# Integration Related Articles

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

From Banning Doubao to Embracing Honor: Why Did WeChat Suddenly 'Change Its Face'?

The article explores the sudden shift in WeChat's strategy towards AI assistants from mobile phone manufacturers, transitioning from strict opposition to active collaboration. For over a year, WeChat fiercely resisted attempts by phone AI assistants (like ByteDance's Doubao in late 2025) to control its features via GUI automation ("simulated clicking"), citing security and data control concerns. This stance created a significant barrier for system-level AI integration. Now, Tencent has initiated A2A (Agent-to-Agent) partnerships with major phone brands like Honor, Xiaomi, OPPO, and vivo. This model allows a phone's system AI (e.g., Honor's YOYO) to parse a user's voice command and send a structured request directly to WeChat's own internal AI agent via secure APIs. WeChat then executes the action (e.g., sending a message) and returns the result. The article attributes Tencent's "change of face" to strategic pressure. While leading in social app usage, Tencent trails rivals like ByteDance and Alibaba in standalone AI app popularity. WeChat, with its vast mini-program ecosystem, is Tencent's key asset for an AI comeback. The upcoming WeChat AI agent aims to handle tasks like booking and payments within the app. However, phone system assistants remain the primary AI entry point for most users. The A2A collaboration allows Tencent to extend WeChat's AI reach to this crucial system layer while maintaining control over its core functions and data. For phone manufacturers, embracing A2A is a pragmatic move. The GUI route proved unviable due to WeChat's blocks. A2A offers a compliant path to integrate a vital service, enhancing their AI assistants' usefulness. It allows them to focus on developing their own AI ecosystems for other services while cooperating on WeChat access. The collaboration is framed as a mutual, strategic necessity: Tencent gains a distribution channel, and manufacturers gain a key functionality. The partnership relies on a "dual authorization" mechanism for security, requiring both user and app consent for each action. While questions about long-term data privacy practices remain, experts note A2A is more secure and compliant than GUI automation. Ultimately, this cooperation is seen as a tentative, calculated truce. Tencent's long-term goal is to make WeChat an AI-powered "service OS." Phone manufacturers aim to make their system AI the central user interface. Their paths may converge or clash in the future, but for now, the A2A deal represents the opening chapter in the battle for the AI-era user入口, driven by necessity and strategic calculus on both sides.

marsbit06/06 01:48

From Banning Doubao to Embracing Honor: Why Did WeChat Suddenly 'Change Its Face'?

marsbit06/06 01:48

From 'Old Dogs' to 'New Darlings': How AI is Revaluing Old Infrastructure, from Dell to Nokia

"Old Dogs" Become AI's New Darlings: Revaluing Legacy Infrastructure The AI investment narrative is shifting. Beyond the spotlight on core chipmakers like Nvidia, a new wave of interest is rising for legacy tech companies—Dell, HPE, Nokia, Cisco, Corning, Western Digital—once labeled as slow-growth, outdated stories. This resurgence stems from AI's evolution from model development to real-world deployment, creating massive demand for physical infrastructure. As AI moves into data center construction and enterprise adoption, the focus turns to who can actually build and deliver complex systems. These established players hold decades of experience in supply chains, integration, networking, and enterprise delivery—assets now critical for scaling AI. The revaluation can be grouped into three key infrastructure areas: 1. **Servers & Integration (e.g., Dell, HPE):** They are becoming essential system integrators, transforming GPUs into full-scale AI servers with networking, power, and cooling, then delivering them to clients. Strong recent earnings and AI-specific revenue/order growth for Dell and HPE underscore this shift. 2. **Networking & Connectivity (e.g., Corning, Nokia, Cisco):** As AI clusters grow, high-speed data transfer becomes paramount. Corning benefits from fiber demand for data center links, Nokia is exploring AI-integrated wireless networks (AI-RAN), and Cisco sees surging orders for data center switches—all critical for efficient AI operations. 3. **Storage (e.g., Western Digital, Seagate):** The AI data explosion requires vast capacity. Beyond high-speed memory (HBM), there's growing need for high-capacity HDDs to store training data, logs, video, and cold/archival data cost-effectively. This revaluation, however, is not a blanket endorsement. True reassessment requires concrete proof: AI-driven orders and revenue growth, upward revisions to company guidance, and sustainable improvements in profit quality, not just top-line sales. In essence, AI is not turning all old tech firms into high-growth stocks; it is selectively re-pricing the "old assets" of companies that are mission-critical for building the new AI infrastructure, transforming their legacy capabilities into renewed growth engines.

