2026-08-06 Quinta

Notícias de cripto - Página 289

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.

Jensen Huang: Prompts are Becoming Obsolete, Loops are the New Paradigm

Jensen Huang, alongside AI leaders like Peter Norvig, Boris Cherny, and Andrew Ng, is advocating for a shift from "prompt engineering" to "loop engineering" as the new paradigm for AI development. Instead of manually crafting individual prompts, the focus is now on designing autonomous loops—systems where AI agents execute tasks, self-validate results, and iterate until completion without constant human oversight. A loop is a management framework that enables agents to operate independently. Key implementations are seen in Claude Code (with features like /loop, /goal, and /schedule) and OpenAI Codex, which employ multiple agents working in parallel within isolated environments. A core principle is the separation of roles: one agent (or model) performs the task, while an independent agent (or a smaller, separate model) validates the output to ensure objectivity. The article outlines a practical roadmap for implementing loops, starting with a "four-condition test" to assess suitability, building a minimal viable loop, and emphasizing critical pitfalls to avoid, such as lacking hard stop conditions or allowing loops to handle tasks requiring human judgment. This evolution is framed as the fourth major shift in AI interaction: from Prompt Engineering (crafting instructions) to Context Engineering (providing background information), then to Harness Engineering (building tool-enabled environments), and finally to Loop Engineering (creating self-sustaining systems). This progression reflects a consistent trend of increasing abstraction, moving human involvement from direct instruction to system design and rule-setting. The concept has academic roots in frameworks like ReAct, which formalized the "reason-act-observe" cycle. While loop engineering promises greater automation, experts caution about managing token costs and warn against outsourcing understanding—AI can assist, but deep problem comprehension remains essential.

marsbit06/25 14:26

Jensen Huang: Prompts are Becoming Obsolete, Loops are the New Paradigm

marsbit06/25 14:26

MemeCore Token Crashes As ZachXBT Warning Puts Insider Supply Back In Focus

MemeCore's M token experienced a severe crash, plunging over 70% in a single session. This sudden sell-off revived concerns highlighted by on-chain investigator ZachXBT regarding tokens with concentrated insider supply and thin liquidity. The incident underscores the fragility of many memecoins, where large paper valuations can vanish quickly when selling pressure hits illiquid markets. It also brings exchange listing standards into question, as listings can imply a legitimacy not supported by the underlying token structure. The crash serves as a stark warning for traders that social traction and high market capitalization do not guarantee resilient liquidity, emphasizing the risks inherent in high-beta crypto assets.

bitcoinist06/25 14:02

MemeCore Token Crashes As ZachXBT Warning Puts Insider Supply Back In Focus

bitcoinist06/25 14:02

GPT Designs GPT

OpenAI has unveiled its first custom AI chip, Jalapeño, a move signaling a strategic shift beyond being a mere model company. While many see it as a challenge to NVIDIA, its core aim is to control the entire intelligent production pipeline—from models and chips to data centers and energy. The key driver is the evolving competitive landscape: model advantages are shrinking, while the computational gap in areas like cost-per-token, system throughput, and energy efficiency is becoming the true long-term barrier. Jalapeño is primarily an inference chip, targeting the massive and growing "inference tax"—the daily operational cost of generating tokens for services like ChatGPT and APIs. By designing its own hardware optimized for its specific workloads and future product roadmaps (even using AI to aid the chip design process), OpenAI aims to drastically reduce token generation costs and improve system efficiency. This creates a potential flywheel: better models help design better chips, which lower costs for running next-generation models, supporting more users and products, which in turn provides more data to refine future chips. The strategy mirrors Apple’s integrated approach, building a closed loop where hardware, software, and applications are co-optimized. In the long term, OpenAI is not trying to become the next NVIDIA (a supplier of "shovels" to all AI companies) but to own and operate the entire "mine"—selling the end product of intelligence itself. This move marks OpenAI's ambition to evolve from creating the smartest models to controlling the foundational infrastructure of AI production.

marsbit06/25 14:01

GPT Designs GPT

marsbit06/25 14:01

Ethereum Foundation Interim Executive Director Speaks Out: What Is Our Mission?

The Ethereum Foundation's core mission is to ensure Ethereum remains a truly permissionless, censorship-resistant, private, and open infrastructure for large-scale, sovereign coordination. The article clarifies the EF's focus and dismisses irrelevant objectives, such as pursuing institutional popularity or short-term speculation. Its core work centers on eliminating systemic weaknesses. This involves fortifying Ethereum across multiple layers—protocol, access, user, and institutional—against exploitation, control, or surveillance. Key initiatives include minimizing harmful MEV and preventing privileged control over transaction flow, making unconditional privacy a foundational default, ensuring staking remains permissionless and decentralized, and strengthening user-facing access points to uphold autonomy. Concurrently, the EF aims to seize strategic opportunities. These include leading the transition to post-quantum cryptography, achieving a fully verifiable protocol stack, establishing Ethereum as private digital cash, integrating user-owned AI agents with personal wallets, and demonstrating that trusted-neutral infrastructure can competitively handle disintermediated coordination at an institutional scale. The article also addresses recent organizational changes, stating that personnel departures were due to strategic realignment, role fit, or natural evolution. It clarifies the approach to spin-outs, emphasizing that external funding will be provided only for work critical to the EF's mission that reduces Ethereum's dependency without creating new risks or mission drift. Ultimately, the EF is committed to building an enduring, neutral system that reshapes global coordination, focusing relentlessly on the principles of censorship resistance, openness, privacy, and sovereignty (CROP).

