# Сопутствующие статьи по теме AI

Новостной центр HTX предлагает последние статьи и углубленный анализ по "AI", охватывающие рыночные тренды, новости проектов, развитие технологий и политику регулирования в криптоиндустрии.

Ministry of Industry and Information Technology Seeks Opinions on 121 Industry Standards Including 'Artificial Intelligence Model Context Protocol'

The Ministry of Industry and Information Technology (MIIT) has issued a notice soliciting public opinions on 121 industry standard proposals, including the "Artificial Intelligence Security Governance—Model Context Protocol Application Security Requirements." This move represents a significant step in China's efforts to establish standardized AI underlying protocols and enhance safety regulation frameworks. The core focus of the consultation is on the application security of the Model Context Protocol, aiming to address protocol compatibility and data security risks during multimodal interactions, long-text processing, and cross-platform invocations of large models through standardized technical specifications.

marsbit03/26 03:32

Ministry of Industry and Information Technology Seeks Opinions on 121 Industry Standards Including 'Artificial Intelligence Model Context Protocol'

marsbit03/26 03:32

Delphi Labs Founder: Two Weeks Deep in China's AI, Shenzhen Hardware Shocks Me, Software Valuations Scare Me

Delphi Labs co-founder José Maria Macedo spent two weeks in China meeting AI founders, VCs, and public company CEOs. His key takeaways: - **Hardware ecosystem in Shenzhen is impressive**, with systematic reverse-engineering of Western products and rapid iteration cycles. Companies like Bambu Lab are highly profitable and scaling fast. - **Software ecosystem is weaker than expected**. Chinese open-source models are strong, but closed-source models lag behind Western counterparts. GPU access remains constrained, and revenue gaps are significant (e.g., Anthropic’s $6B ARR vs. Chinese model companies at tens of millions). - **Founder profiles are highly accomplished** (top universities, Big Tech experience) but often lack rebellious, original vision. The education and VC systems favor execution over true innovation. - **Valuation bubbles exist** at both early and late stages. Some private AI companies are valued at 400x ARR, far exceeding Western multiples. Humanoid robotics is also overheating, with many pre-revenue companies targeting high-valuation IPOs. - **Information asymmetry favors Chinese founders**, who are highly informed about Western markets and tech trends. Many are building globally first, combining Chinese engineering with Western go-to-market strategies. Macedo believes the real alpha lies in finding non-traditional founders who break the "resume template" optimized by local VCs.

marsbit03/26 03:16

Delphi Labs Founder: Two Weeks Deep in China's AI, Shenzhen Hardware Shocks Me, Software Valuations Scare Me

marsbit03/26 03:16

OpenAI Bets on 'Robot Army': 23-Year-Old Prodigy Wins Favor from Sam Altman

While OpenAI adjusts its video strategy, Sam Altman is setting his sights on the more ambitious field of "multi-agent systems." According to The Wall Street Journal, OpenAI has secretly invested in Isara, an AI startup founded by 23-year-old researchers Eddie Zhang and Henry Gasztowtt. Despite being established only in June last year in San Francisco, Isara has already recruited over a dozen top researchers from Google, Meta, and OpenAI itself, forming a highly skilled technical team. Isara’s core vision is to develop a system that enables thousands of AI agents to collaborate efficiently. While individual AI assistants are powerful, they often struggle with large-scale industrial challenges such as biotech R&D or complex financial modeling. Isara aims to solve this by creating a framework where diverse AI agents can communicate, align goals, share data, and tackle interconnected problems—functioning like a coordinated "robot army." This multi-agent approach is seen as a critical step toward Artificial General Intelligence (AGI). OpenAI’s endorsement signals industry recognition of distributed intelligence. In biopharma, the system could simulate thousands of protein-folding pathways, with specialized agents identifying patterns. In finance, it could perform real-time stress tests using global market data. Led by young innovators, this shift suggests the next breakthrough in AI lies not in building larger models, but in enabling smarter collective intelligence.

