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24 May 2026, 20:01

Keyrock Report: 76% of AI Agent Transactions Fall Below Visa’s $0.30 Fee Floor

A new report from Keyrock, a global crypto investment group leading in market making, asset management, OTC, and options trading for digital assets, finds that artificial intelligence (AI) agents have settled more than $73 million across approximately 176 million transactions since May 2025, while four competing payment architectures have taken shape, backed by some of

24 May 2026, 20:00

Mapping Ethereum’s road ahead as leverage builds beneath weak spot demand

Ethereum recovery weakened as hidden sell pressure and macro tightening limited stronger breakout momentum.

24 May 2026, 19:52

Vitalik Buterin confirms ETH Foundation holds just 0.16 percent

🟣 Vitalik Buterin discloses Ethereum Foundation now holds just 0.16 percent of total ETH. He confirms his influence is intentionally decreasing as governance expands. Continue Reading: Vitalik Buterin confirms ETH Foundation holds just 0.16 percent The post Vitalik Buterin confirms ETH Foundation holds just 0.16 percent appeared first on COINTURK NEWS .

24 May 2026, 19:50

China’s AI trade is holding up even as the wider economy stays weak

China is giving investors a weird but very clear setup right now. The economy looks soft, shoppers are not spending with much force, and April retail sales grew at the slowest pace since the post-COVID reopening. Yet the stock trade is not really about malls, restaurants, or hospital names. It is about AI, semiconductors, hard tech, software, cloud capacity, and the companies sitting close to Beijing’s self-sufficiency push. Investors keep buying China’s AI supply chain while the wider economy stays uneven Modern alpha manager WisdomTree’s Liqian Ren thinks the technology growth story will continue as well. While she said that many companies in the AI ecosystem continue earning good profits, she clearly warned that such companies do not have sufficient scale to turn the entire economy around. “It’s very, very uneven,” she stressed. While many hardware manufacturers trade A-shares on the exchanges of mainland China, not Hong Kong, this is important considering that mainland stocks have outperformed this year. The Chinese CSI 300 index, which includes large firms trading in Shanghai and Shenzhen, has gained almost 5% this year while the Hang Seng index in Hong Kong is nearly unchanged. Large private firms are not accessible to stock investors. Private firms like ByteDance and Huawei are not publicly listed. However, many Chinese chip producers, artificial intelligence model developers, and high-tech components makers have gone public recently. Leonid Mironov’s fund holds Tencent Holdings (0700.HK, TCEHY) and Alibaba Group (BABA, 9988.HK) as its largest positions. He also owns hardware names such as Anji Microelectronics (688019.SS) in Shanghai. Leonid said investors still miss how much policy support has helped smaller and mid-sized firms make money. “I think people don’t really see and appreciate how fundamentally beneficial the policy has been to the bottom line of these smaller and mid-cap names,” he said. He is not buying every AI model story, though. Leonid said he is still waiting on Zhipu and MiniMax because he wants clearer proof that customers will stay and that the business model can hold up. Morgan Stanley (MS) is taking the other side. The bank is overweight on Zhipu, MiniMax, and Alibaba. It also has an overweight rating on Cambricon Technologies (688256.SS) with a 2,000 yuan price target, or about $294. DeepSeek cuts V4 Pro pricing and puts China’s AI cost trade against OpenAI and Anthropic Finally, an aspect that plays a significant role in telling the China AI story is pricing. DeepSeek, a Hangzhou startup, has maintained the 75% discount on its V4 Pro for one month after launching its V4 series. The V4 series comprises both V4 Pro and lightweight V4 Flash. By doing so, DeepSeek places itself in the middle of global competition over cost. According to Artificial Analysis, which is a third-party benchmark firm, V4 Pro ranks top globally considering intelligence per dollar cost. In other words, this ranking depends not only on intelligence but also on the amount of output that buyers receive from the model. The latter factor is especially relevant since powerful computation is constrained, while running large AI models is costly. The official API price of DeepSeek’s V4 Pro model ranges from as low as $0.0036 per 1 million cached input tokens and $0.87 per 1 million output tokens. According to Artificial Analysis, the cost of running the Intelligence Index benchmark on this model amounts to about $268. Meanwhile, the cost to do the same thing on OpenAI’s GPT-5.5 and Anthropic’s Claude Opus 4.7 models would be 12 and 19 times higher, respectively. This is relevant for all software developers, exchange houses, trading houses, and AI tool developers. The output cost may be a small issue considering the cost that will be added up from tokens. Third-party tests are significant because not all AI businesses use the same pricing or scores for their AI models. DeepSeek is not the only Chinese name on the list for costs per unit of intelligence. The M2.7 model of MiniMax and the MiMo V2.5 Pro of Xiaomi make the list. Don’t just read crypto news. Understand it. Subscribe to our newsletter. It's free .

