technical innovations developed elsewhere.

DeepSeek founder Liang Wenfeng explains: “For many years, Chinese companies are used to others doing technological innovation, while we focused on application monetisation — but this isn’t inevitable.

“In this wave, our starting point is not the opportunity to make a quick profit, but rather to reach the technical frontier and drive the development of the entire ecosystem … We believe that as the economy develops, China should gradually become a contributor instead of free-riding.”

This has been compared to the “Sputnik moment” in 1957 when the Soviet Union launched the first satellite to orbit the Earth.

However, the technical advances in Soviet science which made it a world leader in humanity’s advance into space never became pervasive in the wider economy, which continued to the end to lag the developed capitalist countries in most decisive measures of productivity.

Today, the challenge to US hegemony is more serious still. Artificial intelligence has the potential to make an even more profound impact on human life than space exploration did.

And the Chinese economy is powering ahead at a sustained rate of growth which has seen it all but draw level with the United States in gross domestic product, even if it still lags on a per capita basis.

It is likely that what one part of the Chinese economy achieves today will become the norm throughout its industry within a few years, given the capacity of the state to manage development on its own terms, combining market incentives with socialist planning and regulation.

It is therefore unsurprising that President Donald Trump has called the DeepSeek development a “wake-up call.” In its international policy, his administration is going to be defined by great power competition.

China is his number one target, since its growing economic and political influence in the world is the main challenge to the decaying US-dominated world order.

US firms will now of course respond by trying to embrace DeepSeek’s chip-efficient methods as their own. Despite all the talk of deregulation and market control, state-driven security concerns will drive Washington’s response, as they did over Sputnik.

Naturally, broader concerns over the control and development of AI, and the need to manage its impact on labour above all, remain whoever is leading its growth.

But there is no doubt that this week’s events are a landmark in the decline of US hegemony, and in the development of global multipolarity. With all its contradictions and contestations, that can only be welcome.

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