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Moonshot ships 2.8T Kimi K3 open weights; Hugging Face discloses AI-agent intrusion

Moonshot AI launched Kimi K3, the largest open-weight model to date at 2.8T parameters; Hugging Face disclosed a production breach executed by an autonomous AI agent.

2 min read 9 sources

Moonshot AI released Kimi K3 on July 16, the largest open-weight model to date by parameter count, with 2.8 trillion total parameters spread across a sparse mixture-of-experts architecture (SiliconAngle). The model routes each token through 16 of 896 routed experts and introduces two architectural mechanisms - Kimi Delta Attention for hybrid linear attention across long sequences, and Attention Residuals for improved information flow across depth - alongside a 1-million-token context window (MarkTechPost). Two variants ship: K3 Max for general and agentic workloads, and K3 Swarm Max for large-scale parallel processing (Axios). API access is live at $3 per million uncached input tokens and $15 per million output tokens, undercutting most Western frontier models at comparable capability (Fortune). Open weights are scheduled for public release on July 27 under a Modified MIT license (TechCrunch).

Hugging Face disclosed on July 16 that its production infrastructure was breached by an autonomous AI agent system executing thousands of individual actions across a swarm of short-lived sandboxes, with command-and-control staged on public services (Hugging Face Blog). The attack entered through dataset code-execution paths - a class of exposure specific to platforms that mix user-uploaded code with automated data pipelines. A limited set of internal datasets and service credentials were accessed; no public-facing models, datasets, or Spaces were tampered with, and the software supply chain was verified clean. Detection came via an LLM-based anomaly pipeline that flagged the intrusion, then drove forensic agents through more than 17,000 logged attacker events. The company noted that its forensic work was constrained by guardrails on hosted models it initially deployed, and recommended that defenders maintain a capable, self-hosted model vetted for incident response before any incident begins.

Google renamed NotebookLM to Gemini Notebook on July 16, integrating the research tool into the Gemini product line (Google Blog). The product is used by more than 30 million people across 600,000 organizations, according to Google’s announcement (9to5Google). New capabilities include code execution for in-notebook data analysis rolling out to Pro subscribers, and planned availability inside Google Search’s AI Mode (TechCrunch).

Compiled automatically from the linked sources and published without manual editing - a neutral summary of third-party reporting, for information only. Every claim links to its origin. Not original reporting.