# platform Related Articles

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

OpenAI's "Most Open" Move: Codex No Longer Exclusively Favors GPT

OpenAI has significantly opened up its Codex programming agent by introducing a "model provider" configuration layer that allows users to connect it with various open-source models, not just its proprietary GPT. Through a configuration file or a simple `--oss` command-line flag, Codex can now route requests to local services like Ollama or LM Studio, or to third-party APIs such as Mistral or DeepSeek. This move is seen as one of OpenAI's most "open" steps, potentially lowering costs and enhancing privacy for developers who can run code generation offline. However, integration isn't seamless for all models. Codex primarily uses OpenAI's newer Responses API, while many open-source models rely on the older Chat Completions interface. This creates compatibility issues, especially for advanced features like function calling. The developer community is already building "routing" or adapter layers (e.g., CC Switch, LiteLLM) to translate between these protocols, enabling hybrid setups where GPT handles planning and open-source models handle execution. Analysts interpret this as a strategic shift for OpenAI: from competing solely on model superiority to controlling the platform and interface standards. By making Codex a flexible, pluggable entry point for AI-assisted programming, OpenAI aims to become the central hub in the developer toolchain ecosystem, even as users gain the freedom to switch underlying models.

marsbit3h ago

OpenAI's "Most Open" Move: Codex No Longer Exclusively Favors GPT

marsbit3h ago

Xiaohongshu's Second Great Voyage, This Time Sailing Towards AI

Xiaohongshu's Second Voyage: Navigating Towards AI Since ChatGPT's emergence, Xiaohongshu's founder Mao Wenchao has been acutely aware of AI's potential threat, recognizing that the life advice people seek from chatbots overlaps directly with his platform's core business. Founded in 2013 as a PDF shopping guide for Chinese tourists, Xiaohongshu evolved into a massive community where millions share authentic, personal experiences—from product reviews to travel tips. This vast repository of "I've tried this" human judgment became its most valuable asset. However, the rise of AI, which delivers instant answers, challenges the very need for users to sift through numerous personal notes. Fearing its treasure trove of lived experience could become mere training data for others, Xiaohongshu is proactively adapting. In 2026, it established a dedicated AI division (Dots), launched RED Skill to turn user experiences into usable AI tools, and acquired the AI search product "Diandian." Its investments now extend to AI firms like MiniMax and hardware startups, moving upstream to address needs before they even become search queries. The platform's commercialization strategy is also evolving. With a newly acquired payment license and tools like the AIPS model to track consumer decision journeys, Xiaohongshu aims to seamlessly integrate recommendations with transactions, embedding commerce within AI-generated answers. Yet, a critical tension remains. While building smarter machines to organize and leverage its human experiences, Xiaohongshu must prevent AI from drowning out the authentic, flawed, and trustworthy "I've tried this" voices that built its community. Its core challenge is to harness AI's power without letting the map—the machine's perfect, synthesized answer—replace the territory of genuine human experience. This balance between technological advancement and preserving human trust defines its current journey and its future.

marsbit06/16 01:14

Xiaohongshu's Second Great Voyage, This Time Sailing Towards AI

marsbit06/16 01:14

Apple Also Has to Pay Rent Now

Apple Pays Rent Too: The Two-Way Flow of "Traffic Tax" and "AI Capability Rent" Between Tech Giants For over two decades, Google has paid Apple an estimated $20 billion annually to remain the default search engine on Safari, a "traffic tax" for a critical user entry point. However, in 2026, the direction of this cash flow partially reversed. Apple agreed to pay Google roughly $1 billion per year to license its Gemini AI models, as Apple's own models reportedly struggled with complex tasks. This creates a unique dynamic: Apple acts as the "landlord" in the established search ecosystem, collecting rent from Google for access. Simultaneously, in the emerging AI arena, Apple becomes the "tenant," paying Google for access to cutting-edge AI capabilities it cannot currently match internally. While Apple claims its new models are "distilled" from Gemini outputs and contain "not a drop" of Google's original code, core dependencies remain. Its knowledge base is refined using Gemini's outputs, and its most powerful cloud model runs on Google's infrastructure. Apple has structured the deal as non-exclusive, allowing it to theoretically switch AI suppliers—a hedge against over-reliance. The future hinges on whether advanced AI models become a commodity (cheap and abundant) or remain a concentrated, scarce resource (expensive and controlled by few). Apple is betting on the former, leveraging its massive device ecosystem to be a powerful, choosy customer. If the latter proves true, its bargaining power could erode. This power dynamic is extending to developers. Apple, Google, and WeChat are all pushing for apps to expose their core functions as standardized "actions" or "intents" that their respective AI assistants (Siri, Gemini, WeChat AI) can directly call. The new scarce resource is no longer just app store visibility, but "being selected by the AI." The currency of "rent" has changed from a 30% revenue share to ceding control over how users interact with an app's functions.

