As Anthropic raises the "AI slowdown theory," AI commercialization is actually accelerating! From model R&D to financial advisors, the AI agent dividend is being realized at an accelerating pace.

Title context: As Anthropic raises the "AI slowdown theory," AI commercialization is actually accelerating! From model R&D to financial advisors, the AI agent dividend is being realized at an accelerating pace. Text: Anthropic, the strongest leader in global AI applications, saw its CEO say just last weekend that "the development of AI large models/AI technology should slow down," and immediately afterward, reports emerged that the next-generation god-tier model Claude Opus 5.2 had already begun gray-scale testing in Claude Code. The latest news also shows the company is striving to advance the penetration of Anthropic's Claude series AI application tools into various industriesreports indicate Anthropic has launched a new type of Claude AI tool for financial/financial advisor use aimed at Wall Street financial giants such as BlackRock. These developments collectively highlight that Anthropic is simultaneously advancing frontier AI risk governance and enterprise AI application commercialization, competing with the strongest AI application competitors such as OpenAI in AI monetization. Many AI application developers in the AI open-source ecosystem have discovered that the next-generation "god-tier model"Claude Opus 5.2has already begun gray-scale testing in Claude Code. In addition, some developers on Claude ecosystem platforms, through packet capture and checking request status (/status), found that although the front-end name has not changed, the model slug behind it already clearly points to Opus 5.2. Anthropic is trying to use stronger model capabilities and agent execution mechanisms to push AI from a programming assistance tool to a work system capable of continuously completing complex tasks. In the latest descriptions from global developers about Opus 5.2, the upgrade directions worth noting include response speed, code completion quality, and the ability to continuously execute and repeatedly verify during long tasks. Among them, the most directly commercially valuable change is: after a user delivers a goal, AI can take on more task decomposition, code writing, testing, and repair work, reducing manual repeated prompting and intervention. Regarding Opus 5.2, some developers even said it seems that Recursive Self-Improvement (RSI) has begun to dominate Anthropic's training paradigm, demonstrating a technical path of "stronger models assisting R&D, improved R&D efficiency, and driving progress in next-generation models." The potential significance of RSI is that AI large models tend to be able to simultaneously become products and AI automated R&D tools, extending competition among model companies to the automation of AI laboratory training execution work, infrastructure maintenance, and frontier theoretical research processes for underlying operators. On September 14, shares of "AI chip superpower" Nvidia fell about 3.4%, while the Philadelphia Semiconductor Index unusually dropped about 6%, as the market was pricing in risks brought by factors such as discussions of AI slowdownAnthropic, OpenAI, and other global AI leaders unanimously called over the weekend for slowing the pace of frontier AI large model development. However, Anthropic, which raised the "AI slowdown theory," has recently been going all out to accelerate the monetization path on the AI application side. In addition to the Opus 5.2 gray-scale test, Anthropic also announced on Monday the launch of the Claude AI financial advisor version, connecting data and analytical tools from Wall Street's top financial institutions such as BlackRock, Vanguard, and Charles Schwab to help advisors prepare for client meetings, review portfolios, organize records, and draft communication materials. On the one hand, the company is calling for a slower pace in the development of frontier model capabilities; on the other hand, it is actively advancing frontier AI large model R&D work and pushing the company's AI large models into existing business processes, striving for larger-scale enterprise customers and AI application revenue data. Frontier AI developers call for slowing down, while the application side is competing for monetization The gray-scale testing of new AI large models and the release of brand-new Claude AI application tools are actively proving that although Anthropic calls for slowing down the AI R&D process, it is accelerating the continued advancement of AI application commercialization. Judging from the active AI application product layouts of leading global AI application vendors, AI tools based on the most frontier AI large models are entering business scenarios with specific processes in finance, content creation, healthcare, and scientific research. OpenAI launched ChatGPT for the financial services industry on September 10, designed in cooperation with Morgan Stanley and Evercore, comprehensively and deeply combining the GPT-6 Astra large model, professional financial data, and document generation capabilities, first serving investment banking and equity research; Roblox expanded its AI game creation tool Build on September 11 and announced plans for a standalone app and browser play; Anthropic launched tools for healthcare institutions earlier this year and expanded life sciences functions, supporting insurance prior authorization material processing, scientific research information retrieval, and preparation of regulatory filing materials. These latest AI application trends all show that competition is extending to who can embed models into high-frequency, verifiable workflows that someone is willing to pay for. However, product launch, pilot use, and full commercial deployment are different stages, and for now the number of announcements cannot be directly taken as the industry penetration rate. Recursive self-improvement has undoubtedly become an important R&D direction publicly discussed by the world's most frontier AI laboratories. Anthropic recently disclosed that its engineers' per-capita quarterly code delivery volume reached about 8 times the 20212025 level, while clearly stating that a