marsbit06/05 00:55

From 'Old Dogs' to 'New Darlings': How AI is Revaluing Old Infrastructure, from Dell to Nokia

marsbit06/05 00:55

ChatGPT Might Be Disappearing Soon

OpenAI announced at its "Intelligence at Work" event that its coding assistant, Codex, will be fully integrated into the ChatGPT app within weeks. This move marks a strategic shift from a conversational AI (Chat) towards a unified "agentic" platform capable of execution. Codex, originally launched to compete with Anthropic's Claude Code, has grown rapidly to 5 million weekly active users, with 20% being non-developers like analysts and designers. Its enterprise revenue now constitutes 40% of OpenAI's total. The integration is the first step in creating a super-app combining ChatGPT (interface), Codex (execution engine), and the Atlas browser (web access). OpenAI also unveiled new Codex features: specialized Agent plugins for six professional roles, an "Annotations" tool for direct document editing, and a "Sites" function to turn work into shareable web apps. Internally, this reflects a power shift; the Codex team now leads core product strategy. While the ChatGPT brand remains for its vast user base, the platform's future is focused on autonomous agents that perform tasks, not just chat. The article notes that competition with Claude Code pushed OpenAI's development, with Codex competing on cost-effectiveness and accessibility rather than raw coding quality. It concludes that the essence of "ChatGPT" is evolving from a chatbot into an AI agent platform, with the name potentially becoming a legacy symbol of its original function.

marsbit06/03 23:52

marsbit06/03 23:52

Crypto.com Exchange Integrates with TradingView for Direct Multi-Asset Trading

Crypto.com Exchange has integrated with TradingView as an official broker, enabling its users to trade directly through TradingView's charting platform by linking their exchange accounts. This integration establishes Crypto.com Exchange as a multi-asset platform on TradingView, allowing qualified traders to execute trades on a wide range of assets directly from their charts. The available assets include traditional stocks and commodities, pre-IPO perpetual contracts, and on-chain assets like tokenized real-world assets (RWAs). The move combines Crypto.com's high-performance trading infrastructure with TradingView's advanced analytics, allowing users to perform market analysis and place trades within a single platform. Eric Anziani, President and COO of Crypto.com, stated that the integration provides a seamless experience, enabling instant transition from analysis to execution with access to deep liquidity, real-time data, and innovative asset classes. This builds upon Crypto.com Exchange's existing market data presence on TradingView, offering enhanced access for traders who utilize the platform for technical analysis and research.

TheNewsCrypto06/03 15:49

Crypto.com Exchange Integrates with TradingView for Direct Multi-Asset Trading

TheNewsCrypto06/03 15:49

Chatbot has been burning money for three years, is it still the 'New Continent' of the AI era?

For years, the AI industry has been guided by a singular "map" — the belief that the AI era's "new continent" would be found in the Chatbot, a super-app akin to the mobile internet's super-apps. This belief was fueled by ChatGPT's explosive 2022 debut. However, three years of heavy investment reveal a different reality: the Chatbot-as-ultimate-entry-point model is struggling. The core issue is economic. Chatbots defy traditional internet economics. Unlike apps with near-zero marginal cost, each AI query consumes significant, expensive compute. More users mean higher costs, not profits. OpenAI, despite ~900M weekly active users, reportedly loses money. The expected network effects and data flywheels that power internet giants are weak in Chatbots, as one user's interactions don't improve another's experience. Monetization is a major hurdle. The subscription model faces low conversion rates, especially in China where users expect AI to be free. The "free + ads" model also struggles. Chatbot interactions often lack commercial intent, and inserting ads compromises the trust essential for an answer engine. Perplexity's minimal ad revenue and subsequent pivot away from ads highlight this difficulty. Switching between Chatbots is easy, making user loyalty low and competition a potential race to the bottom on price. Data suggests the standalone Chatbot's growth is slowing, and user engagement (avg. ~6 mins/day) pales compared to apps like TikTok. The product form itself is limiting; studies show nearly half of interactions are simple Q&A, trapping AI's potential in a passive, single-turn "cage." A contrasting, more successful path is emerging, exemplified by Anthropic. With over 85% of its ~$30B annualized revenue from enterprises, it focuses on AI as a productivity tool, not a companion. The rise of AI Agents (like OpenClaw) and the integration of AI into existing workflows (e.g., Google's AI Overviews, Apple Intelligence in OS) signal a shift. The future may not be a dominant Chatbot app, but AI embedded seamlessly into social apps, operating systems, and hardware — a capability-layer revolution, not a new distribution container. The conclusion is clear: the old "map" centered on a standalone Chatbot super-app is leading to a dead end. To find the true valuable "continent" of the AI era, the industry must update its navigation to prioritize deep integration, practical utility, and sustainable economics over a generic conversation window.

