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Poland, Turkey, And India Lead Global Gold Purchases In 2024

Poland’s central bank has continued its strategy of increasing its gold reserves, which reached 450 tonnes in 2024, placing it 13th globally in terms of stock size. Gold now makes up 17% of Poland’s foreign exchange reserves, which total over $220 billion, according to data from the World Gold Council.

The Polish central bank has been the largest net buyer of gold in 2024, acquiring 90 tonnes, followed by Turkey (75 tonnes) and India (73 tonnes). This move aligns with a broader trend of countries strengthening their financial positions through gold, which is seen as a safeguard against economic instability.

Poland plans to increase the proportion of gold in its reserves to 20%, which could elevate the country to 11th place in the global rankings, approaching the European Central Bank’s gold reserves of around 506 tonnes.

Globally, central banks hold over 30,000 tonnes of gold, with the largest reserves held by the United States (8,100 tonnes), followed by Germany, Italy, France, Russia, and China. As Poland continues to build its gold stockpile, it is positioning itself as a key player in the global financial landscape, with the value of gold providing a solid financial foundation in times of economic uncertainty.

The AI Agent Revolution: Can the Industry Handle the Compute Surge?

As AI agents evolve from simple chatbots into complex, autonomous assistants, the tech industry faces a new challenge: Is there enough computing power to support them? With AI agents poised to become integral in various industries, computational demands are rising rapidly.

A recent Barclays report forecasts that the AI industry can support between 1.5 billion and 22 billion AI agents, potentially revolutionizing white-collar work. However, the increase in AI’s capabilities comes at a cost. AI agents, unlike chatbots, generate significantly more tokens—up to 25 times more per query—requiring far greater computing power.

Tokens, the fundamental units of generative AI, represent fragmented parts of language to simplify processing. This increase in token generation is linked to reasoning models, like OpenAI’s o1 and DeepSeek’s R1, which break tasks into smaller, manageable chunks. As AI agents process more complex tasks, the tokens multiply, driving up the demand for AI chips and computational capacity.

Barclays analysts caution that while the current infrastructure can handle a significant volume of agents, the rise of these “super agents” might outpace available resources, requiring additional chips and servers to meet demand. OpenAI’s ChatGPT Pro, for example, generates around 9.4 million tokens annually per subscriber, highlighting just how computationally expensive these reasoning models can be.

In essence, the tech industry is at a critical juncture. While AI agents show immense potential, their expansion could strain the limits of current computing infrastructure. The question is, can the industry keep up with the demand?

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