closed loop capable of fully autonomously designing and developing next-generation models has not yet been achieved, and there is still a clear gap in research goal selection and judgment capabilities. OpenAI's chief scientist also publicly stated that the company is shifting its research focus to RSI. The coverage of AI-assisted R&D work is increasing significantly and may shorten most AI R&D work stages through code generation, experiment execution, and result analysis. The main impact of frontier AI large models such as Anthropic's model currently undergoing gray-scale testing and the newly launched OpenAI Astra on computing power demand focuses on making more complex tasks executable, thereby expanding the potential scope of use, and more paid agent tasks are expected to increase inference demand over the long term. The continuous expansion of enterprise applications can be described as an important source of sustained accelerated growth in computing power demand. A financial advisor task may include reading holdings, retrieving research, running analysis, checking results, and generating client materials, requiring multiple model calls and external tool execution; if more customers and more institutions hand such tasks to agents, cumulative inference volume, concurrent sessions, and tool operation resources may continue to increase substantially; long context, multi-step reasoning, and parallel sub-agents may also increase the resource requirements of complex tasks. In the AI data center computing infrastructure chain, the strong computing resource demand brought by AI agents may accelerate its spread to multiple links including GPU/ASIC, HBM, server DRAM, enterprise-grade SSD, high-speed optical interconnect equipment inside data centers, as well as data center CPUs and the data center power chain. Agent expansion will simultaneously affect computing, memory, storage, and networking. GPUs and other accelerators handle model computation, high-bandwidth memory (HBM) supports high-speed access to model weights and active inference states; long context and concurrent sessions will increase pressure on the key-value cache (KV Cache), while CPU-side DDR memory handles tasks such as tool execution, database access, and session management. Enterprise-grade NAND solid-state drives (SSD) are used for knowledge bases, documents, and operation records, and under appropriate architectures can take on part of KV cache offloading and reuse. A recent technical explanation by Micron Technology also divided these requirements into layers such as high-speed memory close to accelerators, data center main memory, and context storage. The world's top wealth management institutions are beginning to install AI assistants: Claude strives to compete for Wall Street financial advisors' workstations It is understood that Anthropic is promoting a new version of Claude to financial advisors at Wall Street's top asset management institutions and comprehensive financial institutions, combining this chat Siasun Robot&Automation with financial analysis and risk management technologies provided by BlackRock, Vanguard Group, and other companies. According to senior executives at Anthropic and BlackRock, this AI agent operating system called "Claude for Financial Advisors" is expected to accelerate work such as research, administrative affairs, and portfolio oversight. This is one of the AI company's most important moves to date in expanding into the financial industry. This function can also connect to tools from companies such as Charles Schwab and iCapital, and was developed on the basis of Anthropic's previously launched financial services AI agents; these agents are designed to handle financial services tasks such as producing business pitch presentations and reviewing statements. Anthropic's promotion of products to the financial industry comes as the entire AI industry is in a period of coexisting growth and turbulence. Both Anthropic and OpenAI are planning initial public offerings, which will bring billions of dollars in gains to early investors. OpenAI just launched financial services features tailored for investment bankers and equity researchers last week. At the same time, the rapid development of artificial intelligence technology is raising alarm among legislators and industry leaders around the world. On Saturday, Anthropic CEO Dario Amodei said the development speed of the most advanced systems must be slowed to prevent catastrophe; OpenAI CEO Sam Altman and SpaceXAI CEO Elon Musk both expressed support for his statement. Like OpenAI, Anthropic has been competing for enterprise customers through professional services beyond software engineering and programming. The Claude financial advisor version is part of this effort, focusing on providing advisors with more efficient workflows so they can serve more clients. Jonathan Pelosi, head of financial services at Anthropic, said in an interview: "The people who actually do financial advisor workthe scale is not large, and in fact it is shrinking. These people are retiring, and this group was not large to begin with. Therefore, the supply of high-quality financial guidance is actually not abundant. If we can do something to help these advisors serve more clients, we think that is absolutely a good thing." Anthropic's tool can give more advisors access to portfolio analysis and investment research tools from companies such as BlackRock and Vanguard, and may bring more business to these companies. Financial advisors are increasingly relying on "model portfolios" composed of exchange-traded funds and other investments; for example, BlackRock says it currently manages about $300 billion in such portfolios. Jamie Maggioncalda, head of U.S. wealth advisory and retirement at BlackRock, said: "One of the biggest trends we have observed is that advisors want to outsource work. The opportunity to help advisors build portfolios lies not only in providing better information, but also in helping them improve their service capacity." Investment advice and investment decisions will still be the responsibility of advisors and their clients. Pelosi said: "You will not get investment advice directly from Claude. We leave that judgment to the professionals."