marsbit03/26 02:32

OpenAI Bets on 'Robot Army': 23-Year-Old Prodigy Wins Favor from Sam Altman

marsbit03/26 02:32

The Crisis for Small and Medium-Sized Hotels: Booking's CEO Criticizes Google Gemini and ChatGPT for 'Unfair Practices'

The CEO of Booking Holdings, Glenn Fogel, has issued a strong warning that Google's Gemini and OpenAI's ChatGPT are using their dominant market positions to push small and medium-sized hotels to the brink. Fogel argues that while traditional search allowed users to browse multiple options, AI assistants now often provide only one to three algorithmically filtered "best" recommendations in response to travel queries. This leaves independent hotels, which lack big data resources and dedicated AI optimization teams, effectively invisible in search results. Although Fogel has previously criticized EU regulations like the Digital Markets Act (DMA), he now supports antitrust scrutiny of AI-generated search results. He advocates for audits to ensure that large AI platforms do not unfairly prioritize their own services or those of major corporations that pay high fees. In response to this competitive threat, Booking is investing an additional $700 million by 2026 to develop in-house AI marketing tools and a "Connected Trip" program. The initiative aims to help smaller hotels structure their data to improve visibility across AI platforms, while emphasizing that complex customer service—such as handling flight delays or cancellations—remains a core strength of Booking’s business.

marsbit03/26 02:21

The Crisis for Small and Medium-Sized Hotels: Booking's CEO Criticizes Google Gemini and ChatGPT for 'Unfair Practices'

marsbit03/26 02:21

Kimi, Zhipu, Douban Gather at an Encryption Hackathon: What Did AI Developers Build on Monad?

Monad's "Rebel in Paradise AI" Hackathon, held on March 21, 2026, brought together leading LLM providers like Kimi, Zhipu AI, and Doubao to explore AI agent development on its high-performance parallel EVM blockchain. The event focused on three key areas: Agent Payments, Smart Markets, and Application Innovation, with over $40,000 in prizes and resources. Winning projects included OpenAlice (Grand Prize), a locally run trading agent with transparent workflows; Orbit AI (NVIDIA Special Award), a decentralized AI cloud using satellite GPU clusters; and Kimi-swarm, an open-source multi-agent IDE. Other notable winners were Libra, a Git-like system for machine-written code, and Anime AI Studio, a one-stop anime short film generation agent. The hackathon highlights Monad's strategic push into AI, leveraging its high throughput (10,000+ TPS), low latency, and low-cost infrastructure to support autonomous agent economies. Monad's existing initiatives, like the AI Blueprint program and x402 payment guides, further position it as a key infrastructure for AI and DeFi integration, enabling agents to execute transactions, settle payments, and operate as independent economic entities on-chain.

marsbit03/26 02:15

Kimi, Zhipu, Douban Gather at an Encryption Hackathon: What Did AI Developers Build on Monad?

marsbit03/26 02:15

GitHub Announces Default Use of Copilot User Data for AI Model Training Starting April 24

GitHub has announced an update to its repository policy, effective April 24, 2026, allowing the use of user interaction data to train its AI models. The data collection will include users of Copilot Free, Pro, and Pro+, covering model inputs and outputs, code snippets, contextual information, repository structures, and chat logs. According to GitHub’s Chief Product Officer Mario Rodriguez, the move aims to enhance the accuracy and security of the model’suggestions, with internal Microsoft tests already showing improved acceptance rates. The policy follows an opt-out model, meaning affected users must manually disable data sharing in their privacy settings, sparking debate within the developer community over data ownership and the definition of private repositories. Copilot Business, Enterprise, and educational users are currently exempt due to contractual terms. GitHub defended the change as consistent with industry practices adopted by companies like Anthropic, JetBrains, and Microsoft. However, the inclusion of private repository code in training sets challenges conventional notions of privacy. This shift reflects a broader industry trend where leading AI providers are turning to user interaction data as high-quality public code resources diminish. It signals GitHub’s continued transition from an open-source platform to a closed-loop AI training ecosystem and highlights growing tensions between data compliance and AI model advancement.

