2026-08-09 Domingo

Notícias de cripto - Página 395

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.

WeChat Agent Issues a 'Heroic Summons,' Half of the Internet Responds

WeChat AI Agent is on the horizon. The WeChat Open Platform has issued a guide for developers, offering them ways to integrate into the WeChat AI ecosystem. This will enable mini-programs to be discovered and invoked by the AI. Meituan has already announced its integration, allowing users to access services like food delivery through WeChat AI. Other platforms like Ctrip and Tongcheng have followed suit. Furthermore, WeChat is collaborating with major smartphone manufacturers to enable their native AI assistants to perform actions within WeChat, such as initiating calls or sending messages, through a controlled protocol called Agent-to-Agent (A2A). Reports indicate the WeChat AI Agent will be accessible by swiping right on the main interface. It aims to understand user intent within the rich context of chats, groups, and past interactions, then automatically call upon relevant mini-programs to complete tasks like ordering coffee or booking restaurants. This positions it as a potential "super app" with direct access to WeChat's vast ecosystem of services, social connections, and payment systems. Technically, this is a complex endeavor. It requires advanced natural language understanding, a "world model" to predict interactions within mini-programs (UI-Oceanus), multi-model orchestration for cost efficiency, and careful coordination with millions of third-party service providers. Tencent's development follows a "Co-Design" approach, where product teams and the Hunyuan model team collaborate closely, allowing capabilities honed in other AI products (like Yuanbao for chat, ima for search, WorkBuddy for office tasks) to be transferred to the WeChat Agent. Tencent is strategically opting for the A2A protocol over GUI-based automation (which it has blocked in the past), maintaining control over its ecosystem. To manage the immense scale and cost of serving 1.4 billion monthly active users, Tencent is deepening its ties with DeepSeek, known for its cost-effective training, to secure a low-cost inference backbone. The ultimate goal is to solve practical, everyday problems for users within the WeChat ecosystem, moving beyond technical benchmarks to deliver real utility, which Tencent sees as the key to winning in the long-term AI game.

marsbit06/09 04:14

WeChat Agent Issues a 'Heroic Summons,' Half of the Internet Responds

marsbit06/09 04:14

Humanity Loses $31 Million in Attack, Token Price Plummets 90% Due to a Single Private Key

On June 9th, the digital identity project Humanity Protocol suffered a major security breach resulting in over $31 million in losses. According to on-chain analyst Specter, hundreds of wallets holding the project's H token were drained. The attack was confirmed by founder Terence Kwok to be caused by the compromise of a foundation member's private key. As a precaution, users are advised to avoid interacting with Humanity's cross-chain bridge or liquidity pools. The incident caused the H token price to crash over 90%, from around $0.70 to a low of $0.052, wiping its market cap from $2 billion to approximately $35.7 million. The attacker allegedly minted 100 million new H tokens and is selling them for BNB. This breach adds to existing controversies surrounding Humanity Protocol. Founded in 2024, it aimed to verify human users via palm-print biometrics and zero-knowledge proofs. However, a leaked conversation in 2025 revealed that only about 1 million of its 9 million claimed Human IDs had completed biometric verification, suggesting 88% might be bots. Furthermore, the project has faced allegations of being a repackaged product from a Chinese access control vendor, raising privacy and authenticity concerns. Founder Terence Kwok's previous venture, Tink Labs, a hotel smartphone startup that raised $170 million, failed and entered bankruptcy in 2020 after burning through its funding. The current attack highlights the persistent critical issue of private key management in crypto. Unlike smart contract exploits, a private key compromise bypasses all on-chain security mechanisms. With no user compensation plan announced yet, this $31 million breach may be a final blow to the project's credibility, already weakened by previous controversies and a heavily depreciated token.

marsbit06/09 03:40

Humanity Loses $31 Million in Attack, Token Price Plummets 90% Due to a Single Private Key

marsbit06/09 03:40

MicroStrategy Will Not Die in This Downturn: Reflexivity, STRC Anchoring Back to Par, and the Self-Rescue Logic of "Sell Stock, Not Bitcoin"

