# Computing Related Articles

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

Anthropic's Revenue Surpasses $30 Billion, Signs 3.5 Gigawatt Computing Power Agreement with Google and Broadcom

Anthropic announced its annualized revenue has surpassed $30 billion, a more than threefold increase from $9 billion at the end of 2025. The number of enterprise customers spending over $1 million annually doubled to 1,000 in less than two months. Growth is largely driven by Claude Code, launched in May 2025, which reached over $2.5 billion in annualized revenue by February 2026. In a related move, Broadcom disclosed in an SEC filing that Anthropic will secure approximately 3.5 gigawatts of next-generation TPU compute power starting in 2027, marking its largest single compute commitment to date. This is part of an expanded partnership involving Google and Broadcom, which will design and supply the new TPUs. Unlike OpenAI’s capital-intensive Stargate project, which involves building owned-and-operated data centers, Anthropic adopts a capital-light strategy—relying on long-term compute agreements with cloud providers (AWS, Google Cloud, and Microsoft Azure) without owning physical infrastructure. This multi-cloud, multi-chip approach offers flexibility but may entail higher long-term costs. Anthropic expects a $14 billion loss in 2026 despite ~40% gross margins.

marsbit04/07 07:29

Anthropic's Revenue Surpasses $30 Billion, Signs 3.5 Gigawatt Computing Power Agreement with Google and Broadcom

marsbit04/07 07:29

DeepSeek Paralyzed for 12 Hours: Is the Computing Power of Domestic Large Models Failing to Keep Up with Ambitions?

On the evening of March 29, DeepSeek, a leading Chinese large language model, experienced a 12-hour service outage affecting both its web and app platforms. The disruption, marked by repeated server failures and instability, raised significant concerns about the platform's reliability. Initial explanations pointed to overwhelming user traffic, but data did not support a sudden surge in users. Instead, the incident highlighted deeper structural challenges, particularly in computational supply struggling to keep pace with growing AI demands. As models become more complex—supporting longer context, advanced reasoning, and multimodal tasks—the computational load increases substantially. The outage also underscored emerging usage patterns like “lobster farming,” where automated, high-frequency API calls amplify server load. Meanwhile, anticipation for DeepSeek’s upcoming V4 model—featuring major upgrades like million-token context and stronger multimodal capabilities—suggests even greater future computational pressure. This incident signals a shift in the AI industry: competition is no longer just about model capability but also infrastructure stability, cost efficiency, and engineering scalability. The outage serves as an early warning of the systemic challenges facing AI platforms as adoption expands.

marsbit04/03 12:23

DeepSeek Paralyzed for 12 Hours: Is the Computing Power of Domestic Large Models Failing to Keep Up with Ambitions?

marsbit04/03 12:23

2.1 Gigawatt Computing Power Aircraft Carrier Sets Sail! Microsoft Takes Over Texas AI Factory Project, Moves into Same Campus as OpenAI

In the global AI computing race, Abilene, Texas, is emerging as a key strategic hub. Microsoft has officially taken over a large-scale data center construction project originally initiated by OpenAI. The collaboration, led by data center developer Crusoe, will see Microsoft and OpenAI as neighbors in the same campus. The project will feature two new state-of-the-art "AI factory" data centers, supported by a dedicated 900-megawatt power plant. With Microsoft’s involvement, the campus will expand to a total of 10 data center buildings, reaching a total computing capacity of 2.1 gigawatts. Notably, OpenAI has decided to halt further expansion at the Abilene site and will instead distribute new computing resources across other U.S. locations to optimize grid load and resource allocation. The campus already hosts major players like Microsoft, OpenAI, and Oracle. The 2.1-gigawatt scale signifies a shift from gigawatt-level to larger computing clusters, enabling improved energy sharing and reduced latency for AI model training. This transformation positions Abilene as a critical hub in global AI infrastructure, with physical proximity between Microsoft and OpenAI likely accelerating the development of next-generation large-scale AI models.

marsbit03/30 05:54

2.1 Gigawatt Computing Power Aircraft Carrier Sets Sail! Microsoft Takes Over Texas AI Factory Project, Moves into Same Campus as OpenAI

marsbit03/30 05:54

Cango Releases 2025 Financial Report: Bitcoin Mining Revenue Reaches $670 Million, Accelerating Transformation into an AI Infrastructure Platform

