English translation is being prepared.
Matched fieldsSummary、Body
←Search results
Search “Agents”
The Ministry of Commerce and the Ministry of Science and Technology plan to add 23 AI technologies, including large models and agents, to the export control catalog
The Ministry of Commerce and the Ministry of Science and Technology issued Joint Announcement No. 48, proposing to add a total of 40 technologies in three major fields—artificial intelligence, biomedicine, and photovoltaics—to the Catalog of Technologies Prohibited or Restricted from Export in China. Among them, the 23 AI items cover large models, agents, computing power clusters, and information processing-related technologies, and interim registration management will be implemented immediately before the catalog takes effect. The author's analysis holds that technologies already in the public domain through open source or published papers may be exempted, but parts where only weights are open-sourced while know-how such as training methods and data engineering remains undisclosed are still within the scope of management; agent services such as Manus and Lovart are in principle unaffected, but three structures may trigger registration: deploying the technology stack to overseas servers, exporting Agent technology to overseas entities, or changing control to an overseas entity.
tificial intelligence, biomedicine, and photovoltaics—to the Catalog of Technologies Prohibited or Restricted from Export in China. Among them, the 23 AI items cover large models, agents, computing power clusters, and information processing-related technologies, and interim registration management will be implemented immediately before the catalog takes effect. The author's analysis holds that technologies already in the public domain through open source or published papers may be exempted, but
Matched fieldsSummary、Body
English translation is being prepared.
Matched fieldsSummary、Body
English translation is being prepared.
Matched fieldsSummary、Body
English translation is being prepared.
Matched fieldsSummary、Body
Vercel introduces durable execution for libfx agents
Vercel CEO Guillermo Rauch announced that libfx's createFxAgent() now supports durability, running locally or in the cloud via files, Postgres, or Vercel Workflows, and compatible with Node.js and Bun. libfx adds a new durable adapter API; on Vercel, with durable workflows and queue infrastructure, reliability comes with 1 line of code; if the process crashes mid-tool-call, it can resume from the breakpoint. This capability will later extend to Pi, OpenCode, and custom harnesses.
Matched fieldsSummary
English translation is being prepared.
Matched fieldsSummary、Body
Anthropic Research: How AI Is Changing Its Internal Hiring and Ways of Working
Anthropic has released an internal research report analyzing AI's impact on the company's hiring and work organization, based on data including hiring, AI usage, output metrics, employee surveys, calendars, and recruiting records, as well as interviews with 17 employees. The report says the share of junior employees in technical departments fell from 21% in early 2025 to 14%, and the share of junior technical roles in hiring dropped from 27% to 9%; by August, interactive AI Agents were working six times as many hours as employees, and per-engineer code commits reached five times the level of six months earlier. Human attention has become the bottleneck on Agent output, employees are shifting toward meta-work of building monitoring and orchestration Agents, and hiring now places more value on autonomy and judgment.
f junior employees in technical departments fell from 21% in early 2025 to 14%, and the share of junior technical roles in hiring dropped from 27% to 9%; by August, interactive AI Agents were working six times as many hours as employees, and per-engineer code commits reached five times the level of six months earlier. Human attention has become the bottleneck on Agent output, employees are shifting toward meta-work of building monitoring and orchestration Agents, and hiring now places more value
Matched fieldsSummary、Body
Vercel officially releases Vercel Shop, with Shopify as the backend
Vercel announced that Vercel Shop is now generally available (GA), and used it to build its own Vercel merchandise store as dogfooding. The product provides a production-grade, blazing-fast Next.js storefront that is agent-ready out of the box, with Shopify powering the backend. Guillermo Rauch also praised Shopify CEO @tobi as a mission-driven, detail-oriented, hands-on engineer-type CEO.
Matched fieldsSummary、Body
How to trust the code produced by AI agents more
Lauren Tan proposes using a four-layer inverted pyramid to increase trust in AI agent code: codebase improvements, static analysis, prose-style rules (such as AGENTS.md and skills), and human review, with investment concentrated in the topmost layer. She suggests handing this post directly to your own bot or agent, and provides steps for installing the tool, creating a new Project, and using commands such as /recall, /poteto-mode, /correct, and /architect to analyze historical commits and feedback.
Lauren Tan proposes using a four-layer inverted pyramid to increase trust in AI agent code: codebase improvements, static analysis, prose-style rules (such as AGENTS.md and skills), and human review, with investment concentrated in the topmost layer. She suggests handing this post directly to your own bot or agent, and provides steps for installing the tool, creating a new Project, and using commands such as /recall, /poteto-mode, /correct, and /architect to analyze historical commits and feedba
Matched fieldsSummary、Body
Arena tracks four signals for agents from six major AI labs
Arena tracked four Agent Arena signals for the best agents from Anthropic, OpenAI, Google DeepMind, Kimi, xAI, and DeepSeek from late June to early October, finding that the largest gap between labs lies in whether users enjoy the experience of using them. On Praise vs Complaint, OpenAI and Anthropic scored +35 points above the leaderboard average, while Moonshot, xAI, and DeepSeek ranged from +5 to +13; on Confirmed Success, the average lab's best model rose from -4 to +14 points within three months, with Anthropic leading at +20 with Claude Opus 5.5 (Max). The Bash Recovery gap narrowed from 34 to 16 points, and Steerability from 19 to 11 points.
