← Archive

AI news for 2026-05-18

  • Dynamics-Level Watermarking of Flow Matching Models with Random Codes

    This ArXiv paper introduces a watermarking method for flow matching generative models that embeds identifiers at the dynamics level using random codes rather than post-hoc output modification. The approach is designed to be robust to common watermark removal techniques. It is relevant to model provenance and IP protection for generative AI.

  • Publicis Acquires LiveRamp for $2.5 Billion in Agentic AI Data Play

    Publicis Group has announced the acquisition of data connectivity company LiveRamp for $2.5 billion, framed explicitly as a strategic move to build out agentic AI data infrastructure. The deal signals major advertising and marketing conglomerates moving to control first-party data pipelines for AI agent applications. This is one of the larger M&A moves in the AI data space to date.

  • AI-Mediated Communication Can Steer Collective Opinion, ArXiv Study Finds

    A new ArXiv paper presents empirical findings that AI-mediated communication systems can measurably influence collective human opinion formation. The research has implications for AI safety, alignment, and platform design. It provides a formal framework for analyzing opinion dynamics in AI-assisted social environments.

  • Prospective Multi-Pathogen Disease Forecasting Using Autonomous LLM-Guided Tree Search

    An ArXiv paper presents a framework using LLM-guided tree search for autonomous, prospective forecasting of multiple infectious disease outbreaks. The approach enables the model to reason over and select epidemiological hypotheses without human intervention. This represents a novel application of LLM reasoning to real-world public health forecasting.

  • ChatGPT Falls to Second Place Behind Claude in Generative AI Market Metrics

    Reports circulating on Reddit's r/artificial claim ChatGPT has fallen to second place behind Anthropic's Claude across several key metrics including net new ARR, mobile downloads, business adoption, and daily active users. The claim lacks a primary source citation in the feed but aligns with observable trends in enterprise AI adoption. Credibility is moderate pending verification of the underlying report.