Canggu (NYSE: CANG) reported its 2025 full-year and Q4 financial results, highlighting a significant revenue of $688.1 million for the year, with $675.5 million coming from Bitcoin mining. The company mined 6,594.6 Bitcoin in 2025, averaging 18.07 per day. However, it reported a net loss of $452.8 million for the year, primarily due to one-time transition costs and market-driven fair value adjustments. In Q4, the net loss was $285.0 million. Canggu is strategically pivoting towards becoming an AI infrastructure provider, leveraging its scalable computing and energy network capabilities. The company completed its transition to a direct listing on the NYSE and has taken steps to optimize its balance sheet, including selling Bitcoin to repay debt. As of December 31, 2025, it held $41.2 million in cash and had long-term debt of $557.6 million.

marsbit03/24 03:11

Cango Releases 2025 Financial Report: Bitcoin Mining Revenue Reaches $670 Million, Accelerating Transformation into an AI Infrastructure Platform

marsbit03/24 03:11

Stratechery Overturns the AI Bubble Theory: What Should We Use AI For?

Stratechery's Ben Thompson revises his stance on the AI bubble debate, arguing that current AI investment reflects structural growth driven by fundamental technological shifts, not speculation. He identifies three key transitions in LLM development: ChatGPT’s debut (making AI broadly usable but unreliable), OpenAI’s o1 (introducing reasoning and reliability), and the recent emergence of true Agent systems (e.g., Anthropic’s Opus 4.5 and OpenAI’s GPT-5.2-Codex). The critical innovation is the "agent harness"—a control layer that autonomously schedules models, uses tools, and verifies outcomes, reducing human intervention. This transforms AI from an assistive tool into an actionable infrastructure, enabling complex task execution. Agentic systems drive surging demand for compute, as they require repeated model calls and higher usage frequency. Thompson emphasizes that AI demand now depends not on user numbers, but on per-user agent utilization. Enterprises are adopting AI not only for efficiency gains but for structural workforce reduction, as agents amplify the impact of key employees while lowering coordination costs. He concludes that massive capital expenditures are justified by real demand, and profits will flow to integrated model-harness providers rather than commoditized standalone models.

marsbit03/17 03:57

Stratechery Overturns the AI Bubble Theory: What Should We Use AI For?

marsbit03/17 03:57

Daniil and David Liberman: AI is Not Just a Battle of Models, But a Battle of Computing Infrastructure

In the article "Daniil and David Liberman: AI Is Not Just a Battle of Models, but a Battle of Compute Infrastructure," the authors argue that the core of AI development is not just about algorithmic advances but control over computational resources. They emphasize that AI is not a neutral technology—who owns and governs the compute infrastructure ultimately determines who benefits from AI. Currently, advanced AI compute is highly concentrated among a few cloud providers and specific nations, creating a growing "compute divide." This centralization leads to high costs, limited access, and geographic imbalance. Decentralized alternatives, meanwhile, often waste resources on consensus mechanisms rather than meaningful computation. The authors propose a practical alternative: an infrastructure where most compute is used for actual AI work, governance is based on verified computational effort (not capital), and global GPU access is permissionless. They stress that infrastructure choices made today will have long-term economic and geopolitical consequences. For businesses, early reliance on centralized AI infrastructure creates lock-in effects that reduce strategic flexibility over time. The authors warn that waiting too long to explore decentralized options may make transition prohibitively difficult. They conclude that future generations must recognize that AI architecture is a deliberate design choice—not an inevitability—and that open, decentralized infrastructure is essential to preserving fairness, innovation, and freedom in the AI era.

marsbit03/16 03:19

Daniil and David Liberman: AI is Not Just a Battle of Models, But a Battle of Computing Infrastructure

marsbit03/16 03:19

From 5 Cents per kWh Chinese Electricity to $45 API Export Packages: Token is Becoming the New Currency Unit

The article explores the concept of "Token出海" (Token Outbound), arguing that tokens are evolving from a technical term into a new monetary unit in the machine-driven economy. It begins by drawing a parallel between historical control over information flow (like transatlantic cables) and today's control over AI API calls and value transfer. Tokens now serve a dual role: as a unit of computation in AI and a means of payment in crypto. A key driver is the rise of AI Agents, like OpenClaw, which shift tokens from being a simple "conversation cost" to a "production fuel" for executing complex tasks. This massive consumption creates a competitive advantage for Chinese AI models, which are often priced lower. The article posits that this isn't just about cheap models, but about China leveraging its vast domestic electricity and computing power to export value globally via token-denominated AI services. The convergence of AI and crypto is facilitated by protocols like x402, which enables machines to natively pay for API calls, and ERC-8183, which allows them to enter into complex escrow-based contracts. This creates a machine-native economic layer where tokens act as the fundamental unit of permission, settlement, and value measurement. The conclusion is that while traditional fiat won't disappear, tokens are becoming the foundational monetary unit for the new agentic economy. The future "power to mint currency" may belong to those who can most efficiently compress real-world resources (like electricity and compute) into tradable tokenized services.

