As people oscillate between the crypto world and the AI circle, this repetitive process reminds one of what Keynes said: speculators do not care who is the most beautiful, only who will be chosen in the beauty contest.
Written by Zhou Yixiao
Source: Silicon Star Pro
After Trump won the US presidential election, the market expects him to relax regulations on Cryptocurrency. Trump has previously stated that he will centralize BTC mining in the United States, but this policy may have an impact on the AI industry. In the early morning of November 23rd, the price of BTC reached 99,660 US dollars, once again hitting a new all-time high, approaching the $100,000 mark.
Because BTCMining and AI training both require a large amount of energy and computing power. The synchronous development of the two will inevitably generate competition in terms of electricity and hardware resources. This means that the AI training business may be affected by the fluctuation of BTC prices, especially when miners compete for limited hardware resources. In other words, a pump in BTC prices may drive up the cost of AI training.
AI VS BTC
With the huge success of ChatGPT, AI companies are competing to train and run their own models, hoping to surpass OpenAI’s flagship product. This has created a lot of demand: the inference process of AI models is much more complex than the indexing and retrieval process of search engines, and the energy consumed by a single ChatGPT query is about ten times that of Google search.
This has led AI companies to urgently seek cheap energy and large tracts of land to accommodate related equipment. In North America, some areas have implemented queuing systems, waiting for large data centers to connect to the power grid. However, once a company obtains preliminary approval, building a data center from scratch may take several years, cost millions of dollars, and require a lengthy process of regulatory and administrative approvals.
Internationally, large-scale BTC Mining has always been an extremely profitable business. However, it is also heavily impacted by the Fluctuation in the Crypto Assets market. After the market crash of Cryptocurrency in 2022, many Miners were forced to go bankrupt or shut down completely.
In 2023 and early 2024, mining companies that survived the market downturn reaped profits. However, this year’s BTCHalving (Miner’s reward halving) did not trigger a drastic pump in BTC price as it did in previous cryptocurrency cycles to offset the impact of reduced rewards. Since April this year, the long-term sideways movement of BTC price has compressed the profit space for miners, forcing some miners to seek diversified business models to hedge the risk of cryptocurrency price fluctuations.
Four years ago, when the data center and BTCMining company IREN considered venturing into AI training, they thought that from a business perspective, the business volume at that time was not enough. But now, more and more large BTCMining companies have begun to replace some mining equipment with equipment used to run and train AI systems. These companies believe that providing Computing Power for AI companies may result in a safer and more stable source of income than mining.
Nowadays, the cooperation between artificial intelligence and the BTC mining industry is natural. The two sides have complementary needs. AI companies need the existing venues, access to cheap energy, and infrastructure of BTC miners. BTC miners, on the other hand, pursue stable income brought by AI business and the potential profits brought by the current AI boom.
Some BTCMining companies choose to lease their facilities to AI customers. In June of this year, Core Scientific, a BTCMining company on the brink of bankruptcy in 2022, announced that it will host over 200 megawatts of GPUs for AI startup CoreWeave. Core Scientific stated that the AI company has started purchasing Mining Farms at prices higher than the Mining market, referring to BTCMining facilities as the ‘power shells’ of the data center industry.
Some BTC mining companies operate their own GPUs. BTC mining company Hut 8 received a $150 million investment from Coatue Management to build artificial intelligence infrastructure. In some facilities of the Australia-based mining company IREN, GPUs for AI and ASIC devices for BTC mining share the same space. BTC brings immediate income, but its volatility is high. AI relies on clients and is more stable once clients are acquired. Nasdaq-listed company Bit Deer is also building its own AI data center in Singapore.
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A business that looks very beautiful
However, only a few overseas mining companies can achieve this transformation. Secondly, the equipment used to mine BTC is called ASIC, which is an abbreviation for Application-Specific Integrated Circuit. ‘Specific’ means it cannot be used for other tasks. Mining companies cannot seamlessly connect mining equipment to AI scenarios.
