# Пов'язані статті щодо Technology

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

Dialogue with MIT Economist: Don't Panic About 'AI Doomsday Theory', Verification Capability is a Scarce Resource

In a discussion with MIT economist Christian Catalini, the core argument is that the true scarcity in the AI economy is not intelligence but verification—the human capacity to check, judge, and confirm the correctness of AI outputs. Catalini explains that while automation costs are falling exponentially, verification remains constrained by human biological limits, at least for now. Entry-level jobs are most vulnerable, as AI can easily replicate tasks that rely on measurable, existing knowledge. However, even top experts are inadvertently training their own replacements by generating data that AI learns from—a phenomenon termed the "coder’s curse." Three roles will remain critical in the AI-driven economy: - **Directors**: Those who set intentions and steer AI agents toward goals, dealing with "unknown unknowns." - **Meaning Makers**: Individuals who create cultural, social, or narrative value based on human consensus and status games. - **Liability Underwriters**: Top-tier experts (e.g., lawyers, doctors) who assume responsibility for edge cases and final validation. Catalini advises against panic and encourages experimentation with AI tools to automate current roles and discover new opportunities. He emphasizes that uniquely human traits—like judgment in unmeasurable contexts—will retain value, and crypto-based verification infrastructure may play a key role in ensuring authenticity. The transition will be disruptive, but leveraging AI can amplify human potential exponentially.

marsbitВчора 08:06

Dialogue with MIT Economist: Don't Panic About 'AI Doomsday Theory', Verification Capability is a Scarce Resource

marsbitВчора 08:06

IBM Loses $40 Billion, Block Lays Off Half Its Workforce Yet Stock Rises: In the AI Era, What Assets Are Worth Tokenizing?

On February 23, 2026, IBM’s stock plummeted 13.2%, erasing $40 billion in market value, after AI startup Anthropic announced its Claude Code tool could modernize IBM’s legacy COBOL systems—a core profit driver for IBM. In contrast, Block’s stock surged 24% three days later despite announcing a 50% workforce reduction, citing AI-driven efficiency gains. These divergent reactions highlight how AI is redefining asset value. The article argues AI acts as a "repricer" of assets, favoring those with "AI immunity." Key traits include non-codability (e.g., IBM’s hardware-software integration, which AI can’t fully replicate), data moats (exclusive, high-quality data), and AI-augmentability (assets enhanced, not replaced, by AI). Assets vulnerable to AI are those reliant on human intermediation or standardized processes. The framework extends to real-world asset (RWA) tokenization. Assets worth tokenizing are those resilient to AI-driven devaluation, such as energy infrastructure, GPU computing power, exclusive data assets, and hybrid physical-digital assets. The piece cautions against tokenizing assets dependent on human intermediaries or lacking data moats. The conclusion urges executives to stress-test their asset portfolios using the "AI immunity" framework, dynamically manage asset allocation, and carefully evaluate RWA strategies based on AI resilience. It emphasizes that in the AI era, sustainable assets are those that leverage human judgment and possess inherent physical or exclusive value.

marsbit03/19 01:25

IBM Loses $40 Billion, Block Lays Off Half Its Workforce Yet Stock Rises: In the AI Era, What Assets Are Worth Tokenizing?

marsbit03/19 01:25

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