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Record gold prices leave West scrambling

America's central bankers are playing catch-up. Credit: Getty

America's central bankers are playing catch-up. Credit: Getty

August 21 2024 - 10:30am

Gold prices hit a new record high yesterday afternoon, with its spot price of $2,531.60 (£1,943.83) an ounce up 1% on the day. This means that a standard bar of gold — weighing in at 400 troy ounces (12.4kg) — is now worth more than $1 million. While this is a somewhat arbitrary milestone, it reflects very deep changes in the gold market.

In the early Seventies, when the US dollar was taken off the gold standard, the precious metal was trading at just over $100 an ounce. At the end of that decade and the beginning of the next, amid soaring inflation, there was a spike in the price of gold, which reached over $820 an ounce in late 1980. While the price came down shortly after this, it remained above its Seventies levels, hovering around $300-$400 until the mid-2000s.

It was after the 2008 financial crisis, when central banks turned to quantitative easing (QE), that gold prices began to rally in earnest. Gold first broke the $1,800-an-ounce mark towards the end of 2011 when the Eurozone was experiencing a sovereign debt crisis and the QE programs were in full swing. In the post-2008 world, gold became anchored to inflation expectations, tracking yields on inflation-protected Treasuries (TIPS). Gold prices in the period reflected where investors thought inflation was headed.

But the recent explosion in gold prices appears to have little to do with inflation forecasting. Indeed, we first saw a run-up in the gold price as inflation was rising and now the value continues to increase even though inflation is widely thought to be falling and central banks are considering easing. This suggests that gold has become untethered to inflation expectations, and that something or someone else is driving the price.

That something or someone appears to be central banks, which are buying gold at a record pace. The main buyers are the Chinese, Indian and Turkish central banks, yet Russia anticipated this trend a decade ago. Moscow went through two phases of buying gold, first in the wake of the 2008 financial crisis. In the first quarter of that year, the Russian central bank held around 457 tonnes of gold; by 2014, this had risen to 1,040 tonnes.

But it was after the 2014 annexation of Crimea, which precipitated the first wave of sanctions on the country, that Russian gold-buying really started. By the first quarter of 2020, Russian gold reserves had risen to 2,300 tonnes; having purchased around 97 tonnes a year in its initial phase of gold buying, in its second the country was buying around 210 tonnes a year.

It was the second round of Russian sanctions, imposed in early 2022 in response to the invasion of Ukraine, that spurred other central banks to get in on the action. These sanctions, which included the freezing of Russian foreign exchange reserves, awakened other countries to the fact that the US dollar could be weaponized against foreign nations. The ensuing scramble has involved other central banks trying to catch up with Russia to diversify their reserves through gold purchases, creating windfall gains for Moscow. Russia’s 2,300-tonne gold reserve was worth around $136 billion in 2020 — and cost far less to buy — but today it is worth around $184 billion.

How much higher can the gold price go? These central banks appear to be price-insensitive buyers: they are not buying the metal because they think it is cheap. Instead, they are buying it because they feel they need it, and the price increases we are witnessing haven’t deterred them. This means that, in theory at least, the price can continue to rise until these central banks have satiated their appetite for gold.


Philip Pilkington is a macroeconomist and investment professional, and the author of The Reformation in Economics

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China is threatening America in the AI race

Reports sugget Zhipu AI  has released a new model that can rival leading US systems. Credit: Getty

Reports sugget Zhipu AI has released a new model that can rival leading US systems. Credit: Getty

July 1 2026 - 10:18am

China is trying to catch up with America on artificial intelligence. The Wall Street Journal has reported that Zhipu AI — one of China’s six “AI tiger” LLMs — has released a new model that can rival leading US systems, including Anthropic’s Mythos, in cybersecurity tasks such as pinpointing security bugs. While this marks a milestone in China’s drive to catch up with Western AI capabilities, strong performance on a single benchmark does not mean it has taken the lead. Chinese models still lag behind their Western counterparts in broader capabilities, such as autonomous operation. Skepticism is therefore warranted before resorting to hysterical conclusions, but complacency about the geopolitical implications of China’s AI advances would be an even greater mistake.

On the infrastructure side, Chinese AI is still constrained by access to advanced chips, with American labs way ahead in computing capacity as well as investment. Analysis from earlier this year suggests that Chinese models are likely to be at least a few months behind those in the US. But they are still continuing to make progress, or that the geopolitical importance of AI will be decided only by whose LLM has ventured deeper into the technological frontier. The practical applications of AI, countries’ to capture foreign markets, and the application of AI into the real economy will matter just as much.

Here, China may hold an advantage. As with its dominance across many critical supply chains, Beijing may not need to produce the most advanced AI systems — only those that are affordable and widely deployable. In doing so, it could consolidate global influence by supplying functional, low-cost AI at scale.

Beijing seems to be pursuing exactly that path, developing an AI “open-source” strategy that offers affordable, widely available AI models for companies and individuals to use and modify as they wish. The production of the DeepSeek AI model, which matched the performance of Silicon Valley tools such as ChatGPT at a fraction of the cost for users, created goodwill among Chinese models with developers.

The four most popular models on OpenRouter, an AI hardware platform for developers, are now all Chinese. The goal for China is not only to win the frontier-model race, but to make its systems the default layer of AI adoption across industries and global markets. For most economies, the choice is increasingly between an affordable tool they can deploy now and a more robust one that may be out of reach.

And while the countries adopting Chinese models may be exposed to political pressure and cyber threats from Beijing, safer and more capable alternatives matter little if they are unaffordable. American AI companies are already under pressure to monetize products whose operating costs are rising. If Chinese open-source models become the cheap default for startups, universities, governments and businesses across the developing world, then America’s AI lead will be eroded from below.

Perhaps more concerning for America in the long run is how AI can give Chinese manufacturing even more strength, through the ongoing integration of AI as a general-purpose technology. China’s new Five-Year Plan mentioned AI more than 50 times and includes an “AI+” action plan aimed at spreading AI across the economy.

Beijing has been pioneering automation of its critical infrastructure for years, with promising recent results in increasing warplane production capacity. In that regard, China’s open-model strategy and manufacturing dominance will reinforce each other. Cheap, adaptable models accelerate deployment across the real economy while those deployments generate real-world data and use cases that can feed back into further model improvement.

The United States should not dismiss the importance of its lead in the AI race. That lead worries Beijing, not least because a more automated Chinese economy would also become more vulnerable to AI-generated cyber threats. But nor should Washington assume that China cannot catch up with American capabilities over time.

This AI competition represents part of a broader struggle over tech supply chains and geopolitical influence. Decisions over whether to adopt US or Chinese models could produce a more fragmented global reality, with different regions relying on different cloud providers, chips and security structures. The result will likely be a global economy which is divided into competing spheres, rather than one which produces a single winner.


Miquel Vila is a political and geopolitical risk consultant focusing on industrial strategy, critical infrastructure and global supply chains.

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