The Association for the Advancement of Artificial Intelligence's 2025 Spring Symposium Series was held in Burmingame, California, March 31-April 2, 2025. There were eight symposia in the spring program: AI for Engineering and Scientific Discoveries, AI for Health Symposium: Leveraging Artificial Intelligence to Revolutionize Healthcare, Current and Future Varieties of Human-AI Collaboration, GenAI@Edge: Empowering Generative AI at the Edge, Human-Compatible AI for Well-being: Harnessing Potential of GenAI for AI-Powered Science, Machine Learning and Knowledge Engineering for Trustworthy Multimodal and Generative AI, Symposium on Child-AI Interaction in the Era of Foundation Models, Towards Agentic AI for Science: Hypothesis Generation, Comprehension, Quantification, and Validation. This report contains summaries of the workshops, which were submitted by some, but not all, of the workshop chairs. This symposium aims to advance and diversify the application of AI in emerging engineering and scientific discovery domains. Inspired by progress in large language models, generative AI, and AI-assisted scientific computing, we seek to foster new collaborations between industry and academia to tackle challenging problems in materials, manufacturing, and life sciences. We also plan to explore new directions in human-machine interaction for accelerating knowledge discovery and address related ethical considerations. Through invited speakers, panel discussions, and contributions from researchers with cross-disciplinary expertise, we hoped to cultivate partnerships that drive transformative advances in both AI and scientific research. No formal report was filed by the organizers for this symposium.

This article is part of our coverage of the latest in AI research. What is the next step toward bridging the gap between natural and artificial intelligence? Scientists and researchers are divided on the answer. Yann LeCun, Chief AI Scientist at Meta and the recipient of the 2018 Turing Award, is betting on self-supervised learning, machine learning models that can be trained without the need for human-labeled examples. LeCun has been thinking and talking about self-supervised and unsupervised learning for years. But as his research and the fields of AI and neuroscience have progressed, his vision has converged around several promising concepts and trends.

The biggest concerns over AI today are not about dystopian visions of robot overlords controlling humanity. Social media algorithms are one of the most prominent examples. Take YouTube, which over the years has implemented features and recommendation engines geared toward keeping people glued to their screens. As The New York Times reported in 2019, many content creators on the far right learned that they could tweak their content offerings to make them more appealing to the algorithm and drive many users to watch progressively more extreme content. YouTube has taken action in response, including efforts to remove hate speech. An independently published study in 2019 claimed that YouTube's algorithm was doing a good job of discouraging viewers from watching "radicalizing or extremist content."

The expansion of e-commerce, distance learning in education and remote work as well as health care services during the pandemic prompted the greater use of artificial intelligence (AI) and cloud technology in order to cope with big data. AI and cloud solutions are on the rise in every field, from production to marketing. These, as well as the priorities of the business world, were the matters addressed this week at the Ventures60 event. The big data occupation has been generally translated into more overtime and more boring work. Yet, many institutions are now opting for cloud technology and artificial intelligence to protect themselves from the big data drain.

The world's biggest technology companies are joining forces to consider the future of artificial intelligence. Amazon, Google's DeepMind, Facebook, IBM and Microsoft will work together on issues such as privacy, safety and the collaboration between people and AI.

AI may one day be responsible for aspects of infrastructure and billions of people.