链捕手06/25 13:19

Ethereum Foundation Interim Executive Director Speaks Out: What Is Our Mission?

链捕手06/25 13:19

Switching Research Fields in the Final Year of My PhD, I Landed an Offer from OpenAI: My Interview Journey Was Full of 'Surprises'

Yong Zheng-Xin, a final-year PhD student at Brown University, secured an OpenAI offer after pivoting from multilingual models to AI safety research in his last year. In his blog post "Surprising lessons from my research scientist job search," he shares six unexpected insights from his job hunt. He found that often only one or two key papers matter for securing an interview, not the total number. Interview formats were highly diverse, including unexpected rounds on system design and AI agent usage. "Work trials," common in AI startups, involved paid, sometimes week-long collaborative tasks that disrupted other interview preparations. Timing proved crucial, with opportunity windows sometimes lasting less than a month. Return offers for research roles were rare compared to software engineering. Surprisingly, many interview rounds were unrelated to his specific AI safety focus, instead testing broader research competencies. Zheng-Xin concludes that the ability to demonstrate relevant expertise in a new field can unlock opportunities, regardless of one's previous publication record.

marsbit06/25 13:08

Switching Research Fields in the Final Year of My PhD, I Landed an Offer from OpenAI: My Interview Journey Was Full of 'Surprises'

marsbit06/25 13:08

David Villa Officially Appointed as Brand Ambassador for BitradeX

David Villa, the legendary Spanish striker and 2010 World Cup champion, has been officially appointed as the Global Brand Ambassador for BitradeX. This partnership, announced amid the global excitement for the 2026 World Cup, aims to enhance the platform's international brand influence. Villa, a key figure in Spain's golden era of football and the nation's all-time top scorer, embodies a spirit of perseverance, focus, and the relentless pursuit of excellence. BitradeX officials stated that this champion mentality aligns perfectly with their own core values of innovation, long-term development, and global strategic expansion. As a global AI-driven digital asset ecosystem, BitradeX will collaborate with Villa across branding, global market promotion, community engagement, and strategic initiatives. The company believes Villa's widespread influence and trusted international image will serve as a crucial bridge to connect with users worldwide. This collaboration marks a significant step in BitradeX's globalization strategy, with both parties committed to exploring new opportunities in the digital age and writing a new chapter of shared achievement.

链捕手06/25 12:56

David Villa Officially Appointed as Brand Ambassador for BitradeX

链捕手06/25 12:56

STRC 跌破面值，比特币财库实验进入下半场

The price of STRC, Strategy's dividend-paying preferred stock, has fallen below its $100 face value, triggering a re-evaluation of the "bitcoin treasury" corporate model. This highlights a critical tension: the company's asset base consists of high-volatility, non-cash-flow-generating Bitcoin, while its capital structure requires continuous cash payouts for dividends and interest. The decline of STRC signals that market pressure is shifting from asset price volatility to the pricing of the company's financing tools. Strategy's core model involves a three-step conversion: turning equity into Bitcoin exposure, converting Bitcoin holdings into capital market credit, and packaging non-yielding BTC into cash-paying securities like STRC. While Strategy holds a massive 847,363 BTC, the focus is now on cash flow mismatches. The company faces annual preferred stock dividend obligations of approximately $1.7 billion, far exceeding the cash flow from its legacy software business. Its ability to meet these obligations relies on continued access to capital markets. The market is now scrutinizing which of three potential costs becomes untenable first: rising dividend costs to attract investors, dilution costs from issuing more common stock, or the reputational cost of selling BTC—a move contrary to its "hodl" narrative. For the broader crypto market, a constrained Strategy means the potential loss of a predictable, narrative-driven marginal buyer for Bitcoin. The STRC discount serves as a reminder that the longevity of such models depends not just on Bitcoin's price, but also on financing windows, cash reserves, and investor willingness to pay a "trust premium" for the structure.

