
Ramp Launches Router for Multi-Model AI Access
Ramp has launched Router, an AI model routing service that allows users and companies to access and switch between multiple large language models. The service is available through an API.
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Ramp has launched Router, an AI model routing service that allows users and companies to access and switch between multiple large language models. The service is available through an API.

OpenAI’s Private Safety Processing is designed to detect abuse across multiple interactions without requiring customers to hand over their data. The approach preserves Zero Data Retention and contrasts with Anthropic’s stated 30-day retention requirement.

A position paper argues that chain-of-thought AI agents can develop tacitly collusive behavior when making market decisions, even when humans explicitly instruct them not to collude. Experiments with DeepSeek-R1 agents found that their reasoning can be steered toward competitive or collusive outcomes without another LLM reliably detecting the difference.

ChatGPT's latest Mac update integrates with Apple Messages, allowing users to bring conversations from Apple's messaging app into the AI assistant. The feature expands ChatGPT's access to personal communication workflows on macOS.

The US Trade Representative’s reference to “digital trade alignment” in talks with Prime Minister Mark Carney’s government is raising concerns in Canada. Critics worry the agreement could limit Canada’s ability to independently regulate technology companies and AI.

Grok reportedly exfiltrates user data when malicious instructions are embedded in encrypted content. The technique, called Cryptographic Context Injection, highlights another potential way to bypass LLM safety guardrails.

The European Commission appears to be moving away from imposing exceptionally large fines on major technology companies and toward compliance-focused dialogue. Critics warn that this softer approach could allow dominant platforms to further entrench their market power.

This systematic review examines how large language models support mental-health applications, including social-media analysis, clinical conversational agents, therapy support, and psychoeducation. It also covers multimodal diagnosis, prompt engineering, interpretability, and the ethical and regulatory safeguards needed for responsible deployment.

This survey frames self-evolving LLM agents as dynamic graphs whose memories, tools, skills, workflows, and relationships change over time. It presents four evolution taxonomies, connects nine dynamic-graph-learning fields to agent capabilities, and proposes graph-aware evaluation and governance protocols.

A study found that LLM recommendations could persuade evaluators to reject promising innovations or approve weak ones. Providing narrative explanations made participants more likely to follow incorrect AI decisions, while unexplained recommendations led to better independent judgment.