24 May 2026, 19:10

OpenAI and Anthropic now sit at the center of Big Tech’s AI cloud backlog

The AI boom now has one very ugly question hanging over it. Is the money real, or are Big Tech companies just feeding cash to AI startups and booking the same cash as cloud sales later? That question now sits right on top of OpenAI and Anthropic, because fresh filings show both companies are tied to more than half of the almost $2 trillion in future cloud revenue sitting on the books of Microsoft ( MSFT ), Oracle (ORCL), Alphabet ( GOOGL ), and Amazon (AMZN). It sounds too good to be true, and yes, it is wild. A tech giant invests billions in an AI firm through some financing agreement, and in that agreement, the AI firm is advised to deploy its funds on purchasing cloud infrastructure owned by the same tech giant. And so, the AI firm receives funding, the cloud firm makes income, and Wall Street enjoys looking at some impressive figures. The money does not get very far, however. It goes out through one door and returns through another door in the guise of a new customer. Microsoft books OpenAI cloud spending after funding the same customer Microsoft’s OpenAI collaboration serves as an illustrative example. Microsoft spent close to $13 billion on funding OpenAI; however, this investment was not limited to cash contributions only. The majority of that investment consisted of Azure credits, which OpenAI used to develop and execute its AI models using Microsoft infrastructure. The usage of the Microsoft servers by OpenAI generated revenues for Microsoft. As a result, Microsoft contributed financially to OpenAI’s activities, OpenAI used Microsoft resources to execute them, and Microsoft recognized that contribution as demand from its customers. OpenAI’s cloud bill has now climbed above $60 billion a year. Its revenue is around $25 billion. That means its server costs are more than double what it brings in. For a normal company, that would look like a giant red flag. In AI land, it gets treated like growth. Anthropic is running a similar play with Amazon. The company spent about $2.66 billion on Amazon Web Services in nine months. That was roughly the same size as its revenue at the time. So the money coming in was almost matched by the money going straight back out to AWS. That is where the second part of the scam plays out. With more money flowing into Anthropic or OpenAI at a higher valuation, the technology giants that have invested in them can inflate the value of their stakes to make money without having sold any goods or collected any cash. A gain has been made. Google’s parent company, Alphabet, earned $62.6 billion in the first quarter of 2026. $28.7 billion was attributed to Google’s gains in relation to its stake in Anthropic. Amazon posted $30.3 billion in earnings in the first quarter of 2026. Its Anthropic gains accounted for $16.8 billion of it. Amazon burns real cash while AI paper gains lift reported profit However, Amazon’s cash metrics appeared to be in a more difficult position. Free cash flow fell by 95% to $1.2 billion, and the company also invested $44.2 billion into physical data centers. This clearly demonstrates the difference between accounting profits and real cash. One sits in spreadsheets, while the latter builds real-life data centers using land, semiconductors, electricity, cooling, connections, buildings, and personnel. This could lead to concentration risks for both companies. In particular, Microsoft has 49% of its $627 billion future backlog dependent on OpenAI. On its part, Oracle has 54% of its $553 billion future pipeline dependent on OpenAI alone. This all looks eerily familiar to something straight out of the dot-com era. Back in 2001, when Global Crossing and Qwest Communications traded equal fiber network capacity and recorded such swaps as sales. As a result, Qwest lost $1.4 billion in fraudulent revenue. Meanwhile, Global Crossing filed for bankruptcy. The only thing that separates both cases today is the fact that such swaps by telecommunications companies were not considered legal at that time, while today’s AI cloud loop easily fits in today’s accounting rules. According to the Kobeissi Letter, the ten largest American stocks constitute 41% of the S&P 500. Among these stocks, we find Magnificent Seven, including Apple and Tesla. This percentage is 14 points above the previous dot-com peak in 2000. “This means about 41 cents of every dollar invested in the S&P 500 flows directly into shares of just 10 firms,” The Kobeissi Letter wrote . “Roughly 35 cents of every dollar flows specifically into the Magnificent 7 group. All while nearly 50 cents of every dollar is now going into AI-linked stocks. Mega-cap tech is all that matters right now.” Don’t just read crypto news. Understand it. Subscribe to our newsletter. It's free .

