Taiko 如何引领 Rollup 的去中心化之路？

区块律动2024-08-29 tarihinde yayınlandı2024-08-29 tarihinde güncellendi

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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.

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

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Japan To Recognize Foreign Stablecoins As Electronic Payment Instruments Starting June 1

Japan's Financial Services Agency (FSA) will officially recognize certain foreign trust-issued stablecoins as "electronic payment instruments" under its Payment Services Act, effective June 1, 2026. This amendment excludes qualifying foreign stablecoins from being classified as securities, allowing domestic licensed operators to handle them. To qualify, foreign issuers must be licensed under laws equivalent to Japan's, cooperate with FSA oversight, manage reserve assets under foreign law with proper audits, maintain anti-crime systems, and ensure the stablecoin and its reserves are in the same currency. Eligibility for reliable redemption at face value will be assessed case-by-case. This move expands Japan's stablecoin regulatory framework established in 2022, part of broader efforts to regulate crypto assets. Recent steps include classifying crypto as financial instruments, proposing a 20% flat tax on crypto income, and issuing joint guidance for crypto use in real estate transactions, emphasizing KYC and anti-money laundering checks.

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Japan To Recognize Foreign Stablecoins As Electronic Payment Instruments Starting June 1

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On the Eve of the Tech IPO Boom, Polymarket Joins Forces with NASDAQ to Seize 'Valuation Authority'

At the dawn of a major tech IPO wave, prediction market platform Polymarket is forming an exclusive partnership with Nasdaq Private Market (NPM) to launch contracts predicting the valuations of pre-IPO giants like OpenAI, Anthropic, and SpaceX. This move aims to capture the "valuation adjudication right" in the booming but opaque private market, where accurate valuation data is scarce for retail investors. Facing stiff competition from rival Kalshi, which holds an 89% US market share and full regulatory approval, Polymarket's deal with NPM is a strategic counterattack. NPM provides crucial, real-time secondary market transaction data from employee stock sales to settle the new prediction contracts. In return, Polymarket's market-generated probability data becomes a valuable "institutional signal" for NPM's clients. This follows Polymarket's broader strategy of monetizing its prediction data through partnerships with giants like ICE (Intercontinental Exchange) and Dow Jones, integrating its signals into mainstream financial data feeds and media. The Nasdaq deal specifically targets the lucrative and high-profile arena of pre-IPO tech valuations, potentially raising the entry barrier for competitors in this niche.

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On the Eve of the Tech IPO Boom, Polymarket Joins Forces with NASDAQ to Seize 'Valuation Authority'

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Stop Blindly Clicking Confirm: Ethereum Wants You to Understand What You're Signing

The article criticizes the common practice of "blind signing" in Web3, where users confirm cryptographic transactions without understanding the content, typically presented as unreadable hexadecimal code. It introduces Ethereum's new initiative, "Clear Signing," as a solution aimed at making transaction signatures human-readable. Clear Signing, based on the ERC-7730 standard, allows protocols to provide standardized, structured metadata (like a "translation dictionary") that explains the semantic meaning of a transaction—such as "Swap 1,000 USDC for at least 0.42 WETH on Uniswap V3." This metadata is stored in a public registry for wallets to fetch and display in plain language, moving beyond mere structured data formats like EIP-712. The article clarifies that Clear Signing is not an instant fix but a foundational infrastructure shift that requires widespread adoption by protocols and wallet support. It complements, rather than replaces, existing wallet security features like transaction simulation. The initiative represents a crucial step toward genuine user sovereignty by restoring informed consent, making blockchain accessible to non-technical users and addressing a long-standing security and usability debt in the ecosystem.

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Stop Blindly Clicking Confirm: Ethereum Wants You to Understand What You're Signing

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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.

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