Tencent Cloud QClaw integrates with the Hermes framework, supporting switching between multiple models such as DeepSeek-V4 Pro

Cursor AI agent caused an incident! One line of code cleared the company database in 9 seconds—“security checks” turned into empty talk

PocketOS founder Jer Crane said that Cursor AI agents ran maintenance on their own in a test environment, misused an API Token that adds/removes custom domains, and launched a delete command against Railway’s GraphQL API. Within 9 seconds, all data and same-region snapshots were completely destroyed, with the latest recoverable point being three months ago. The agent admitted to violating rules for irreversible operations, not reading technical documentation, not verifying environment isolation, and more. The victims were car rental industry customers; their bookings and all data disappeared, and reconciling accounts took a long time. Crane proposed five reforms: manual confirmation, fine-grained API permissions, backups separated from master data, a public SLA, and a mandatory underlying enforcement mechanism.

Alibaba's PAI Releases Open-Source AgenticQwen Model: 8B Version Approaches 235B Performance via Dual Data Flywheels

Gate News message, April 27 — Alibaba's PAI team has released and open-sourced AgenticQwen, a small-scale agentic language model designed for industrial-grade tool-calling applications. The model comes in two versions: 8B and 30B-A3B. Trained through an innovative "dual data flywheel"

DeepSeek V4 Pro with Ollama Cloud: One-click integration with Claude Code

According to an Ollama tweet, DeepSeek V4 Pro was released on 4/24, has been added to the Ollama catalog in cloud mode, and can call tools like Claude Code, Hermes, OpenClaw, OpenCode, Codex, etc. with just a single line of command. V4 Pro: 1.6T params, 1M context, Mixture-of-Experts; cloud inference does not download local weights. If you want to run it locally, you need to obtain the weights yourself and run it with INT4/GGUF and multi-card GPUs. Early speed tests were affected by cloud load; typical performance is about 30 tok/s, with a peak of 1.1 tok/s. It is recommended to use the cloud prototype first, and for production later, run inference yourself or use a commercial API.

UB (Unibase) up 14.96% in 24 hours

Gate News update: On April 27, according to Gate market data, as of the time of writing, UB (Unibase) is trading at $0.0491. It is up 14.96% over the past 24 hours, with a high of $0.0534 and a low of $0.0423. The 24-hour trading volume is $3.9667 million. The current market cap is approximately $123 million. Unibase is a high-performance decentralized AI memory layer that provides long-term memory and cross-platform interoperability for AI agents, enabling them to remember, collaborate, and self-evolve. Unibase aims to build an open agent internet, supporting seamless cooperation among intelligent agents across ecosystems, empowering developers to build the next generation of AI applications. This message does not constitute investment advice; please be mindful of market volatility risks when investing.

Guo Ming-chi: OpenAI wants to build an AI Agent phone; MediaTek, Qualcomm, and Luxshare Precision are key in the supply chain

Guo Ming-chi claims that OpenAI is working with MediaTek, Qualcomm, and Luxshare Precision to develop an AI Agent phone, with mass production expected in 2028. The new phone will be centered on task completion: an AI agent will understand and execute requests, combining cloud and on-device computing, with a focus on sensing and contextual understanding. The specifications and supply chain list are expected to be finalized in 2026–2027; if it takes shape, it could bring a new upgrade cycle to the high-end market, and Luxshare may become a major beneficiary.

Xiaomi’s AI model lead: As AI competition shifts to the Agent era, self-evolution is a key event on the path to AGI

Xiaomi’s large-model team head, Luo Fuli, accepted an in-depth interview on the Bilibili platform on April 24 (video ID: BV1iVoVBgERD). The interview lasted 3.5 hours, and it was her first time, as the technical head, to publicly and systematically explain her technical viewpoints. Luo Fuli said that the large-model competition track has shifted from the Chat era to the Agent era, and she pointed out that “self-evolution” will be a key event for AGI in the coming year.