2026-08-12 Quarta

Notícias de cripto - Página 541

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 Are the Most Believers in AGI Buying NVIDIA Put Options?

The article analyzes the significant, market-moving 13F filing for Q1 2026 by Situational Awareness LP (SALP), a fund managed by former OpenAI researcher Leopold Aschenbrenner. While Aschenbrenner is a prominent believer in the accelerated arrival of AGI and has built the fund as a focused bet on AI infrastructure, the filing revealed large new put option positions (totaling billions in notional value) on key AI/semiconductor names like Nvidia, SMH ETF, Broadcom, and AMD. The article argues this is not a bearish turn on AI but a sophisticated hedging strategy. Given the macro backdrop in late March (rising oil prices, inflation concerns, higher-for-longer interest rates), the fund is managing volatility in its high-beta, high-valuation portfolio of AI infrastructure plays (like Bloom Energy, CoreWeave, Core Scientific). The puts act as "insurance" against a potential systemic pullback in the AI trade. Simultaneously, SALP maintained or added to core long positions in companies tied to power, data centers, compute, and storage—the "bottlenecks" expected to capture AI capital spending. It trimmed or exited some Q1 winners (e.g., Lumentum) and reduced leverage (e.g., selling CoreWeave calls), suggesting a rotation from crowded, high-momentum trades towards assets with clearer long-term fundamental pathways. The key takeaway is an evolution in the AI investment theme: from a broad, linear rally to a more discerning, "show-me-the-money" phase. The focus shifts from simply buying the AI narrative to identifying companies that can convert capex into tangible revenue, while actively managing portfolio risk in a volatile macro environment. The strategy reflects a move from unilateral bullishness to "offense with defense."

marsbit05/20 12:23

Why Are the Most Believers in AGI Buying NVIDIA Put Options?

marsbit05/20 12:23

AI Saved a Group of New Energy Investors

The article "AI Saves a Group of New Energy Investors" details a remarkable turnaround in the green energy investment sector, driven by its convergence with artificial intelligence infrastructure. After a prolonged downturn marked by valuation slumps and funding cold spells since 2022, the sector has experienced a dramatic resurgence in 2026. This shift is attributed to new policies, particularly the "AI-Energy Synergy" national strategy, which mandates green power and energy storage systems for new large-scale computing centers. This redefines green electricity and storage from traditional manufacturing into core, indispensable assets for AI's operational backbone, creating a new narrative where "computing power equals electricity, and green power equals assets." This paradigm change is reflected in surging market performance. Power stocks like Datang Power have seen massive gains, and green energy ETFs have recorded significant capital inflows. The IPO market is also active, with companies like Sige New Energy listing successfully. Investment and financing have accelerated sharply, with major expansion projects and large-scale IPOs like China Resources New Energy's record-breaking offering. Notably, some top projects have seen valuations rebound by approximately 60%. The article highlights that the previous industry trough became a prime investment window. With AI-driven demand predicted to create massive power shortfalls (e.g., a projected 55GW gap for data centers), sectors like energy storage, grid upgrades, and green power are seeing explosive growth. Investors are now prioritizing areas like power management, large-scale storage, virtual power plants, and supporting technologies like liquid cooling—the "pick-and-shovel" plays of the AI infrastructure boom. Examples like KKR's highly successful investment in cooling company CoolIT Systems underscore the lucrative opportunities. In conclusion, the integration with AI has sparked a fundamental revaluation of new energy assets. For investors who endured the sector's低谷, a harvest season has arrived, with the broader investment upswing seemingly just beginning.

marsbit05/20 11:53

AI Saved a Group of New Energy Investors

marsbit05/20 11:53

Learn Codex with the "Morning Briefing": Six Replicable Levels of Use

This article introduces a "Morning Briefing" as a simple, progressive framework for learning to effectively use Codex (an AI assistant), moving from basic information gathering to a more sophisticated, autonomous work partner. It outlines six actionable levels: **Level 1: Basic Information Query.** Start by simply asking Codex to check your Slack, Gmail, and Calendar to summarize what needs your attention today. **Level 2: Personalization with an Agents File.** Create a persistent file containing your default preferences for the briefing's format and content, so it's consistently useful. **Level 3: Automation.** Set the briefing to run automatically every weekday morning, creating a reliable starting point for your day. **Level 4: Project-Specific Briefings.** Instead of one overwhelming summary, create separate, dedicated threads for different projects (e.g., a launch, recruitment), each with its own focused briefing. **Level 5: Drafting Follow-Up Actions.** Elevate the briefing from a summary to an action starter by having it draft replies, prepare meeting notes, or highlight stalled decisions—ready for your review. **Level 6: Building a Memory System (Vault).** Integrate a knowledge vault (a structured file system) where important recurring information (project statuses, key people, decisions) is stored and updated. The briefing consults this vault to provide richer context and learns over time. The approach's strength is its incremental nature. Each level teaches a core Codex capability (connectors, personalization, automation, project context, assisted work, persistent memory) within a familiar, practical workflow, avoiding overwhelming theoretical concepts. It transforms a simple daily check-in into a personalized, evolving work operating system.

marsbit05/20 11:16

Learn Codex with the "Morning Briefing": Six Replicable Levels of Use

marsbit05/20 11:16

Can Alibaba Cloud Rewrite Itself?

Over the past five months, Alibaba Cloud's MaaS (Model as a Service) revenue has surged 15x, marking a strategic overhaul where the company is shifting its 17-year-old system designed for "humans using cloud" to a new paradigm centered on "Agents consuming Tokens." At its recent summit, Alibaba Cloud announced a full-stack upgrade encompassing "chip-cloud-model-inference," all optimized for AI Agents. Key launches include the new AI product portal "QianWen Cloud," hyper-node servers powered by the in-house AI chip Zhenwu M890, and the latest flagship model, Qwen3.7-Max. Senior VP Liu Weiguang described this as building "China's largest AI factory," where chips are raw materials, the cloud is the workshop, models are machines, and the inference platform is the assembly line, with Tokens as the final product. The company is now emphasizing its chip strategy, unveiling the Zhenwu M890 and a two-year roadmap for future chips. With over 560,000 chips deployed across 400+ clients, Alibaba Cloud aims to control the marginal cost per Token, mirroring Google's integration of TPU and Gemini for optimal cost-performance. The cloud infrastructure itself is being rewritten. Traditional cloud interfaces are being transformed into standardized, Agent-callable Skills. A new scheduling logic focuses on "task scheduling" over "resource scheduling" to handle the unpredictable, elastic workloads of Agents. Liu noted that AI applications now automatically provision cloud resources, with one customer's daily automated provisioning equaling two weeks of manual work. For models, the focus has shifted from conversational prowess to execution capability. Qwen3.7-Max demonstrated this by autonomously writing and optimizing a production-grade AI compute kernel for the new Zhenwu M890 chip over 35 hours, achieving a 10x performance improvement. The underlying Bailian platform was upgraded for efficiency, and it maintains an open ecosystem, hosting third-party models. This restructuring extends beyond technology to sales, organization, and metrics. Alibaba Cloud has established dedicated MaaS sales teams, separated from traditional IaaS, with new KPIs focusing on high-quality Tokens that solve real problems, the number of core business systems integrated with models, and the efficiency of Agent task completion. The underlying bet is clear: AI represents an opportunity orders of magnitude larger than before. Despite the uncertainty, Alibaba Cloud is aggressively rebuilding its entire system, betting on an AI-driven future where Tokens could become its largest product line.

marsbit05/20 10:22

Can Alibaba Cloud Rewrite Itself?

marsbit05/20 10:22

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