# AI Related Articles

HTX News Center provides the latest articles and in-depth analysis on "AI", covering market trends, project updates, tech developments, and regulatory policies in the crypto industry.

Why Does the Term 'Year of AI Computing Power Realization' Have Pitfalls? —Understanding the Four Hurdles from Policy Signals to Actual Orders in One Article

This article critiques the phrase "The First Year of AI Computing Power Cashing In," arguing it oversimplifies a complex, multi-stage process. It proposes a "Four Gates" framework to assess the true commercialization of domestic AI computing power (like Huawei's Ascend chips): 1. **Policy Procurement:** Widely open in 2026. Significant government funding and large bulk orders from tech giants like Alibaba and Tencent exist. However, purchasing hardware is not the same as deploying it for real use. 2. **Real Deployment:** A crack has opened. The key evidence is DeepSeek V4, a top-tier AI model fully migrating from NVIDIA's CUDA to domestic computing platforms. This proves the capability for real, high-level tasks, but widespread adoption beyond leading tech firms is still nascent. 3. **Mature Software Ecosystem:** A narrow crack has opened. While frameworks like Huawei's CANN are progressing, they lag far behind NVIDIA's vast, established CUDA ecosystem in terms of supported models and developer ease-of-use. Building this middle-to-downstream developer environment is estimated to need 1-2 more years. 4. **Scalable Replication:** Essentially closed. This final gate, where thousands of mid-sized enterprises across various industries can easily adopt the technology without major migration costs, is not expected before 2027-2028. The core risk is conflating these stages. While 2026 marks a real turning point in policy-driven procurement and proving technical viability (Gates 1 & 2), the phrase "cashing in" is premature for the full industry. True, large-scale value realization depends on the later, slower-to-open gates of software maturity and scalable replication to the broader market. DeepSeek V4's shift is identified as the most critical 2026 signal, changing the narrative from "can it work?" to "when will supply meet demand?"

marsbit16m ago

Why Does the Term 'Year of AI Computing Power Realization' Have Pitfalls? —Understanding the Four Hurdles from Policy Signals to Actual Orders in One Article

marsbit16m ago

Berkshire Hathaway and SoftBank: One Must Die

Berkshire and SoftBank: A Tale of Two Extremes The article presents a speculative future (set in 2026) contrasting the investment philosophies and potential fates of Berkshire Hathaway and SoftBank Group. Under new CEO Greg Abel, Berkshire sits on a massive cash pile of nearly $400 billion, built by selling assets like Apple stock over many quarters. Buffett and now Abel deem the market overvalued and refuse to invest, leading to significant underperformance. The "disease" of too much cash poses an existential threat to Berkshire's identity as a capital allocator, potentially forcing a future breakup or special dividend if the bull market persists. Its "death" would be a slow, dignified fading of its legendary investment narrative. In stark contrast, SoftBank's Masayoshi Son is all-in on a high-stakes gamble. To fund a colossal $64.6 billion (and growing) investment in OpenAI, SoftBank has aggressively leveraged itself. It has sold core holdings like Nvidia, T-Mobile, and Alibaba, taken on over $100 billion in parent-level debt, and secured a record $40 billion bridge loan. The survival strategy hinges on a successful OpenAI IPO and the high valuation of its Arm holdings. However, this creates multiple interconnected risks: an OpenAI IPO delay, a correction in Arm's lofty valuation, or a credit market freeze. Any of these could trigger a liquidity crisis. SoftBank's potential "death" would be swift and dramatic. The core thesis is that in this speculative market, one extreme strategy—Berkshire's paralyzing caution or SoftBank's all-or-nothing leverage—will likely prove unsustainable. One may lose its soul, the other may face financial rupture.

链捕手5h ago

Berkshire Hathaway and SoftBank: One Must Die

链捕手5h ago

Three Months of Raising $6 Billion in Funding: What Are the Leading Crypto VCs Betting On?

While the crypto bear market persists, top-tier venture capital firms are making significant moves by raising massive new funds, signaling a strategic bet on the industry's future. Haun Ventures and a16z recently announced funds totaling $1 billion and $2.2 billion, respectively. This follows other major raises from firms like Dragonfly, Paradigm, ParaFi, and Blockchain Capital. In under three months, these six VCs have amassed over $6 billion in fresh capital, a clear example of counter-cyclical investing during a quiet market phase. The fundraising landscape highlights a sharp divergence between large and small VCs. Many mid-sized and smaller funds are struggling with poor returns, limited exit options, and difficulty raising new capital, leading some to scale back or exit. In contrast, leading firms are strengthening their dominance due to structural advantages: superior access to high-quality deals, the ability to invest across all stages, greater capacity for long-term bets and risk, and stronger negotiation power. These new funds are largely converging on key investment themes. The strongest consensus centers on next-generation on-chain financial infrastructure, including stablecoins, real-world asset (RWA) tokenization, prediction markets, and on-chain payments. VCs are focusing on projects with validated demand that can attract traditional finance flows. Another major focus is artificial intelligence (AI), particularly AI agents, as crypto seeks to position its open, composable networks as foundational infrastructure for the emerging AI economy. Ultimately, this wave of bear-market fundraising is a strategic wager on the next cycle. By deploying capital when valuations are lower and market noise is reduced, these top VCs aim to identify and back the foundational projects that will define the industry's future, betting on which companies will become the next generation of leaders.

marsbit6h ago

Three Months of Raising $6 Billion in Funding: What Are the Leading Crypto VCs Betting On?

marsbit6h ago

AI Agent Practical Guide: How to Power an Entire Company with Three Intelligent Agents?

