2026-07-09 Quinta

Notícias de cripto - Página 1466

Mantenha-se a par do mercado de cripto. Notícias em tempo real, análises, preços, histórias em alta e análise de especialistas — tudo num só lugar.

Why Large Language Models Aren't Smarter Than You?

The article explores why large language models (LLMs) are not inherently smarter than their users, arguing that their reasoning ability depends entirely on how users guide them. When discussing complex topics informally, LLMs often fail to maintain conceptual coherence and produce shallow or derailed responses. However, if the user first formalizes the problem using precise, scientific language, the model's reasoning stabilizes. This occurs because different language styles activate distinct "attractor regions" in the model’s latent space—areas shaped by training data that support specific types of computation. Formal language (e.g., scientific or mathematical) activates regions conducive to structured reasoning, featuring low ambiguity, explicit relationships, and symbolic constraints. These regions support multi-step logic and conceptual stability. In contrast, informal language triggers attractors optimized for social fluency and associative coherence, which lack the scaffolding for sustained analytical thought. Thus, users determine the LLM’s effectiveness: those who can formulate prompts using high-structure language activate more powerful reasoning regions. The model’s performance ceiling is not its own intelligence limit but reflects the user’s ability to access and sustain high-capacity attractors. The author concludes that true artificial reasoning requires architectural separation between internal reasoning and external expression—a dedicated reasoning manifold—to prevent collapse when language style shifts. The "formalize first, then translate" method is not just a trick but reveals a fundamental design principle for future AI systems.

深潮12/15 07:21

Why Large Language Models Aren't Smarter Than You?

深潮12/15 07:21

"Asia's First Stock" HashKey Goes Public: A Decade of Dedication, Edge Emerging

"Asia's first crypto stock" HashKey has listed on the Hong Kong Stock Exchange, marking a milestone after a decade of strategic development. As of September 2025, the platform has facilitated HKD 1.3 trillion in cumulative spot trading volume, commanding over 75% market share among Hong Kong’s 11 licensed virtual asset trading platforms. HashKey’s success stems from its long-term compliance-first strategy, aligning closely with Hong Kong’s evolving regulatory landscape. While many platforms operated in regulatory grey areas, HashKey focused on building robust infrastructure, obtaining licenses, and adhering to strict anti-money laundering (AML), know-your-customer (KYC), and asset segregation requirements. The company capitalized on Hong Kong’s introduction of the Virtual Asset Service Provider (VASP) licensing regime in 2022, becoming one of the first fully regulated exchanges. The compliance-heavy model requires significant investment in technology, auditing, and risk management, resulting in higher operational costs and a longer path to profitability. However, it has positioned HashKey as a trusted gateway for institutional investors, offering services including staking, asset management, and real-world asset (RWA) tokenization. HashKey’s IPO symbolizes a broader industry transition from speculative trading to institutional participation and regulated financial infrastructure. It represents the rise of compliance as a core competitive advantage in the virtual asset sector and underscores Hong Kong’s strategic role in shaping Asia’s digital finance future.

深潮12/15 06:36

"Asia's First Stock" HashKey Goes Public: A Decade of Dedication, Edge Emerging

深潮12/15 06:36

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