24 May 2026, 19:07

US and China pour record capital into AI as funding race intensifies on both sides

The artificial intelligence sectors in both the United States and China are being flooded with unprecedented capital. However, the AI funding is now becoming a competition between the two largest economies. Global AI startups raised $255.5 billion in Q1 2026 alone. Meanwhile, Chinese AI ventures separately pulled in over 110 billion yuan ($16.2 billion). How is the Chinese government fueling the AI boom? Pan Xiaodong, the secretary general of the Ministry of Science and Technology, made some huge announcements at a Beijing press conference back in February. He mentioned that the Chinese government had launched a national venture capital guidance fund. It focuses on early-stage, small, long-term, and hard-tech enterprises. This includes AI, semiconductors, and advanced manufacturing. The estimated total scale of the fund is around 1 trillion yuan ($144.45 billion). Investors linked to the Chinese government reportedly participated in more than 140 AI deals in 2025. It is a huge jump compared to the 10 deals per year seen before 2018. The authority has also joined hands with financial institutions and local governments. This is done to establish various funds totaling over 350 billion yuan. This includes tech-industry integration funds and secondary market funds. DeepSeek will reportedly have its first outside investment round led by China’s Integrated Circuit Industry Investment Fund (the “Big Fund”). The AI company came into the light for its cost-efficient models. The startup’s valuation surged from $10 billion to $20 billion in April. It later reached an estimated $45-$50 billion by early May. Other investment rounds backed by the government include Moore Threads, a Beijing-based GPU designer, which raised $720 million at a $4.1 billion valuation in February 2025. Moonshot AI secured $700 million at a $10 billion valuation in January 2026, while StepFun reportedly raised $717 million. Linkerbot, a robotic-hand startup, is targeting a $6 billion valuation backed by Ant Group and Bank of China Asset Management, while Unitree Robotics has filed for a Shanghai listing seeking up to $7 billion. The US and China are protecting their industries from outside influence Washington banned American investors from backing Chinese AI and chip companies back in January 2025. In late April, China applied its own version of the same restriction. The National Development and Reform Commission instructed Moonshot AI, StepFun, and ByteDance not to accept US capital without explicit government clearance after Meta acquired Manus for $2 billion. Cryptopolitan previously reported that the Trump administration accused Chinese labs of “industrial-scale” distillation of American AI models. Distillation is a method where a developer uses data from a larger AI model to train a smaller one. The White House memo outlined four measures to stop this, including sharing intelligence on distillation tactics and coordinating defenses with US AI companies. Anthropic also previously accused DeepSeek, Moonshot AI, and MiniMax of exploiting its models. Despite the tensions, the total deal activity for the Chinese private equity market reached 2,568 transactions worth 234.4 billion yuan in Q1 2026, and foreign-currency deals in China more than doubled year-on-year to 210 in the same period. The disclosed investment value jumped by 495% to 67.3 billion yuan ($9.9 billion). In the US, investments from the first quarter of 2026 surpassed the $254.4 billion deployed across all of 2025. OpenAI, Anthropic, and xAI accounted for more than two-thirds of the total. Despite the differences in the US and Chinese governments’ approaches, they are both producing results. Chinese large-model companies have shortened iteration cycles to under three months by 2026, and a Stanford University report suggested that the performance gap between top US and Chinese AI models has “effectively closed.” Don’t just read crypto news. Understand it. Subscribe to our newsletter. It's free .