marsbit06/02 10:35

Chatbot has been burning money for three years, is it still the 'New Continent' of the AI era?

marsbit06/02 10:35

From "Selling Cloud" to "Selling Token": Telecom Operators Fully Join the AI Battlefield

From selling cloud services to tokens, operators fully join the AI battlefield. Major Chinese telecom operators—China Telecom, China Mobile, and China Unicom—are launching AI token packages for personal, family, and enterprise use. This marks a shift from selling traditional services like voice and data to offering tokens as a new standard unit for AI service consumption. Operators are transforming into AI service integrators, moving beyond their role as cloud providers. They are building an integrated structure that combines models, computing power, applications, unified billing, and security. By bundling various AI models, pooling heterogeneous computing resources, developing industry-specific agents, and leveraging their existing billing systems, they aim to lower entry barriers and simplify AI adoption for businesses. The token model is becoming a key packaging method for AI services, moving beyond developer markets to the mainstream. Operators are positioning themselves as the essential infrastructure for the AI era, aiming to make AI a billable, manageable, and reliable utility similar to electricity or network services. However, challenges remain in ensuring model quality, cost reduction, and achieving sustainable commercial success. The ultimate goal is to make AI a measurable and scalable production factor for industries.

marsbit06/01 10:13

From "Selling Cloud" to "Selling Token": Telecom Operators Fully Join the AI Battlefield

marsbit06/01 10:13

From Parallel Finance to Mainstream Finance: The On-Chain Securities Era Ushers in a Historic Window

From Parallel Finance to Mainstream: The Dawn of On-Chain Securities For over a decade, the crypto industry has operated as a parallel financial system with its own currencies, markets, and assets—from Bitcoin and ICOs to DeFi, NFTs, and memecoins. Despite building a robust internal ecosystem, a wall has separated it from the traditional financial world. That barrier is now crumbling. The industry's first act was one of internal evolution: ICOs streamlined fundraising, DeFi recreated financial services on-chain, and layer-2 networks competed for scalability—all within the crypto bubble. While innovative, this cycle remained closed, with capital and users circulating internally, leading to volatile boom-bust cycles. Even Bitcoin ETFs, while attracting Wall Street capital, merely provided a channel to buy crypto assets without bridging the systems. The next, larger narrative is Real-World Assets (RWA) moving on-chain. This involves tokenizing stocks, bonds, funds, and future cash flows. Blockchain can compress the complex traditional processes of trading, settlement, clearing, and custody into a seamless, automated network operating in seconds. This shift is creating a new financial gateway: the native crypto securities broker. This entity will combine functions of an exchange, broker, bank, and custodian into a unified global financial operating system. Consequently, the next major battleground won't be the "public chain wars" focused on speed and cost, but the competition to build the financial infrastructure capable of hosting high-quality, liquid real-world assets. Access to global equities, index funds, or stakes in companies like SpaceX could erase the boundary between crypto and traditional finance, unlocking a market orders of magnitude larger than crypto's current valuation. In summary, after years of creating a separate financial world, crypto's next decade will be defined by its integration into the existing global financial system, marking the true beginning of its largest growth story.

marsbit06/01 07:22

From Parallel Finance to Mainstream Finance: The On-Chain Securities Era Ushers in a Historic Window