Arena tracked four Agent Arena signals for the best agents from Anthropic, OpenAI, Google DeepMind, Kimi, xAI, and DeepSeek from late June to early October, finding that the largest gap between labs lies in whether users enjoy the experience of using them. On Praise vs Complaint, OpenAI and Anthropic scored +35 points above the leaderboard average, while Moonshot, xAI, and DeepSeek ranged from +5 to +13; on Confirmed Success, the average lab's best model rose from -4 to +14 points within three m
Matched fieldsSummary、Body
How OpenAI Designs Failover for Model Providers
For customers such as those in financial services, OpenAI explains the production routing and failover design for critical AI workloads between the direct OpenAI API (1P) and third-party cloud providers (3P). The direct API allows early access to preview models and features, and failover is enabled only when a request can be safely retried and the fallback route meets the requirements—for example, in a payment flow, a timed-out Responses API call for a read-only fraud assessment can be retried before the transaction deadline. In-progress sessions in the Agents API cannot be recovered by switching providers; multi-provider support is a platform capability, while failover is a workflow decision.
(3P). The direct API allows early access to preview models and features, and failover is enabled only when a request can be safely retried and the fallback route meets the requirements—for example, in a payment flow, a timed-out Responses API call for a read-only fraud assessment can be retried before the transaction deadline. In-progress sessions in the Agents API cannot be recovered by switching providers; multi-provider support is a platform capability, while failover is a workflow decision.
Matched fieldsSummary、Body
English translation is being prepared.
Matched fieldsSummary、Body
English translation is being prepared.
Matched fieldsSummary、Body
English translation is being prepared.
Matched fieldsSummary、Body
English translation is being prepared.
Matched fieldsSummary、Body
ElevenLabs Blog: AI Voice Agents Integrate with Salesforce, HubSpot, Zendesk
ElevenLabs released a guide on how to connect ElevenAgents voice agents to CRM and customer service systems such as Salesforce, HubSpot, and Zendesk, enabling bidirectional data operations such as reading customer records, creating tickets, and updating contacts during calls. The article states that with real-time context access, agents resolve inquiries up to 10 times faster than traditional approaches such as scripted chatbots or fixed phone trees, and can automatically log ticket history and reduce manual data entry through in-call and post-call webhooks.
ElevenLabs released a guide on how to connect ElevenAgents voice agents to CRM and customer service systems such as Salesforce, HubSpot, and Zendesk, enabling bidirectional data operations such as reading customer records, creating tickets, and updating contacts during calls. The article states that with real-time context access, agents resolve inquiries up to 10 times faster than traditional approaches such as scripted chatbots or fixed phone trees, and can automatically log ticket history and
Matched fieldsSummary、Body
English translation is being prepared.
Matched fieldsSummary、Body
English translation is being prepared.
Matched fieldsSummary、Body
Meta Releases 816B Open-Source Model Muse Spark Open, Partnering with Apple for Local Execution
Meta has released the open-weight model Muse Spark Open, which uses a MoE architecture with 256 experts, activates about 42B parameters per token, has a context window of 1 million tokens, and supports text, image, video, and audio input but outputs text only. Meta has partnered with Apple to run the approximately 530 GByte four-bit quantized version on two interconnected Mac Studio M5 Ultra machines, distributing computation via the MLX framework and Thunderbolt 5, achieving about 25 output tokens/second at an 8192-token context. Artificial Analysis tests show that it scores 39 on the Intelligence Index, making it the strongest American open-weight model currently available, but it trails MiMo-V2.6-Pro's 46 points and GLM-5.3's 45 points, and ranks last in four Agent tests. The model weights are available on Hugging Face in two versions: 16-bit at approximately 1.6 TByte and four-bit at approximately 530 GByte, with API pricing at $1.25 per million input tokens and $4.25 per million output tokens.
an 8192-token context. Artificial Analysis tests show that it scores 39 on the Intelligence Index, making it the strongest American open-weight model currently available, but it trails MiMo-V2.6-Pro's 46 points and GLM-5.3's 45 points, and ranks last in four Agent tests. The model weights are available on Hugging Face in two versions: 16-bit at approximately 1.6 TByte and four-bit at approximately 530 GByte, with API pricing at $1.25 per million input tokens and $4.25 per million output tokens.
Matched fieldsSummary