# Пов'язані статті щодо Data

Центр новин HTX надає останні статті та поглиблений аналіз на тему "Data", що охоплює ринкові тренди, оновлення проєктів, технологічні розробки та регуляторну політику в криптоіндустрії.

Microsoft CEO Satya Nadella's Latest Warning: Betting Entirely on a Single AI Model Hands Over a Company's Lifeblood

Microsoft CEO Satya Nadella warns that companies relying solely on a single AI model could jeopardize their survival. He argues that over-dependence leads to "vendor lock-in," where businesses risk ceding control over their core data, memory, contextual history, and AI usage patterns. This dependence essentially outsources a company's critical thinking and operational know-how to an external provider. The deeper a company integrates with one AI system—feeding it prompts, internal data, and workflows—the more it reveals its unique business methods and competitive edge. This accumulated knowledge could become accessible to the AI supplier. Furthermore, switching providers becomes extremely costly and complex, as companies would need to rebuild their entire AI-augmented workflow, memory, and tool integrations from scratch. Nadella's solution is "decoupling." Companies should separate their proprietary data, memory, and control layer (or "harness") from the underlying AI models. By retaining metadata from every AI interaction, businesses can preserve their operational "brain" or institutional knowledge. This allows them to flexibly use different AI models (e.g., from OpenAI, Anthropic, Microsoft) for specific tasks without losing their accumulated expertise. The core idea: companies can rent the smartest models available, but they must keep their own "brain" and operational control firmly in-house.

marsbit3 год тому

Microsoft CEO Satya Nadella's Latest Warning: Betting Entirely on a Single AI Model Hands Over a Company's Lifeblood

marsbit3 год тому

From Hot Storage to Cold Memory: Decentralized Storage in the AI Era's Storage Boom

"From Hot Storage to Cold Memory: Decentralized Storage in the Era of AI Storage Boom" This article explores the divergent market trajectories of AI-driven centralized storage and Web3's decentralized storage. It argues that while AI storage is experiencing a massive revaluation focused on "hot data efficiency" — maximizing computational throughput via technologies like HBM, enterprise SSDs, and sophisticated data pipelines — decentralized storage projects like Filecoin and Arweave are currently sidelined. Their core value proposition lies in "cold data trust," prioritizing data integrity, censorship resistance, and long-term archival over raw speed. The piece details the AI storage architecture, emphasizing its role as a "performance engine" critical for feeding GPUs, contrasted with decentralized storage's focus on serving as a permanent, verifiable ledger for humanity's collective memory. It analyzes the challenges decentralized storage faces, including product-market fit, enterprise readiness, and token economic misalignment, but concludes that its fundamental value in preserving provenance, public datasets, and civilizational archives positions it for potential long-term revaluation as issues of data sovereignty, AI auditability, and historical preservation become more acute. The current market rewards efficiency, but the pendulum may eventually swing back towards trust.

marsbit23 год тому

From Hot Storage to Cold Memory: Decentralized Storage in the AI Era's Storage Boom

marsbit23 год тому

Michael Saylor: 110 Reasons to Oppose BIP-110

Michael Saylor presents 110 arguments against Bitcoin Improvement Proposal (BIP) 110, a soft fork aimed at restricting certain non-monetary data storage uses (like inscriptions) on the Bitcoin blockchain. He acknowledges the proponents' valid concerns—such as node costs, fee pressure, and preserving Bitcoin's monetary focus—but fundamentally disagrees with the proposed solution. Saylor argues that BIP 110 represents a dangerous precedent of using consensus rules to enforce value judgments on transaction validity, moving away from Bitcoin's core principles of neutrality and permissionless innovation. His key objections are organized into eleven categories: 1) It violates neutrality and hard consensus by banning currently valid transactions. 2) It fails to meet the high burden of proof required for a consensus change, lacking concrete data on the alleged crisis. 3) Its seven bundled technical restrictions are overly broad, targeting generic script functionalities and blocking future upgrade paths. 4) It sacrifices compatibility and future optionality by closing off designed upgrade hooks. 5) Its temporary rules add significant complexity (grandfathering, expiry states) without sufficient justification. 6) The economic and security impacts, particularly on miner revenue and fee markets, are uncertain and unmodeled. 7) Superior, market-based tools (fee markets, relay/mining policies) already exist to manage blockchain load. 8) It stifles innovation by creating a chilling effect for developers. 9) Its modified activation mechanism (55% threshold, forced signaling) is aggressive and risks network splits. 10) The precedent it sets—using consensus to suppress disliked but legal uses—is more dangerous than the problem it aims to solve. 11) A better path exists: improving measurements, refining resource-based policies, and allowing market forces to work. Saylor concludes that Bitcoin's strength lies in its neutral rules, open markets, and hard consensus. Changing these foundational elements to target specific use cases is an unnecessary and risky "iatrogenic" intervention. He advocates for guarding Bitcoin's neutrality rather than acting as its redeemer.

marsbit07/22 00:06

Michael Saylor: 110 Reasons to Oppose BIP-110

marsbit07/22 00:06

Revenue Soars 16%, Restaurant Chain Credits Bitcoin: Real Growth or PR Stunt?