marsbit06/01 07:22

Agentized OS: It's Not About AI, It's About the Foundation

The Agentic OS: Beyond AI, It's About the Foundational Stack In 2026, major operating systems like Android, iOS, HarmonyOS, and Windows are entering the "Agentic" era, integrating proactive AI assistants deeply into the system layer. However, the real competition lies not in the flashy AI features showcased at events, but in the three-layer foundational stack that enables them: the system-level AI Runtime, proprietary/controllable chips, and the on-device/cloud model matrix. The AI Runtime acts as the central scheduler, managing model inference, resource allocation, and exposing capabilities to apps. Controllable chips (e.g., Apple Silicon, Google Tensor, Huawei Kirin) are crucial for deep hardware-software co-optimization, determining the efficiency and experience limits of on-device Agents. The on-device/cloud model matrix provides the "intelligence," with proprietary, chip-optimized small models (like Gemini Nano, Apple's ~3B model) handling daily tasks locally for low latency, privacy, and reliability, while cloud models tackle complex requests. Deep synergy between these three layers enables key Agent differentiators: ultra-low latency and power efficiency, genuine "on-device first" privacy, access to system-level personal context across apps, and reliable performance as a system service even offline. OS vendors with strong integration across this stack (like Apple, Google, and Huawei) build a deeper moat. Beyond this core stack, long-term competitiveness depends on variables like structured App integration (e.g., App Intents/AppFunctions) for reliable multi-step workflows, and robust privacy frameworks that build user trust. This shift towards Agentic OS extends beyond phones and PCs to IoT, cars, and XR glasses via existing multi-device ecosystems. The race is won not in a keynote, but through generations of meticulously co-developed chips, models, and system software.

marsbit05/27 10:19

Agentized OS: It's Not About AI, It's About the Foundation

marsbit05/27 10:19

AI Server Power Supply Undergoes Major Transformation, ADI Bets Big with a $1.5 Billion Investment

**Title: AI Server Power Supply Undergoes Major Shift as ADI Makes $1.5 Billion Bet** **Summary:** Analog Devices Inc. (ADI) has announced a definitive agreement to acquire Empower Semiconductor in an all-cash transaction valued at approximately $1.5 billion. This move highlights the critical and growing importance of advanced power delivery technologies in the era of data-intensive AI computing. The acquisition targets Empower's key technologies that address fundamental power challenges in high-performance AI data centers: **Integrated Voltage Regulators (IVR)**, which integrate dozens of discrete components into a single IC for high density and nanosecond transient response; **ECAP Silicon Capacitors (SiCaps)**, offering ultra-low ESL/ESR for high-frequency filtering; **Vertical Power Delivery (VPD)** architecture, which reduces transmission distance and losses; and the overarching **FinFast** technology platform. ADI's strategy aims to fill the "last millimeter" gap in power delivery from the board level to directly beneath the processor die. The deal follows ADI's recent product launches and strategy focused on AI data center power, including µModule solutions, SiC switches, and 800V high-voltage DC systems. The article details the industry-wide trend towards higher integration and VPD to manage soaring GPU/accelerator power demands, now reaching kilowatt levels per card. It examines the three evolutionary stages of AI power: traditional lateral power delivery, VPD, and ultimately substrate-integrated voltage regulators (SIVR). Competitors like Infineon, MPS, Vicor, and TDK are also advancing VPD solutions, while companies like Murata, Samsung Electro-Mechanics, and Rohm are leading in silicon capacitor development. In conclusion, as AI server power consumption escalates dramatically, technologies like IVR, SiCaps, and VPD are becoming essential for efficient power delivery within constrained spaces. ADI's significant investment signals an urgent industry need for innovation in this domain.

marsbit05/22 00:38

AI Server Power Supply Undergoes Major Transformation, ADI Bets Big with a $1.5 Billion Investment

marsbit05/22 00:38

USDC Begins Nested Issuance, Coinbase Launches Custom Stablecoin Branding Service

Coinbase has launched its "Custom Stablecoins" platform, enabling businesses to offer branded stablecoins. The first client is Flipcash, a social payments app, which has introduced USDF. USDF is a Solana-based stablecoin, pegged 1:1 to USDC, and is designed to serve as a stable pricing and settlement unit for Flipcash's user-created community currencies. This move shifts the focus of stablecoins from being standalone assets or investment products to becoming embedded payment and settlement components within broader applications. For businesses like Flipcash, the core need is not to become a stablecoin issuer, but to integrate stable, reliable digital cash functionality—handling pricing, payments, and settlements—without managing the complex underlying infrastructure of issuance, reserves, on-chain contracts, fiat on-ramps, and compliance. Coinbase's platform provides this infrastructure as a service, positioning the exchange as a stablecoin infrastructure provider. While USDC remains the foundational reserve asset, the branded token (e.g., USDF) offers applications a tailored, user-facing financial tool. This development highlights a potential path for stablecoins to become ubiquitous backend utilities in social, gaming, and e-commerce applications, though it also brings significant regulatory and operational complexities associated with handling real user funds.

链捕手05/21 15:07

USDC Begins Nested Issuance, Coinbase Launches Custom Stablecoin Branding Service