This article analyzes the recent sharp decline in Bitcoin and MicroStrategy (MSTR), framing it as a targeted "reflexivity" attack. The trigger was MSTR using its cash reserves to buy back convertible notes, raising market concerns about a liquidity crisis. The playbook follows George Soros's principle: market expectations can shape reality. Fears that MSTR might be forced to sell BTC caused panic selling, lowering BTC's price and worsening MSTR's financial ratios, thus reinforcing the negative narrative. The author argues that MSTR's Structured Convertible (STRC), while falling in price, is a floating-rate security that will eventually return to par value (100). The price drop reflects the market demanding a higher yield due to perceived risk, but as a floating-rate instrument, its coupon can adjust, naturally pulling the price back to par over time. This is crucial for MSTR's continued ability to raise funds. The core thesis is that MSTR's best move to counter the attack is to **issue new equity (sell shares)**, not sell its Bitcoin holdings. While selling BTC would solve the immediate cash crunch, it would destroy the company's core investment thesis and premium. It would dilute the BTC per share, likely erase the market premium over its net asset value (mNAV > 1), and worsen its debt-to-asset ratio. Issuing shares while mNAV is high (e.g., 1.25x) allows MSTR to raise cash for reserves without harming shareholder value or the "perpetual accumulation" narrative. It improves the debt ratio and reassures STRC holders, breaking the negative reflexivity cycle. In conclusion, while MSTR could survive this episode even by selling BTC, doing so would fundamentally alter its investment proposition and weaken it for future cycles. The optimal, value-preserving strategy is to sell equity to rebuild reserves and maintain the long-term growth flywheel.

marsbit06/09 03:39

MicroStrategy Will Not Die in This Downturn: Reflexivity, STRC Anchoring Back to Par, and the Self-Rescue Logic of "Sell Stock, Not Bitcoin"

marsbit06/09 03:39

Humanity Loses $31 Million, a Private Key Causes Token Price to Plunge 90%

On June 9th, the digital identity project Humanity Protocol suffered a major security breach resulting in over $31 million stolen from hundreds of wallets holding its H token. The attack was caused by the compromise of a private key belonging to a foundation member, leading the team to advise users against interacting with its bridge or liquidity pools. Following the incident, the price of the H token plummeted by over 90%, from around $0.70 to a low of $0.052, wiping out a significant portion of its market capitalization. The attacker allegedly minted 100 million new H tokens and began selling them for BNB. Humanity Protocol, founded in 2024, aimed to verify human users through palm-print biometrics and zero-knowledge proofs on Polygon CDK. Despite raising $50 million across two funding rounds and achieving a unicorn valuation, the project faced prior controversies. Shortly after its June 2025 token launch, reports emerged that only about 1 million of its 9 million registered IDs had completed biometric verification, suggesting 88% might be bots. Furthermore, allegations surfaced that the project might be a rebranded "shell" of a Chinese access control company, raising concerns about data privacy and authenticity. The project's founder, Terence Kwok, has a controversial business history. His previous venture, Tink Labs, burned through $170 million in funding before collapsing in 2020. The breach highlights the persistent critical risk of private key management in crypto. With no user compensation plan detailed in the initial response, the incident deals a severe blow to trust in a project already struggling with credibility issues.