Steak ’n Shake, a U.S. fast-food chain, attributed a 16% year-over-year increase in July same-store sales partly to its adoption of Bitcoin as a payment method. However, the company has not disclosed key data points, such as the actual number of Bitcoin transactions, total sales volume processed in Bitcoin, or the exact amount saved on payment processing fees. This lack of detailed information makes it difficult to isolate Bitcoin's direct impact on sales growth from other contributing factors like marketing campaigns, menu updates, promotional discounts, and operational changes. While the brand highlights the cost advantage of Bitcoin transactions—estimated to be about 50% cheaper per transaction than credit card fees—it has not provided evidence that a significant volume of sales actually uses this payment method. Steak ’n Shake’s parent company, Biglari Holdings, had already reported strong sales growth earlier in the year, driven by factors such as product upgrades and operational improvements, with no mention of Bitcoin in prior shareholder communications. The article questions whether the primary value of Bitcoin for Steak ’n Shake lies more in its public relations and branding benefits—attracting crypto enthusiasts and generating media attention—rather than in tangible business gains. To validate Bitcoin's role as a genuine growth driver and provide a replicable model for other merchants, the company would need to share comprehensive data, including Bitcoin transaction share, customer retention metrics, and detailed cost savings, allowing for a clearer analysis of its true contribution to revenue.

Foresight News07/17 07:01

Revenue Soars 16%, Restaurant Chain Credits Bitcoin: Real Growth or PR Stunt?

Foresight News07/17 07:01

On the Eve of the US Stock Inflation Test, Wall Street Faces the Most Severe 'Data Deception' in History

On the eve of the crucial US June CPI release, a significant credibility gap is emerging between official inflation data and consumer sentiment. While May CPI and PCE figures suggested a "concerning but not critical" picture, the University of Michigan Consumer Sentiment Index plummeted to its lowest level in nearly 50 years. This contradiction is prompting economists to question the reliability of key macroeconomic indicators. The core issue, as highlighted by labor economist Kathryn Anne Edwards, lies in a systemic flaw within the current inflation measurement framework. The Consumer Price Index (CPI) averages prices across a "market basket" meant for a "typical consumer," thereby masking vastly different inflation experiences across demographic groups. For instance, Bureau of Labor Statistics (BLS) research indicates that from 2006 to 2023, the lowest income quintile faced a cumulative inflation rate 7.7 percentage points higher than the highest quintile—a disparity largely invisible in the headline CPI number. This averaging effect means investors and policymakers relying on aggregate CPI may be basing decisions on a statistically smoothed figure that fails to capture the true distribution of economic pressure. Edwards argues that expanding this measurement framework is technically feasible, requiring primarily political will rather than new data collection. The BLS already tracks 100,000 items monthly; creating more granular indices for different family types, income levels, and housing statuses would mainly involve re-weighting existing data. The BLS has produced such experimental series before. A more nuanced data picture is crucial for accurate policy and market forecasting. Ultimately, improving measurement cannot solve underlying economic stresses. Edwards notes concurrent pressures like slowing hiring, stagnant wage growth, persistently high prices, rising credit card debt, a subdued housing market due to high rates, and AI's potential disruption to jobs. These factors collectively explain the deep chasm between official statistics and consumer pessimism. The key takeaway for markets is the need to look beyond a single headline CPI number. Understanding the divergence in inflation experiences across the population is critical for accurately assessing the real pressure within the economy, the path of Federal Reserve policy, and risks on the consumer side.

marsbit07/13 14:24

On the Eve of the US Stock Inflation Test, Wall Street Faces the Most Severe 'Data Deception' in History

marsbit07/13 14:24

The Market Trades on Expectations, But You're Waiting for Answers

The market trades on expectations, not on waiting for answers. A common misconception is that prices react after data is released. In reality, sensitive capital moves based on anticipated changes in policy, capital flows, and sentiment. Once an expectation forms, prices adjust in advance. For example, if the market expects the Federal Reserve to cut interest rates, assets like gold, growth stocks, or BTC may rise ahead of the actual announcement. When the cut finally happens, the market might show little movement or even pull back—not because the news isn't significant, but because it was already priced in. The same applies to reports like non-farm payrolls. If weak employment data is anticipated, gold and bonds may rally beforehand. When the data confirms the weakness, prices may not rise further, as it merely validates existing expectations. This explains why markets sometimes appear irrational: good news doesn't always lift prices, and bad news doesn't always cause declines. The key is to assess whether an event was already anticipated and whether capital has begun to price it in or is now taking profits. The market is always trading the future, not the present. Price movements reflect bets on what comes next. Therefore, focusing solely on headlines can lead to losses. Instead, investors should ask: Was this news already expected? Is the market still pricing it in, or is it time to cash out? In short, the market doesn't wait for answers—it acts on the future it believes in, often long before the news becomes public.

marsbit07/03 01:27

The Market Trades on Expectations, But You're Waiting for Answers

marsbit07/03 01:27

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