An AI Infra practitioner told Silicon Star, ‘For example, H100 is commonly used for training models, while Mining will use 4090.’
In other words, to serve the AI industry, BTCMiner must purchase new equipment, and the requirements for artificial intelligence and BTCMining data centers are different. Entering a completely new and highly complex industry is already very difficult, not to mention competing with well-funded tech giants like Google, Amazon, Microsoft, and others.
So, not all mining companies can replicate the high-value collaboration between Core Scientific and CoreWeave. Especially for small-scale miners, they actually don’t have much resources to offer to the AI industry.
Virtual Money Mining has been banned in China. However, some companies from other industries want to take a share of the AI trend. They either directly enter the field or set up Computing Power subsidiaries to engage in the business of ‘Computing Power leasing’. According to statistics, there are more than 100 A-share listed companies related to Computing Power leasing, including ‘lottery printing king’ Hongbo shares, ‘MSG king’ Lianhua Holdings, and others. On video platforms, there are even contents like ‘tearing down a house and setting up a trap, buying 800 graphics cards, and partnering with old middle school classmates to do Computing Power leasing’.
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In an ideal state, the business model of Computing Power leasing only requires initial investment in GPU server equipment, hosting the hardware in a professional smart computing center, and then leasing Computing Power to end users, with hardware maintenance and software services being handled by the smart computing center.
However, in reality, this may not be a good business. The demand for Computing Power leasing comes from the development of the AI large model industry, while the cost of leasing high-end hardware for training AI is rapidly falling. Eugene Cheah, CEO of Featherless.Ai, pointed out that the overseas H100 leasing price once reached as high as $8 per hour, but now it has fallen to below $2 per hour. This is mainly because some companies signed Computing Power leasing contracts early on, and in order to avoid waste of idle capacity, they began to resell the reserved computing resources. Most of the market chooses the Open Source model, resulting in a decrease in demand for new models.
The domestic Computing Power leasing market is also experiencing a similar phenomenon of ‘Computing Power surplus’, but ‘the leasing market is unlikely to lower prices because they were bought at high prices in the early stages,’ a practitioner in the smart computing industry told Silicon Valley Star.
“It’s still fast”
There is a saying in the crypto world, ‘computing is power’, Computing Power is power, and this phrase has now spread to the AI circle.
Behind Computing Power is energy, and there is a close relationship between developed countries and high energy consumption. This can be seen in the comparison chart of per capita electricity generation (in kilowatt-hours, kWh). In other words, having surplus energy is a necessary condition for the manifestation of civilization progress. After all, on top of the basic survival level like agriculture, there are new layers such as manufacturing, transportation, public services, urbanization, and computing, all of which require energy support.
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In this dimension, the infrastructure originally established to serve the Cryptocurrency is providing solutions for the Computing Power needs of the AI era. This is undoubtedly an opportunity for the overseas Digital Money Mining industry, which has always wanted to get rid of speculation, to prove its own value. As long as this trend continues, leading vendors will benefit from the enthusiasm and Liquidity brought by AI.
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In every wave of technological innovation, there will always be a ‘gold rush’. For speculators, what they are always chasing is the profit itself, whether the target is Digital Money, artificial intelligence, or tulips from three hundred years ago, it seems not to be important.
After the Bitcoin Halving, some miners are facing a dilemma: either continue Coin Hoarding and Mining, hoping for a pump in BTC price, or transition to running AI data centers, hoping to catch the fast train of artificial intelligence and make a quick profit. Now that the coin price has reached a new all-time high, some people are starting to sigh again: ‘It’s still too fast.’ But there is a saying in the crypto world, ‘It’s harder to hoard coins than to hoard widows.’
When people oscillate between the crypto world and the AI circle, the repeated process reminds one of Keynes’s saying: speculators do not care about who is the most beautiful, only who will be chosen in the beauty contest.
And this “beauty pageant” will continue indefinitely.
