Security

A coalition of tech giants and organizations urged U.S. policymakers to protect open-weight AI models. They argue open access democratizes AI, boosts competition, and prevents vendor lock-in, drawing parallels to the open-source software movement. The letter also reframes security discourse, suggesting open models enable better threat detection, and defends AI distillation as a legitimate research technique. The signatories advocate for avoiding premature restrictions and fostering broader AI access.

APEC economies have issued the “Chengdu Statement on AI,” emphasizing security, data protection, and IP rights while supporting open-source development. This signals a shift towards greater government oversight of AI, particularly as China promotes accessible open-source models. The statement aims to foster dialogue on cybersecurity and data sharing, reflecting a growing global focus on balancing AI innovation with robust security measures.

China has warned of a “back-door” security risk in Anthropic’s Claude Code AI tool, citing potential transmission of sensitive user data to remote servers. This warning, issued by China’s Ministry of Industry and Information Technology, follows accusations of Alibaba attempting to extract Anthropic’s AI capabilities. Despite official restrictions, many in China reportedly access U.S. AI tools, prompting companies like Alibaba to ban their employees from using Anthropic products. The situation underscores rising U.S.-China tech competition and the critical need for AI security.

Alibaba has banned employees from using Anthropic’s AI tools due to security risks and allegations of intellectual property theft. This follows Anthropic’s accusation of Alibaba attempting an “AI distillation attack” and their terms prohibiting use by entities from “adversarial nations” like China. Alibaba now mandates the use of its own AI assistant, Qoder, amidst scrutiny of potential code loopholes in Claude and efforts by Anthropic to close access through proxies.

Next-generation AI assistants, from Apple and Qualcomm, will offer advanced capabilities for task management and app navigation. However, development prioritizes user control and security, incorporating explicit approval checkpoints for sensitive actions like financial transactions. This “human-in-the-loop” model limits AI autonomy, ensuring users retain final decision-making authority and data privacy through granular access controls and integration with secure partner services. This controlled approach aims to mitigate risks and foster trust in agentic AI.

Microsoft is adjusting its security leadership. Charlie Bell is moving to an individual contributor engineering role, while Hayet Gallot, formerly of Google Cloud, returns to lead Microsoft’s security division. This change occurs as Microsoft faces investor scrutiny over growth, particularly in the generative AI era. Gallot’s appointment signals a strengthened focus on security, with Ales Holecek also shifting roles within the security team. These moves are part of broader efforts to capitalize on the AI boom.

Businesses are rapidly adopting AI agents, but safety protocols lag. This creates risks like security breaches and accountability issues. A Deloitte report reveals a significant governance gap, with most organizations lacking strong oversight. “Governed autonomy,” with clear boundaries and human gatekeeping for high-risk actions, is proposed as a solution. Prioritizing visibility and control over speed is key for secure and trustworthy AI agent deployment.

Organizations struggle to see AI returns not due to the technology itself, but their application infrastructure. The Cloudflare report shows modernized applications are key; companies ahead in modernization are three times more likely to see AI ROI. This emphasizes building a strong, agile foundation for AI, rather than just experimenting with new tools. Security and streamlined tools also enable faster, more effective AI integration and developer productivity.

Datadog’s shares surged 23% after exceeding Q3 earnings expectations, reporting $885.7 million in revenue, a 28% year-over-year increase. Fueled by strong demand for its AI-powered security solutions, Datadog forecasts Q4 revenue between $912 million and $916 million, surpassing Wall Street estimates. The company’s strategic investments in AI, including Bits AI Agents and LLM Observability enhancements, are driving growth. Datadog’s adjusted EPS reached 55 cents, and customers with over $100,000 ARR increased by 16%.

Cloudflare is enhancing its PowerUP Partner Program with new solution bundles aimed at simplifying security and application management for partners. These bundles offer a holistic security approach and address the growing need for consolidated solutions in complex digital environments. The revamp includes discounts for partners based on program level and solutions offered, focusing on reducing complexity, mitigating cyber risks, and controlling costs. Strategic partnerships with IBM, Kyndryl, and Rakuten Mobile are also highlighted.