Foresight News06/09 03:18

Humanity Loses $31 Million, a Private Key Causes Token Price to Plunge 90%

Foresight News06/09 03:18

How to Conduct Deep Research Using Claude's Dynamic Workflows

The article "How to Use Claude's Dynamic Workflows for Deep Research" discusses overcoming the pitfalls of technical research, where both humans and AI can get overwhelmed by information, leading to vague conclusions. It introduces Claude Code's new "Dynamic Workflows" feature, which automatically designs and executes task-specific workflows before starting a task, unlike simpler "planning modes." This approach incorporates validation, result convergence, and adversarial verification from the outset. The core of Dynamic Workflows is six predefined scheduling patterns that address how to decompose tasks and synthesize results: 1. **Classify-and-Act (Routing):** An agent classifies the task and routes it to the most suitable specialist agent for execution. It's precise and efficient but struggles with ambiguous tasks. 2. **Fan-out & Merge:** The task is split into parallel, independent subtasks whose results are later merged. It's fast and isolates contexts but is more expensive and challenging to synthesize. 3. **Adversarial Verification:** Multiple "challenger" agents critique a worker agent's conclusion, requiring majority approval. This counters confirmation bias and self-assessment errors but relies on verifiable facts. 4. **Generate & Filter:** Multiple agents generate many candidate solutions, which are then filtered against a rubric to output only the best. It fosters diversity but depends heavily on the filter's quality. 5. **Tournament:** Multiple agents compete on the same task, with pairwise comparisons eliminating contestants over rounds to select the best. This offers stable relative judgment but is complex. 6. **Loop:** An agent iteratively attempts a task, learning from errors and adjusting until a stop condition is met. It handles tasks with unknown scope but risks infinite loops without proper design. The author compares their own custom deep-research system, which involved multi-agent analysis and deduplication but lacked goal-oriented convergence, to Claude's built-in workflow. The official workflow adds critical layers: initial problem decomposition, credibility assessment of sources, cross-agent voting to delete weak conclusions (not just averaging), and output tightly focused on the user's original goals and actionable recommendations. This structurally addresses common AI issues like goal drift, premature stopping, context pollution, and output bias. In summary, Dynamic Workflows represent a shift from smarter single conversations to a structured research process, compressing what used to require many dialogues into 3-4 interactions, albeit at higher token cost. The author notes remaining challenges for their specific domain (blockchain research): the need for fact-based verification over official documentation, depth in truly novel interdisciplinary thinking, the practical validation of proposed solutions, and tailoring information density to the audience.

marsbit06/09 03:07

How to Conduct Deep Research Using Claude's Dynamic Workflows

marsbit06/09 03:07

When LPs Teach Me Investment with Doubao: A Self-Narrative of a Private Equity GP Switching Careers

When LPs Use Doubao to Teach Investing: A Transition Story of a Private Equity GP AI is making life increasingly difficult for small private equity fund managers, as a former GP of an offshore dollar fund reveals. The fund, managing tens of millions in US stocks, outperformed the Nasdaq but struggled with fundraising. Its traditional Cayman SPC/BVI structure failed to attract major Asian LPs, who now prefer Hong Kong LPF or Singapore VCC frameworks. The rise of AI-powered quantitative strategies has further squeezed the space for funds like his, which relied on subjective, discretionary investing. AI tools have leveled the information playing field, empowering LPs—often high-net-worth individuals, entrepreneurs, or family offices—to analyze investments themselves using chatbots like Doubao. This has eroded trust in GPs' expertise, leading to more frequent challenges over investment decisions and even withdrawals, especially during market rallies when retail investors sometimes outperform funds. Friction arises not necessarily from AI's capabilities but from how LPs use it. Many rely on conversational AI for validation rather than rigorous analysis, sometimes receiving misleading or hallucinated advice. While AI democratizes research, effective investing still requires discerning real insight from plausible-sounding output. Ultimately, AI is unlikely to fully replace GPs. Asset management remains a trust-based service. However, the industry must adapt. The future may see "human私募" (private equity) learning from AI and focusing more on providing value beyond pure analysis—perhaps by mastering the emotional intelligence and trust-building that machines cannot replicate.

