# Standard Related Articles

HTX News Center provides the latest articles and in-depth analysis on "Standard", covering market trends, project updates, tech developments, and regulatory policies in the crypto industry.

A Chip Company Releases AIDC Energy Storage Certification Standards. Why NVIDIA? Computing Power Reshapes Power Supply Logic. Who's in the Lead and Who's Left Out?

NVIDIA has released a "Battery Energy Storage System Self-Certification Guide," setting strict technical standards for energy storage systems specifically for AI data centers (AIDC). The guide focuses solely on certifying the Power Conversion System (PCS), not the batteries, with 10 mandatory performance metrics and 12 validation tests requiring real-world and simulation comparisons. Key requirements include rapid dynamic response to AI workloads, high-frequency system telemetry, and detailed electromagnetic transient models. The move is driven by the extreme and fluctuating power demands of next-generation AI hardware. Modern AIDCs require energy storage systems to act as intelligent, controllable grid assets, not just passive backup, to manage instantaneous, massive power load shifts that traditional UPS systems cannot handle. This redefines the competitive landscape for energy storage providers, shifting focus from capacity and cost to advanced control capabilities and system integration. While the market potential is significant—with forecasts of hundreds of GWh in new demand by 2030—the certification creates a high barrier to entry. It requires proven PCS delivery volumes and credible plans for rapid capacity scaling, favoring established, well-resourced players. Early movers like Fluence (partnering with Siemens) and several Chinese companies have secured projects ahead of the standard, but new entrants must now navigate this rigorous, costly, and time-intensive certification process to compete in the AIDC energy storage market.

marsbit06/23 04:11

A Chip Company Releases AIDC Energy Storage Certification Standards. Why NVIDIA? Computing Power Reshapes Power Supply Logic. Who's in the Lead and Who's Left Out?

marsbit06/23 04:11

AI Agents Also Need 'Credit Checks': ERC-8126 is Filling the Gap in On-chain Trust

The article discusses ERC-8126, a proposed standard designed to address the lack of trust and verification for AI Agents operating on-chain. While ERC-8004 provides AI Agents with a basic on-chain identity (answering "Who are you?"), it does not guarantee trustworthiness. ERC-8126 aims to fill this gap by establishing a verification layer (answering "Are you reliable?"). It standardizes how independent verification providers can assess an agent's associated risks across five key areas: Token/Contract Verification (ETV), Media Content Verification (MCV), Solidity Code Verification (SCV), Web Application Verification (WAV), and Wallet Verification (WV). These providers generate a standardized risk score (0-100) and proofs based on their checks, without acting as a single authoritative certifier. This allows wallets, marketplaces, dApps, and other agents to consume these risk signals—for example, to display warnings, filter listings, or make interaction decisions. The standard also incorporates concepts like Private Data Verification (PDV) and Zero-Knowledge Proofs (ZKP) to allow verification without exposing sensitive underlying data. Positioned alongside ERC-8004 (Identity) and ERC-8183 (Commerce for agents), ERC-8126 represents a step toward building a verifiable and accountable infrastructure for the emerging on-chain AI Agent economy, shifting trust assessment from purely user-based judgment to standardized, consumable signals.

marsbit06/22 13:54

AI Agents Also Need 'Credit Checks': ERC-8126 is Filling the Gap in On-chain Trust

marsbit06/22 13:54

Apple Re-invented Image Compression with AI: Same Quality, One-Third the File Size

Apple’s PICO: An AI-Powered Image Codec That Cuts File Size by Two-Thirds at Equal Perceived Quality In 2025, JPEG AI became the first international standard for learned image compression. However, it, like most codecs, still prioritizes mathematical metrics like PSNR over true perceptual quality—what the human eye finds pleasing. Apple researchers have introduced PICO (Perceptual Image Codec), a neural codec designed to optimize for human perception. It tackles key practical challenges: 1) Speed: A novel "one-shot context model" accelerates entropy encoding without sacrificing compression efficiency. 2) Artifacts: A dedicated TextFidelity loss preserves text clarity, and a TilingArtifact loss eliminates color seams between image tiles processed in parallel. 3) Control: It avoids the "hallucinations" common in GAN-based perceptual models. In a large-scale human evaluation (74,925 comparisons), PICO achieved the same perceived quality as standards like AV1, VVC, and JPEG AI while using only 30-43% of the bitrate. It also outperforms other learned perceptual codecs by 20-40%. Remarkably, it runs in 230ms (encode) and 150ms (decode) on an iPhone 17 Pro Max. While less efficient on synthetic graphics, PICO represents a significant shift from optimizing mathematical scores to directly targeting human visual experience, making high-quality perceptual compression practical for consumer devices. The work builds on expertise from WaveOne, whose team joined Apple and previously advanced neural video compression.

marsbit05/30 02:47

Apple Re-invented Image Compression with AI: Same Quality, One-Third the File Size

marsbit05/30 02:47

2026 New Policy Interpretation: The "Mutual Pursuit" of Intelligent Agents and AI Terminals, and the Three Major Value Reconstructions in the AIoT Industry