Odaily星球日报03/13 04:41

From 5 Cents per kWh Chinese Electricity to $45 API Export Packages: Token is Becoming the New Currency Unit

Odaily星球日报03/13 04:41

Is Quantum Computing A Threat To Bitcoin? ARK Invest Breaks It Down

ARK Invest and Unchained's research paper examines the potential threat quantum computing poses to Bitcoin's cryptography. The authors conclude it is a legitimate long-term concern but not an imminent threat. Current quantum systems are in the "NISQ era" with limited qubits and high error rates, far from the estimated requirement of at least 2,330 logical qubits to break Bitcoin's encryption. The report describes quantum development as a gradual progression, not a sudden event, providing ample warning and time for the market and network to adapt. It estimates that roughly 35% of Bitcoin's supply could theoretically be exposed, but many of these coins are either lost or can be migrated to safer address formats. The paper highlights that meaningful quantum breakthroughs would disrupt broader internet security first, triggering a coordinated response. While the technical risk is distant, it raises future governance challenges, as upgrading Bitcoin's cryptography would require community consensus. The authors frame the issue as a manageable long-term engineering problem rather than an abrupt point of failure.

bitcoinist03/12 16:02

Is Quantum Computing A Threat To Bitcoin? ARK Invest Breaks It Down

bitcoinist03/12 16:02

NVIDIA's Jensen Huang Latest Article: The 'Five-Layer Cake' of AI

NVIDIA's Jensen Huang articulates AI not merely as a software application but as a fundamental infrastructure, comparable to electricity or the internet, in a layered "five-layer cake" structure. This stack begins with **Energy** as the foundational constraint, powering real-time intelligence generation. Above it, **Chips** convert energy into computational power efficiently. The **Infrastructure** layer comprises data centers and systems that function as "AI factories." **Models** form the next layer, processing diverse data types like language, biology, and physics. At the top, **Applications**—such as drug discovery, autonomous vehicles, and robotics—create economic value. Huang emphasizes that AI is an industrial-scale transformation, driving massive global infrastructure expansion requiring trillions in investment and a skilled workforce—from electricians to network technicians—beyond just computer scientists. He notes that AI has recently crossed a threshold: models are now reliable enough for widespread use, reducing hallucinations and improving reasoning, which accelerates real-world applications. Open-source models, like DeepSeek-R1, further propel growth across the entire stack. This infrastructure revolution will reshape energy consumption, manufacturing, labor, and economic growth. Every company and country will participate, though the field remains early-stage, with vast opportunities and responsibilities ahead.

marsbit03/10 14:18

NVIDIA's Jensen Huang Latest Article: The 'Five-Layer Cake' of AI

marsbit03/10 14:18

After Sending NVIDIA AI Servers into Space, This Space Startup Now Sets Its Sights on Bitcoin Mining

A space computing startup, Starcloud, is expanding its ambitions after successfully sending NVIDIA AI servers into orbit. The company now plans to launch Bitcoin mining operations into space, aiming to leverage the advantages of the extraterrestrial environment. CEO Philip Johnston revealed that Starcloud intends to deploy Bitcoin ASIC hardware on its Starcloud-2 satellite, scheduled for launch in 2026. If successful, it would mark the first-ever Bitcoin mining operation in space. The company believes space offers significant benefits, including near-limitless solar energy, reduced cooling costs due to extreme environmental conditions, and freedom from terrestrial energy constraints and regulatory pressures. However, the economic viability remains uncertain due to high launch costs, hardware durability challenges in high-radiation environments, and rapidly evolving mining technology. While the initiative may currently hold more symbolic than practical value, it reflects a growing trend of extending blockchain and computing infrastructure beyond Earth. Starcloud, backed by investors like a16z and Sequoia, has already made strides by training an AI model in orbit using an NVIDIA H100 GPU. The company, along with others like Google and SpaceX, is part of a broader movement to develop space-based data centers, signaling that the next frontier for AI and computing may indeed be in orbit.

marsbit03/10 05:33

After Sending NVIDIA AI Servers into Space, This Space Startup Now Sets Its Sights on Bitcoin Mining

marsbit03/10 05:33

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