# 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.

You'll Be Surprised How Much WeChat's Architecture Differs from Telegram's

An article compares the core architectural philosophies of WeChat and Telegram, highlighting fundamental differences in data storage, monetization, and developer ecosystems. **Data Storage:** Telegram offers unlimited, synchronized cloud storage for seamless access across all devices. In contrast, WeChat stores chat history locally on each device, requiring a manual migration process for transfer and tethering desktop sessions to an active smartphone. **Features & Ecosystem:** Telegram's open Bot API allows for easy, free bot creation, while WeChat's massive ecosystem of over 4.8 million "mini-programs" operates within a closed, curated, and more regulated platform. Commenting also differs: Telegram uses integrated discussion threads for channels, whereas WeChat relies on pre-moderated comments for official accounts and separate chats for interaction. **File Sharing & Payments:** Telegram supports large file transfers (up to 4GB for Premium), while WeChat limits most files to 200MB. A key divergence is in payments: WeChat Pay is deeply integrated into daily life and commerce in China, whereas Telegram lacks a comparable built-in fiat payment system, focusing instead on third-party bots and crypto. **Analysis:** The comparison reveals two distinct models: WeChat is a tightly integrated, closed ecosystem deeply embedded in the real economy, while Telegram prioritizes open protocols, flexible data handling, and low barriers for developers. An added perspective notes that WeChat's fusion of messaging and payments in a single interface without end-to-end encryption for chats potentially broadens the attack surface, raising security questions as more functions converge.

cryptonews.ruYesterday 12:20

You'll Be Surprised How Much WeChat's Architecture Differs from Telegram's

cryptonews.ruYesterday 12:20

Shocking: OpenAI Fully Open-Sources Codex Harness

OpenAI has open-sourced the core framework of Codex, called "Harness," under an Apache-2.0 license. This move allows developers to deeply integrate AI agents into their own applications and workflows, moving beyond the limitations of generic chat interfaces. The Harness is the underlying execution system that manages an AI agent's complete lifecycle: understanding tasks, maintaining memory, using tools, handling failures, and requesting human approvals. OpenAI demonstrated that optimizations to the Harness alone can dramatically boost a model's performance, tripling scores on a benchmark while using significantly fewer tokens. The release includes three key components: a CLI tool (`codex exec`) for automated tasks, official SDKs (TypeScript/Python) for programmatic control, and the `app-server` for embedding agents directly into products. This enables features like persistent state, real-time event streaming, and human-in-the-loop controls. Early adopters showcase its versatility beyond coding. Examples include a tax preparation system that cut processing time by one-third, Cisco's platform for building apps with natural language, and a demo logistics dashboard where agents analyze data and propose actions within the existing interface. This paradigm shift grants developers full control over the user interface, context, tools, and security boundaries. AI becomes an invisible assistant within specialized software, rather than a separate chatbot. By open-sourcing the engine behind its powerful agents, OpenAI aims to spark a new wave of native, deeply integrated AI applications.

marsbit08/21 08:01

Shocking: OpenAI Fully Open-Sources Codex Harness

marsbit08/21 08:01

Tokenization Scale Soars to $4.3 Billion, But Why Did Securitize Incur a $5.5 Million Loss?

Securitize's first quarterly report post-IPO reveals a paradox: while its tokenized assets under management hit a record $4.3 billion (up 16% YoY) and platform trading volume surged 147% to $5.3 billion, total revenue fell 5% to $14.4 million. Tokenization revenue specifically dropped ~12% to $7.8 million, leading to an adjusted EBITDA loss of $5.5 million. CFO Francisco Flores explained that most trading volume is not yet monetized, with the majority of tokenization revenue still coming from one-time projects like new protocol integrations. In contrast, asset servicing revenue, a more recurring stream, grew slightly to $6.6 million. The company has lowered its full-year revenue guidance to $70-$80 million from an initial projection of $110 million. Industry experts note this highlights a structural challenge for the tokenization sector. Scaling assets on-chain doesn't automatically scale a profitable business model. Current implementations often rely on costly, customized projects for each new asset or jurisdiction. The future, they argue, lies in building standardized infrastructure that generates recurring "infrastructure revenue" from post-issuance activities like compliance, distributions, and secondary trading—similar to enterprise software. Analysts caution against misinterpreting high trading volumes as indicative of a mature fee-based model, as Securitize's broad volume metric includes many non-monetized actions. The key test for the industry is whether adding billions in new assets can generate sustainable revenue without constant new custom projects.

marsbit08/20 10:06

Tokenization Scale Soars to $4.3 Billion, But Why Did Securitize Incur a $5.5 Million Loss?

marsbit08/20 10:06

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