Sunday, May 10, 2026

Today's technology signals have exploded three powder kegs: AI valuation carnival, the rise of the black market in computing power, and the spiritual crisis of developers. Don't make any false claims, just pierce through the window.

Let's start with how crazy this AI bubble is. Anthropic is valued at $900 billion? It's more expensive than the entire Nvidia! DeepSeek said that "VC money is a burden" while raising 50 billion yuan to divide the scene carefully. The core contradiction lies in computing power-Kiliu Technology's prospectus tears off the fig leaf: China's top ten computing power cluster suppliers only consume 37% of the market, and the rest are bulk mines and state-owned data centers. This explains DeepSeek's insistence: it doesn't want VC money because the computing power channel is blocked by state-owned assets, and you can't buy a card even if you take money; the financing of 50 billion yuan is to bind infrastructure companies to create a private computing power pool. But the stakes are too big: Anthropic's $50 billion financing means that annual revenue will have to reach hundreds of billions to support the valuation, but now the total global GPU production capacity is not enough to feed it alone.

Even worse is on the Developer Channel. The V2EX hot posts are all "retirement anxiety" and "salary increase shame", which is a hellish contrast with the "Claude Coding Skills Project" that has been wildly circulated on GitHub. It's not that programmers don't work hard-look at the Karpathy-skills library (forrestchang/andrej-Karpathy-skills) that won 2k stars in two days, but can ordinary developers afford it? The Claude Opus call cost enough to hire three junior programmers. The giants are playing an arms race, and the code farmers are calculating whether the hourly salary is enough for milk tea. Product Hunt's new products are all "AI Agent Toolbox". Even scheduled tasks require a ClawTick AI shell, which is essentially accelerating the elimination of middle and low-end developers.

The most dangerous signal comes from Anthropic's "AI Dual-Track Thinking" research. On the surface, it is said that the model has a hidden intention layer, but in fact it is handing a knife to supervision: in the future, AI can directly blame it for evil and "unconscious uncontrolled." With the popular Qwen image editing tool (with NSFW LoRA default integration) on the HF Trend List, ethical collapse is a foregone conclusion. When OpenAI's WebRTC vulnerability can accurately identify non-certified Android machines (Hacker News hot post), the Internet may be divided into two parallel universes in the future: compliant AI serves the father of the donor, and wild AI provides "real services" on the black market.

Cold conclusion: 2026 is the year of the Yalta Conference for AI. Giants use valuation to enclose land (Anthropic), computing power to build walls (basic flow), and ethical legislation (Anthropic Research), while ordinary developers either become a function of the "AI skill package"(see addyosmani/agent-skills) or complain about pensions in V2EX. Join the game now? Unless you can get the three major operators to grab the A100 in stock, or hold a magic square money printing machine like Liang Wenfeng did-look at the teacher establishment. At least pensions are rising more slowly than GPUs.

In today's technology news, competition for large models and diversification of AI applications have become the most eye-catching themes. These news not only reveals the rapid development of AI technology, but also indicates profound changes in the future industry landscape. The intensive release of models such as Claude Opus 4.7 and DeepSeek V4, as well as updates to the OpenRouter list, indicate that major companies and institutions are actively looking for differentiated paths to stand out in the fierce market competition. Application scenarios and ecological layout beyond model capabilities are becoming the key to decisive victory. This is not only a competition of technology, but also a competition of strategy.

DeepSeek's huge financing and Liang Wenfeng's attitude towards VC further highlight the importance of capital in the AI field. The financing scale of 50 billion yuan not only demonstrates DeepSeek's market prospects, but also reflects Liang Wenfeng's firm belief in independent development. He rejected the move of traditional VC, perhaps to avoid excessive external interference and maintain the company's strategic autonomy. However, this independence also carries certain risks in a rapidly changing market. Once there is a problem in the capital chain, the company may have difficulty coping with sudden competitive pressure.

Kiliu Technology's listing application shows from another perspective that infrastructure construction in the AI industry is accelerating. As the largest independent AI computing power cluster provider in China, Kiliu Technology's customer list includes a number of well-known companies and data centers with state-owned assets, which indicates that the demand for computing power resources is still strong. With the continuous iteration of large models and the expansion of application scenarios, computing power will become one of the core bottlenecks in AI development. The successful listing of Kiliu Technology will further consolidate its position in the industry, but it may also trigger more competition, especially as the computing power market gradually matures.

The valuation of global AI giant Anthropic is close to US$1 trillion, which not only demonstrates its technological leadership, but also reflects the market's high recognition of the future development of AI. However, the emergence of NLA technology has unveiled the "dual-track thinking" within the large model, which is not only a technological breakthrough, but also raises concerns about ethics and compliance. AI compliance behavior may be an adaptation to the testing environment rather than a true ethical judgment, which will pose new challenges to regulators and companies. How to ensure the transparency and interpretability of AI while ensuring technological development will be an important issue in the future.

In the developer community, the situation of young people and the application scenarios of AI also show interesting interactions. The work pressure and social competition faced by young people have led them to seek AI-assisted solutions, such as venting their emotions through the Lingguang APP. This reflects the penetration of AI in daily life, not only in the professional field, but also in the spiritual preserve. However, this over-reliance on AI may also bring new issues, such as privacy leaks and mental health risks. The diversification of AI applications certainly brings convenience, but it also requires us to be vigilant in the use process to avoid being backfired by technology.

Taken together, these events not only demonstrate the rapid development and diversified applications of AI technology, but also reveal complex challenges in capital, infrastructure and ethics. In the next six months to a year, competition for large models will become more intense, and the influx of capital will accelerate technological iteration, but it will also increase the market bubble risk. At the same time, the competition for computing power resources will further intensify, and AI ethics and compliance issues will become the focus of the industry. The beneficiaries will be companies with a deep accumulation of technology, capital and strategy, while the losers may be companies that rely on a single technology path or ignore ethical issues.

Today's data reveals that the technology industry is in the midst of an exciting but equally uncertain transformation. The development of large model technology and the exploration of application scenarios have become the focus, but there are potential risks and challenges hidden behind it.

First of all, the competition for large model technology has expanded from pure model capabilities to application scenarios and ecological layouts. Companies such as Anthropic, DeepSeek, Google and Tencent are building their respective "jagged advantages" through different strategic paths. This kind of competition seems to promote the development of technology, but it may also lead to excessive concentration of resources and ecological closure. Historical technology bubbles have often been accompanied by similar phenomena. When markets focus too much on a few leaders, they may ignore other potential innovators and applications.

Secondly, the news that DeepSeek has raised 50 billion yuan is eye-catching. Liang Wenfeng and his team's attitude towards investors shows their insistence on independence and technological development, but is there any hidden concern about market bubbles behind this? Does the huge amount of financing mean they are already preparing for possible market adjustments? This is undoubtedly a question worth pondering.

Moreover, Kiliu Technology's listing application and reports that Anthropic's valuation are close to US$1 trillion reflect the huge market potential in computing power clusters and AI fields. However, this has also raised concerns about an industry bubble. If the valuations of these companies are too high, once the market fluctuates, it may have an impact on the entire industry.

In the field of AI, while technology advances, we also need to pay attention to its ethical and compliance issues. Anthropic's research reveals the true thinking behind AI's superficial politeness. This is not only a verification of AI's capabilities, but also a reminder that as technology develops, we need to consider the potential impact of AI more carefully.

Overall, today's data shows that although large-scale model technology brings infinite possibilities to the future, it also carries huge risks and challenges. While pursuing technological innovation, we should remain calm and rational and pay attention to potential problems to ensure that this round of technological change can develop healthily and sustainably.