Odaily星球日报06/09 02:39

When LPs Teach Me Investment with Doubao: A Self-Narrative of a Private Equity GP Switching Careers

Odaily星球日报06/09 02:39

Wang Chuan: After Investing in Storage Stocks and Seeing a Thirty-Fold Return, How to Remain Unanxious (Part 7) - A Quarter-Century Cycle

Wang Chuan: Reflections on Investment Anxiety and Market Cycles After Observing a 30x Gain in a Storage Stock (Part 7) – A Quarter-Century Cycle This article examines the cyclical nature and inherent risks in technology hardware investments, using the storage and semiconductor sectors as examples. It criticizes the misleading practice of "annualized" Net Dollar Retention (NDR) rates, where short-term growth is extrapolated unrealistically. A key concept explored is "reflexivity" – demand driven by panic, exploration, and liquidity during market booms, which can vanish just as quickly when conditions reverse. This reflexivity exists both in product demand and among speculative stock buyers, creating powerful feedback loops that inflate prices during upturns and exacerbate crashes during downturns. The author highlights a major risk for hardware sectors: unlike assets with defined cycles (e.g., Bitcoin's halving), there's no guarantee of a swift recovery post-crash. Companies like Micron, Intel, and Cisco took roughly a quarter-century to surpass their 2000 highs, enduring drawdowns exceeding 80%. This is attributed to the "bullwhip effect" in supply chains, where demand collapses instantly but过剩产能 persists, and a migration of narrative-driven capital. High-valuation stories吸引 speculative funds during growth phases, but these funds quickly depart for the next hot narrative once growth slows, leaving behind stronger companies with much lower valuations. The piece warns of dangerous mental models formed during bull markets: 1) equating current strong demand with perpetual high growth, and 2) believing that making fast, large profits is easy. Citing巴菲特, the author notes that easy money undermines rationality, likening speculators to Cinderella at a ball with a clock that has no hands. The current phase presents an asymmetric risk-reward scenario: potential for further gains exists, but the downside risk is an 80%+ drawdown and a multi-decade wait for breakeven, which reflexive speculators cannot tolerate. The hypothetical investor "老王" (Lao Wang), who achieved a 30x return, is used to illustrate potential pitfalls. Leverage could lead to a wipeout during a sharp correction. Even without leverage, ingrained beliefs in easy money would likely lead him to double down after losses, expecting a quick rebound. Instead, he might face a protracted decline, depleting his resources through frantic trading as the high-growth narrative fades. The conclusion references Schopenhauer, comparing those who have seen multiple market cycles to an audience seeing the same magic trick repeatedly—once the illusion is understood, its power is gone.

marsbit06/09 02:16

Wang Chuan: After Investing in Storage Stocks and Seeing a Thirty-Fold Return, How to Remain Unanxious (Part 7) - A Quarter-Century Cycle

marsbit06/09 02:16

US Stocks Too Expensive? This Top CIO Scoured the Globe and Found 5 Stocks More Attractive Than NVIDIA

Summary: Main Street Research CIO James Demmert maintains his bullish 8,100 target for the S&P 500 but argues that greater opportunities now lie overseas. He identifies five international stocks with superior valuations poised to benefit from the AI revolution, suggesting international markets will outperform the US for years. Key Recommendations: 1. **ASML (Netherlands):** A foundational chip manufacturing technology provider, offering crucial AI exposure and geographic diversification. Demmert's top long-term pick. 2. **HSBC (UK/Asia):** A global bank with a 9x P/E ratio, better growth prospects than US peers like JPMorgan, and strong Asian presence. 3. **Siemens Energy (Germany):** A direct play on global power grid expansion driven by AI, crypto, and EV electricity demand. 4. **BHP Group (Australia):** A "hidden AI play" and "second derivative" of the trend due to massive copper demand for data centers. Trades at a 16x P/E. 5. **AstraZeneca (UK):** An undervalued healthcare stock with a strong pipeline (18x P/E, >20% growth), expected to benefit from AI's impact on medicine. Core Thesis: International outperformance is driven by both attractive valuations and a major policy shift. While the US tightens fiscal policy, Europe and Japan are launching unprecedented stimulus, reigniting growth. Demmert recommends allocating 45% of a portfolio internationally, citing excessive US investor conservatism as a key mistake.

marsbit06/09 02:11

US Stocks Too Expensive? This Top CIO Scoured the Globe and Found 5 Stocks More Attractive Than NVIDIA

marsbit06/09 02:11

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