marsbit06/25 12:43

STRC 跌破面值，比特币财库实验进入下半场

marsbit06/25 12:43

Standard Chartered Bank’s 50-Fold Fantasy: Predicting AAVE to Reach $3,500

Standard Chartered Bank has issued an optimistic research report predicting that the AAVE token could surge 50-fold to $3,500 by 2030. This forecast is based on the projection that the total value locked (TVL) in DeFi will grow 37x to approximately $2.7 trillion, driven by stablecoin expansion and the tokenization of real-world assets (RWA). The bank's model links Aave's potential valuation directly to its protocol revenue, which is primarily driven by net interest margins. The report highlights Aave's current dominant position, noting it captures over 80% of the net earnings ("protocol retained earnings") in the lending sector while holding only about half of its TVL. It also points to the recent launch of the Aave V4 architecture and a healthy revenue stream of $142 million in 2025 as positive fundamentals. Grayscale's separate analysis, applying traditional valuation metrics like DCF, concluded AAVE is currently undervalued. However, the article notes significant challenges. Aave's peer-to-pool lending model suffers from inherent capital inefficiency, with an estimated $52 million annual "deadweight loss" due to idle funds needed for liquidity buffers. This structural flaw was exposed during the April KelpDAO exploit, which locked a WETH pool at 100% utilization for days. Emerging protocols like Morpho, with more efficient point-to-point models, are cited as growing competitive threats. In summary, while institutional forecasts paint a macro picture of massive growth fueled by RWA adoption, Aave's path forward hinges on addressing its core structural limitations and competitive pressures within the evolving DeFi lending landscape.

链捕手06/25 11:41

Standard Chartered Bank’s 50-Fold Fantasy: Predicting AAVE to Reach $3,500

链捕手06/25 11:41

Tidal Investment: We Remain Bullish on the AI Industry Chain, But the Reasons Have Changed

Tidal Investment remains optimistic about the AI industry chain, but the rationale has shifted. The market narrative has changed. While recent large-scale IPOs (e.g., SpaceX) and major fundraising plans by tech giants like Alphabet and Meta have caused some nervousness, this isn't a sign of an AI peak. The focus has moved from the initial question of AI's viability to the sustainability of massive investment cycles. The key players—primarily the major cloud providers—are not slowing down; their capital expenditure (Capex) guidance for 2026 has been increased across the board (e.g., Alphabet to $180B, Amazon to $200B). This investment cycle is proving resilient and difficult to stop. Unlike traditional hardware cycles, current AI Capex is distributed across multiple physical layers—computing, memory, networking, and critically, power infrastructure. Bottlenecks are shifting from chips to elements like electricity, transformers, and cooling systems, which have much longer lead times and cannot be easily pre-built like fiber optics during the dot-com bubble. Supply chain data (e.g., Eaton's 240% YoY data center orders) confirms this broad-based, project-driven expansion. Market concerns are acknowledged but viewed differently. First, while Capex growth currently outpaces revenue growth, raising ROI questions, this mirrors the early scaling phase of cloud computing itself. A change in view would require concrete signals like downward Capex revisions or missed AI product targets, which haven't materialized by mid-2026. Second, comparisons to the 2000 dot-com bust are flawed. That crash was driven by a massive, parallel oversupply of cheap capacity (fiber). The current cycle faces *supply constraints* in critical, capital-intensive physical infrastructure that cannot be overbuilt as easily. In conclusion, the wave of fundraising reflects the next, more complex act of the AI story. Physical bottlenecks and sustained high Capex plans suggest this is not the finale but an ongoing, capital-intensive build-out phase. The script has changed, but the play is far from over.

marsbit06/25 10:36

Tidal Investment: We Remain Bullish on the AI Industry Chain, But the Reasons Have Changed

marsbit06/25 10:36

Tidal Investment: We Remain Bullish on the AI Industry Chain, But for Different Reasons Now

Tidal Investments remains optimistic about the AI industry chain, but the rationale has shifted. The market is concerned about massive concurrent fundraising by tech giants like SpaceX, OpenAI, Alphabet, and Meta, fearing an AI peak. However, the authors argue this signals the next act of AI development, not its end. Capital expenditure (Capex) from major cloud providers (Alphabet, Amazon, Meta, Microsoft, Oracle) continues to surge aggressively into 2026. This investment cycle is more resilient than past hardware cycles due to its scale and complexity. Bottlenecks have shifted from chips to critical physical infrastructure like power grids, transformers, cooling, and data center construction—areas with long lead times and limited capacity for rapid expansion. Supply chain data (e.g., Eaton's orders) confirms substantial, tangible progress. Key market concerns are addressed: 1. **ROI vs. Capex Growth**: While Capex growth outpaces revenue, the authors note cloud giants have historically overcome similar phases through scale. The cycle will only be in danger if Capex guidance is cut, orders are canceled, or AI product demand falters—none of which are currently observed. 2. **Comparison to the 2000 Dot-com Bubble**: Unlike the telecom bubble, where cheap, oversupplied fiber crashed prices, AI infrastructure (especially power) is constrained, customized, and subject to lengthy approvals, making a similar supply glut and crash unlikely. In conclusion, the wave of fundraising reflects the immense, ongoing capital needs for AI's next phase, constrained by slow-moving physical bottlenecks. The AI cycle is not over; the script has simply changed.

链捕手06/25 10:29

Tidal Investment: We Remain Bullish on the AI Industry Chain, But for Different Reasons Now

链捕手06/25 10:29

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