marsbit06/15 10:42

Apple Also Has to Pay Rent Now

marsbit06/15 10:42

WeChat Looks to Overturn Qianwen's Table

WeChat is entering the AI agent arena, directly challenging Alibaba's Qianwen. On June 8, WeChat opened its AI ecosystem to developers, allowing integration of its AI assistant into mini-programs. Users will soon be able to access this assistant by swiping right in the main WeChat interface, using natural language to perform tasks like hailing rides, ordering food, shopping, and making payments—essentially enabling actions like "one-sentence ride-hailing or food delivery" within WeChat. This capability targets the core strength of Alibaba's Qianwen, which has leveraged the broader Alibaba ecosystem (including Taobao, Amap, and Fliggy) to transform from a chatbot into a life-service assistant capable of handling real-world transactions. Qianwen has seen significant success, with hundreds of millions of orders processed during promotional events. WeChat's move is significant due to its massive ecosystem of millions of mini-programs covering various daily service scenarios and its over 1 billion monthly active users. This gives WeChat a potentially unparalleled advantage in user reach and habitual use compared to Qianwen's 166 million MAU. Major platforms like Meituan, JD.com, and Ctrip have already announced alliances with WeChat AI. In response, Qianwen announced on June 3 the opening of its platform to third-party agents and brands, aiming to expand its service network and solidify its competitive moat. The article frames this as the beginning of a new phase of intense competition between the two tech giants in the AI agent space, reminiscent of past battles in the mobile internet era.

marsbit06/10 10:29

WeChat Looks to Overturn Qianwen's Table

marsbit06/10 10:29

Microsoft is Afraid of Being Marginalized by AI Giants

Microsoft, once the defining force of the PC era, now faces a familiar challenge in the AI age: the risk of being relegated to a profitable but invisible infrastructure provider. This anxiety was laid bare at Build 2026, where CEO Satya Nadella unveiled a major strategic pivot. The catalyst was a quiet April agreement that dissolved Microsoft's exclusive licensing and cloud-hosting deal with OpenAI, its once-vital partner. This erased Microsoft's key AI moat. With OpenAI and Anthropic defining AI applications and gaining enterprise traction—even within Microsoft's own ranks—Nadella had to answer: without exclusivity, what is Microsoft's role? The answer was a suite of seven in-house AI models, a developer-focused AI workstation (Surface RTX Spark Dev Box), and, most crucially, the Agent 365 platform for enterprise AI governance. The models, notably targeting Anthropic's strengths in coding and enterprise, signal a defensive move. However, the broader strategy is to make the models themselves less decisive. Financially, Microsoft's AI revenue is strong, driven largely by Azure running others' models. Yet its user-facing products like Copilot show weak penetration and engagement. Microsoft earns infrastructure money but lacks direct user mindshare. Nadella's core fear is being "hollowed out." As OpenAI and Anthropic prepare for IPOs and gain financial independence, they may build their own infrastructure, threatening Azure's lucrative AI revenue stream. Microsoft's window is to entrench itself deeper: not as the model creator, but as the indispensable platform for securely deploying, managing, and governing all AI models within the enterprise through Agent 365. Build 2026 revealed Microsoft's bet: in the AI era, the ultimate power lies not in any single model, but in the enterprise "operating system" that controls them. Nadella is determined to ensure Microsoft is the driver of this new era, not just a passenger.

marsbit06/03 11:03

Microsoft is Afraid of Being Marginalized by AI Giants

marsbit06/03 11:03

SaaS Battle Royale: The Survivors Who Win All Share One Common Trait

**Summary** The AI revolution has triggered a "SaaS apocalypse," forcing a brutal market shakeout. The key dividing line is the pricing model. Companies like Snowflake and Datadog, which charge based on consumption (e.g., data processed or compute used), are thriving. AI workloads actively *generate* more demand for their services, fueling growth. Datadog's accelerating revenue is a prime example. Microsoft and Palantir, as platform/ecosystem players, also benefit by acting as essential channels for AI deployment. In contrast, traditional SaaS firms built on per-seat or per-task licensing (e.g., Intuit, Adobe) face direct pressure, as AI threatens to automate the very human tasks their software supports. Companies like Salesforce, a per-seat giant, are caught in the middle. While showing strong AI monetization (e.g., its Agentforce platform) and experimenting with consumption-based "Flex Credits," its stock remains under pressure, illustrating that the market rewards *completed* transitions, not just the intent. The recent Microsoft Build conference underscored key trends: AI is evolving from an assistant to an autonomous "agent," and platform providers like Microsoft are consolidating their control. The market's recovery is highly selective, focused on identifying which companies are "fed by AI" versus "eaten by AI." Future focus will be on the diffusion of this recovery to transforming companies and the real-world adoption data of AI agents like Microsoft Copilot.

marsbit06/03 02:02

SaaS Battle Royale: The Survivors Who Win All Share One Common Trait

marsbit06/03 02:02

活动图片