AI Agent Implementation Guide: How to Use Three Intelligent Agents to Run an Entire Company? Every solopreneur faces the same bottleneck: too much work for one person, yet not enough revenue to hire three full-time employees at $60,000 each. These roles—market research, content creation, and daily operations—are essential and often consume the founder's time. The smartest entrepreneurs are now "building" AI agents for these jobs instead. Using Claude, MCP servers, and agentic workflows, you can build three specialized AI agents: 1. **Research Agent:** Acts as a full-time market intelligence analyst. It proactively monitors competitors, tracks industry trends, identifies opportunities, and delivers a concise weekly briefing. It requires a knowledge base of competitors and market data, tools like web search APIs and access to your files, and a workflow that runs automatically every Monday. 2. **Content Agent:** Manages your entire content production pipeline from ideation to publishing. It generates topics, drafts content, edits for your specific brand voice, repurposes content across platforms, and schedules posts. Key steps include feeding it your best writing samples to learn your style and implementing quality checks to ensure content meets your standards before you add your unique "soul" to it. 3. **Operations Agent:** Serves as your chief of staff, handling time-consuming administrative tasks like email triage, meeting preparation, and generating weekly reports. By connecting to your email, calendar, and project management tools, it can compress hours of daily work into a 15-minute review. The crucial step is enabling these agents to collaborate as a team. A shared knowledge base allows them to work together; for example, the research agent flags a competitor's new feature, the content agent creates a response, and the operations agent drafts a related email to clients. Financially, three human employees cost around $180,000 annually plus overhead, while three AI agents primarily cost your Claude subscription and setup time. While agents lack human judgment, creativity, and empathy, they can handle 70-80% of the workload for these core roles in a startup's first 12-18 months. The guide recommends building one agent per week: start with research, then content, then operations. In three weeks, you can have a 24/7 AI-powered team instead of working alone.

marsbit6h ago

AI Agent Practical Guide: How to Power an Entire Company with Three Intelligent Agents?

marsbit6h ago

Ray Dalio's Latest Interview: Can the U.S. Still Escape the Cycle of Decline?

In a comprehensive interview, Ray Dalio, founder of Bridgewater Associates, analyzes whether the US can escape its historical "great cycle" of decline. He argues the nation faces a confluence of structural pressures, not a single crisis. Key points include: 1. **The Debt Cycle:** Unsustainable fiscal deficits and rising debt-to-income ratios are eroding national capacity, constraining spending on defense, welfare, and global commitments. 2. **Internal Political & Social Conflict:** Deep wealth gaps and value differences fuel intense political polarization. Addressing deficits becomes a zero-sum political battle over "who pays and who benefits," making consensus nearly impossible. 3. **Erosion of the World Order:** The post-1945 US-led, rules-based international system is breaking down, reverting to a state of great-power competition and conflict where raw power, not multilateral rules, resolves disputes. 4. **Currency & Safe Assets:** While the Chinese yuan may gain use as a medium of exchange, Dalio doubts it will become a primary global store of wealth. In an era of fiat currency debasement, assets like gold are regaining prominence as safe havens. 5. **AI's Dual Role:** Artificial Intelligence could boost productivity and help manage debt, but it also risks exacerbating wealth inequality, job displacement, and geopolitical tensions. Dalio concludes the US is in a period of increasing disorder, with debt, domestic strife, and international realignments converging. The critical factors for national recovery are foundational: improving education and civic素养, fostering social cohesion and productivity, and avoiding war—both civil and international. The path forward depends less on markets and more on these fundamental societal choices.

marsbit7h ago

Ray Dalio's Latest Interview: Can the U.S. Still Escape the Cycle of Decline?

marsbit7h ago

Conversation with Mai-Lan from AWS: The Next Battlefield for S3 – How to Handle the Data Consumption Surge in the Agent Era

The explosive rise of Agent AI, exemplified by OpenClaw in China, is putting unprecedented pressure on cloud data infrastructure. Unlike human engineers, Agents consume data in an "extremely active and aggressive" parallel fashion, launching tens to hundreds of queries simultaneously, leading to exponentially higher call frequencies and throughput. Mai-Lan Tomsen Bukovec, VP of Technology at AWS, emphasizes that cost-effectiveness in this data layer is now a decisive factor for customers building Agent systems. To address this, AWS is positioning its foundational Amazon S3 service, now 20 years old, as the critical data platform for the Agent era. Recent key innovations include: **S3 Table** with native Apache Iceberg support, enabling Agents to efficiently interact with structured data via familiar SQL; **S3 Vector**, which introduces vectors as a native type for building contextual data and serving as a shared "memory space" for AI systems; and the newly launched **S3 Files**, which provides a POSIX-compliant file system interface over S3, allowing Agents to interact with data through the familiar paradigm of files and directories. These enhancements are designed to meet the unique data interaction patterns of Agents, which are trained on models already proficient with SQL, file systems, and contextual vectors. By unifying these access methods on the scalable, durable, and cost-efficient S3 foundation, AWS aims to provide the data backbone capable of supporting the next wave of hyper-scale, high-frequency Agent applications.

marsbit7h ago

Conversation with Mai-Lan from AWS: The Next Battlefield for S3 – How to Handle the Data Consumption Surge in the Agent Era

marsbit7h ago

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