In May 2026, China's national ministries released two pivotal policy documents that jointly establish a strategic "dual-track" framework for the AIoT industry. The "Intelligent Agent Standardized Application and Innovation Development Implementation Opinions" defines the "soul"—positioning intelligent agents as core AI products. The "Artificial Intelligence Terminal Intelligence Grading" national standard defines the "body"—establishing a four-tier capability ladder (L1 to L4) for AI hardware. This synchronized policy approach is globally unique, moving beyond market-led (US) or risk-focused (EU) models. It frames AIoT as a new type of "intelligent infrastructure," comparable to electricity or the internet in historical significance. The core analysis identifies a value evolution from IoT 1.0 (connection) to AIoT 4.0 (collaboration, represented by the forward-looking L4 level). This "L4" signifies a paradigm shift: from users operating tools to delegating tasks to agent-like devices ("Intelligent Action of All Things"). The article outlines three strategic paths for companies: becoming Standard Definers, Scenario Integrators (focusing on 19 specified application areas), or Infrastructure Builders. A critical 18-24 month window is identified for strategic positioning. A "Four Levers" strategy is proposed: leveraging Standards (L-level certification), leveraging Scenarios (deep vertical focus), leveraging Open Source (for cost reduction and ecosystem influence), and leveraging Momentum (engaging in global protocol ecosystems). In conclusion, these policies are a starting gun for a decade-long industrial transformation, shifting the industry narrative from "Intelligent Connection of All Things" to "Intelligent Action of All Things," with companies needing to choose their赛道and execution strategy decisively.

marsbit05/12 11:56

2026 New Policy Interpretation: The "Mutual Pursuit" of Intelligent Agents and AI Terminals, and the Three Major Value Reconstructions in the AIoT Industry

marsbit05/12 11:56

From KYC to KYA, Is It Time to Give AI Agents Their Own 'ID Cards'?

Titled "From KYC to KYA: Is It Time to Issue 'Identity Cards' for AI Agents?", this article discusses the emerging concept of Know Your Agent (KYA) as AI agents become increasingly autonomous. In Agent-to-Agent (A2A) scenarios, where agents execute contracts, payments, and trades without human intervention, the lack of a shared identity standard creates risks like unauthorized transactions, fraud, and accountability gaps. KYA acts as a trust layer to verify an agent's origin, authority, and accountability. The need for KYA is most critical outside centralized platforms (like Google or Coinbase), such as in decentralized exchanges (DEX), A2A payments, and merchant payments. Several key players are building KYA infrastructure: - **ERC-8004**: A proposed Ethereum standard that issues a unique AgentID as an NFT, building on-chain identity, reputation, and validation systems. - **Visa TAP**: Visa's solution issues agent identity credentials, with transactions verified via triple signatures (legitimacy, delegator, payment method). - **Trulioo**: Extends its KYC/KYB compliance infrastructure using a Digital Passport for Agents (DAP), issued after verifying both the developer and user, and refreshed per transaction. - **Sumsub**: Focuses on post-issuance real-time verification, detecting agent anomalies during transactions using its existing compliance systems. Regulatory bodies are also acting. The EU AI Act mandates operator identification in logs for high-risk AI systems, the US NIST prioritizes agent identity management standards, and Singapore has released a national AI governance framework. Similar to how the 2019 FATF Travel Rule impacted crypto exchanges, possessing KYA infrastructure may determine market entry in the AI agent era. The market is expected to segment rather than produce a single winner, with success depending on integrations with merchants, payment networks, and KYC client bases.

marsbit05/10 05:45

From KYC to KYA, Is It Time to Give AI Agents Their Own 'ID Cards'?

marsbit05/10 05:45

When AI's Bottleneck Is No Longer the Model: Perseus Yang's Open Source Ecosystem Building Practices and Reflections

In 2026, the AI industry's primary bottleneck is no longer model capability but rather the encoding of domain knowledge, agent-world interfaces, and toolchain maturity. The open-source community is rapidly bridging this gap, evidenced by projects like OpenClaw and Claude Code experiencing explosive growth in their Skill ecosystems. Perseus Yang, a contributor to over a dozen AI open-source projects, argues that Skill systems are the most underestimated infrastructure of the AI agent era. They enable non-coders to program AI by writing natural language SKILL.md files, transferring power from engineers to all professionals. His project, GTM Engineer Skills, demonstrates this by automating go-to-market workflows, proving Skills can extend far beyond engineering into areas like product strategy and business analysis. He also identifies a critical blind spot: while browser automation thrives, agent operations are nearly absent from mobile apps, the world's dominant computing interface. His project, OpenPocket, is an open-source framework that allows agents to operate Android devices via ADB. It features human-in-the-loop security, agent isolation, and the ability for agents to autonomously create and save new reusable Skills. Yang believes the value of open source lies not in the code itself, but in defining the infrastructure standards during this formative period. His work validates the SKILL.md format as a portable unit for agent capability and pioneers new architectures for agent operation in API-less environments. His design philosophy prioritizes usability for non-technical users, ensuring the agent ecosystem can be expanded by practitioners from all fields, not just engineers.

marsbit04/13 01:29

When AI's Bottleneck Is No Longer the Model: Perseus Yang's Open Source Ecosystem Building Practices and Reflections

marsbit04/13 01:29

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