marsbit03/26 01:39

GitHub Announces Default Use of Copilot User Data for AI Model Training Starting April 24

marsbit03/26 01:39

AI2 Releases Fully Open-Source Web Agent MolmoWeb: Controlling Web Pages Using Only "Vision"

AI2 has released MolmoWeb, a groundbreaking, fully open-source web agent that operates solely by analyzing screenshots, marking a significant leap in vision-driven web navigation. Unlike traditional agents that rely on DOM, MolmoWeb captures and interprets visual data to make decisions—such as clicking, scrolling, or typing—making its process transparent and robust. Despite its compact size (4B and 8B parameters), MolmoWeb performs impressively: it scores 78.2% on the WebVoyager benchmark, nearing OpenAI’s proprietary o3 model (79.3%), and achieves up to 94.7% success with multiple attempts. It even surpasses Anthropic’s Claude3.7 in UI element localization. AI2 also released MolmoWebMix, a massive open dataset with 36K human-browsing tasks, over 2.2M screenshot-QA pairs, and GPT-4o-verified synthetic data. The model and data are fully available on Hugging Face and GitHub under Apache 2.0, promoting transparency and collaboration in AI development. Challenges remain in complex instructions, logins, and legal compliance.

marsbit03/26 01:39

AI2 Releases Fully Open-Source Web Agent MolmoWeb: Controlling Web Pages Using Only "Vision"

marsbit03/26 01:39

"Borrowing a Chicken to Lay Eggs"? Apple Secures Google Gemini License: Crafting the Strongest On-Device AI Through Model "Distillation"

Apple has reportedly secured full access to Google's Gemini model, not for simple API integration, but to perform "model distillation"—a technique that allows Apple to train smaller, more efficient on-device AI models by learning from Gemini’s advanced reasoning processes. This approach enables Apple to develop localized AI systems that operate entirely on-device, improving speed and safeguarding user privacy. The distilled models are expected to power a significantly upgraded Siri in iOS 27, enabling deeper interaction, complex question-answering, document understanding, and practical task execution—all without requiring cloud connectivity. While leveraging Google’s model in the short term, Apple continues to develop its own foundational AI models internally, adopting a dual strategy of near-term collaboration and long-term independence. This move represents Apple’s effort to balance cutting-edge AI performance with its strict privacy and efficiency standards, potentially reshaping the landscape of on-device artificial intelligence.

marsbit03/26 01:08

"Borrowing a Chicken to Lay Eggs"? Apple Secures Google Gemini License: Crafting the Strongest On-Device AI Through Model "Distillation"

marsbit03/26 01:08

Google DeepMind Releases Lyria 3 Pro: AI Music Transitions from "30-Second Previews" to Full Songs

Google DeepMind has launched Lyria 3 Pro, a significant upgrade from the previous version released just six weeks prior. The key improvement is the extension of AI-generated music from 30 seconds to 3 minutes, alongside a new "structure-aware" capability. This allows the model to understand and construct a song's internal composition—such as intros, verses, choruses, and bridges—based on user's text, image, or video prompts, marking a shift from a simple generator to a creative tool. While competitors like Suno and Udio have offered similar features since early 2025, Google's entry into this competitive space is notable due to its vast distribution reach via the Gemini ecosystem. The model supports multiple languages, includes vocals and instruments, and automatically adds SynthID watermarks for AI content identification. Access is tiered for paid Gemini users (AI Plus, Pro, Ultra), with daily generation limits, while free users remain on the 30-second Lyria 3. It is also available for developers via API and for enterprises through Vertex AI. However, copyright concerns regarding training data remain unresolved, similar to ongoing industry disputes.

marsbit03/26 00:58

Google DeepMind Releases Lyria 3 Pro: AI Music Transitions from "30-Second Previews" to Full Songs

marsbit03/26 00:58

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