Blog

Studying the Risks and Benefits of AI Companions: Researchers Discuss a New Framework for Understanding AI Companionship

Admin — Wed, 08 Apr 2026 13:45:00 GMT

AI systems are beginning to occupy a new role in people’s lives.

Advancing AI: Highlights from March

Admin — Wed, 01 Apr 2026 14:00:00 GMT

This month, Sony AI's work spans the foundations of generative models and the frontiers of audio and signal processing research. More than 10 papers have been accepted to ICASSP 2026 in Barcelona, covering music structure analysis, audio-visual generation, sound separation, Foley synthesis, and speech processing. Sony AI researcher Chieh-Hsin "Jesse" Lai—alongside Yang Song, Dongjun Kim, and Stefano Ermon—has written “The Principles of Diffusion Models,” a new book that traces the shared mathematical structure underlying DDPMs, score-based models, and flow-based methods. And in the news, Alice Xiang has been recognised in “AI Magazine's” Top 100 Women in AI for 2026, and joined the “Me, Myself and AI” podcast to discuss FHIBE, Sony AI's consent-driven benchmark for evaluating bias in computer vision.

On Writing The Principles of Diffusion Models, A Q&A With Sony AI Researcher, Jesse Lai

Admin — Thu, 05 Mar 2026 15:30:00 GMT

Introduction

Advancing AI: Highlights from February

Admin — Mon, 02 Mar 2026 05:00:00 GMT

February at Sony AI was defined by momentum across global stages, research publications, and conversations about how AI moves from theory into practice.

Sony AI’s Contributions at AAAI 2026

Admin — Fri, 30 Jan 2026 05:00:00 GMT

Sony AI’s Contributions at AAAI 2026

AAAI 2026 is a reminder that progress in AI isn’t one straight line. This year’s Sony AI contributions span improving and enhancing continual learning and interpretability, robust decision-making in dynamic environments, and creator-facing tools for editing audio and video with intent intact. The common thread is practical trust: not just better outputs, but clearer reasoning, steadier behavior, and more predictable control.

How Sony AI’s Scientific Discovery Team is Reimagining How Researchers Evaluate ...

Admin — Mon, 26 Jan 2026 05:00:00 GMT

In today’s research landscape, thousands of scientific papers are published each day; a metaphorical sea of knowledge. Even domain experts struggle to keep up. As Pablo Sánchez Martín, Researcher at Sony AI, explained, “Doing a proper literature review can easily become a full-time job, and that’s only one part of a scientist’s work.”

Sony AI 2025, Year in Review

Admin — Mon, 22 Dec 2025 05:00:00 GMT

As the year comes to close, we’re reflecting not only on key research milestones, but on the scale of work achieved across our global teams. In 2025, we published 87 papers, contributed to 15 major conferences, and expanded collaborations across audio, imaging, reinforcement learning, ethics, analog design, and scientific discovery.

Protecting Creator’s Rights in the Age of AI

Admin — Mon, 15 Dec 2025 05:00:00 GMT

The rise of artificial intelligence technologies that can generate songs and mimic musical styles and artists has led to a surge in AI music content with unclear origins, prompting concerns about authenticity, fairness and ownership. Much of this output is being created with tools trained on unlicensed datasets that provide no credit or compensation to the rightsholders whose work unpins these models.

Advancing AI: Highlights from November

Admin — Mon, 01 Dec 2025 05:00:00 GMT

November was a pivotal chapter for Sony AI, marked by the debut of our ethics project FHIBE, a consent-driven benchmark years in the making, and a trio of blogs that traced its foundations, its construction, and the people who brought it to life. Together, these stories highlight how ethical data practices, technical rigor, and human-centered design can reshape AI’s relationship with the world.

NeurIPS 2025: Sony AI’s Latest Contributions

Admin — Mon, 01 Dec 2025 05:00:00 GMT

NeurIPS 2025 brings together work across Sony AI that targets real problems in real settings. The research in this roundup focuses on models that adapt under constraints, handle fragmented or sensitive data, support creators, and make decisions that hold up when conditions change. Each project moves toward systems that behave more consistently and more transparently. The goal is the same across every group: make AI easier to trust, easier to evaluate, and easier to use in complex environments. We encourage you to dive into our research highlights below to learn more about our contributions.