# Сопутствующие статьи по теме Centralization

Новостной центр HTX предлагает последние статьи и углубленный анализ по "Centralization", охватывающие рыночные тренды, новости проектов, развитие технологий и политику регулирования в криптоиндустрии.

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

Polymarket's "Hand of God": Frequent Prediction Disputes, the Black Box of Adjudication Power Under the "Centralization" Dilemma

A semantic dispute over whether the U.S. "invaded" Venezuela led to a multimillion-dollar betting outcome on Polymarket, where the "No" option was controversially settled despite real-world actions that many perceived as invasion. This incident highlights a recurring structural flaw in decentralized prediction markets: the challenge of defining "truth" for complex real-world events. Similar semantic ambiguities have repeatedly occurred on Polymarket, such as a high-stakes bet on whether Ukraine’s President Zelensky wore a suit at a specific event. While real-world evidence seemed clear, the outcome was swayed by decentralized oracle UMA’s governance mechanism, allowing token holders to vote on disputed results—sometimes enabling large players to manipulate outcomes. These cases reveal the limits of "code is law" in prediction markets. While blockchain excels at executing predefined rules trustlessly, it struggles with contextual, socially constructed events like political or military interpretations. The authority to define and settle reality ultimately remains centralized in the hands of rule-makers and arbitrators, even when execution is decentralized. Prediction markets work best for clearly defined, data-driven questions but face inherent challenges when applied to politicized or semantically ambiguous events. The core issue isn’t whether the market is decentralized, but who holds the power to define reality when consensus breaks down.

marsbit01/22 11:04

Polymarket's "Hand of God": Frequent Prediction Disputes, the Black Box of Adjudication Power Under the "Centralization" Dilemma

marsbit01/22 11:04

The Most Centralized Giant in the Crypto World Starts Selling the 'Decentralized AI' Dream

Tether, the highly centralized issuer of the USDT stablecoin, reported $13 billion in profit in 2024—far exceeding the combined revenues and losses of major AI firms like OpenAI and Anthropic. With only 150 employees, Tether earns primarily by investing user funds in U.S. Treasury bonds, profiting from the interest without paying users any yield. Now, Tether is aggressively investing in AI. It loaned over $600 million to Northern Data, Europe’s largest GPU cloud provider with over 10,000 Nvidia H100 GPUs. It also released QVAC Genesis, a massive open-source AI training dataset, and acquired Blackrock Neurotech, a brain-computer interface company, for $200 million. Total AI-related investments approach $1 billion, with potential additional deals in robotics sector. Despite its centralized control over USDT reserves and lack of external audits, Tether promotes a “decentralized AI” vision—advocating for local AI operation and individual data ownership. Critics find this ironic, given Tether’s opaque governance. Tether’s move into AI may stem from concerns over declining Treasury yields and a desire to position itself as a tech innovator. Unlike AI startups burning billions without clear profitability, Tether uses stablecoin profits to fund speculative AI bets—insulating itself from sector risks while gaining influence. The article suggests that in 2026, the best business model in AI might be not doing AI at all, but rather funding it with profits from a separate, lucrative venture.

比推01/05 14:50

The Most Centralized Giant in the Crypto World Starts Selling the 'Decentralized AI' Dream

比推01/05 14:50

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