In the past 5 years, AI has been trending towards becoming a closed and propreitary field -- undoing hard work from the previous decade. This is alarming for scientific progress. The reasons for this trend are complex, and so are the solutions -- ranging from energy and resources to capital pressure to geopolitics to breaking previous societal mechanics around intellectual property. I will give an opinionated view of how to get us as a field to a better place.

Most youth grow up in low- and middle-income countries (LMICs) in an increasingly digitized context but with unequal digital media access, skill, and opportunity. In these settings, limited resources to effectively scaffold digital media use constrain youth thriving. As a result, globally, adolescents facing offline disadvantages often find themselves further marginalized in the digital realm. In this talk, I will review the current knowledge on the interaction between digital media and adolescent development, highlight crucial evidence gaps in LMICs, and propose and future directions to address these pressing issues.

At the CERN Large Hadron Collider, protons collide 40 million times per second at the highest energies achievable in the lab, probing the microscopic nature of subatomic particles on the smallest length scales. These proton-proton collisions give rise to thousands of particles per collision, whose energy deposits and hits are measured by massive detectors and read out as hundreds of millions of data channels. By comparing this data to those predicted by theory through simulation, we can test the validity of our theory and search for the existence of new particles, like dark matter, or interactions, like the elusive Higgs boson self-interaction. This avalanche of data will continue to grow in the next generation of experiments, posing tremendous challenges. Machine learning (ML) methods are increasingly essential to analyze this data while overcoming these challenges. In this talk, I will cover several opportunities to apply ML to reconstruct particles from detector measurements, simulate collisions, filter collisions in real time, and perhaps even discover new physical laws or symmetries.

Bio: Javier Duarte is an Associate Professor of Physics at UC San Diego and a member of the CMS experiment at the CERN Large Hadron Collider. He leads a research group developing new …

The EU aims to ensure that AI is safe and trustworthy. For this purpose, the AI Act is the first-ever comprehensive legal framework on AI worldwide, guaranteeing the health, safety and fundamental rights of people, and providing legal certainty to businesses across the 27 Member States. The European Commission established the AI Office in June 2024 to support the EU’s approach to AI. It will play a key role in implementing the AI Act by supporting the governance bodies in Member States in their tasks. It also ensures a strategic European approach on AI at the international level.

The AI Office will enforce the rules for general-purpose AI models. At the same time, the AI Office promotes an innovative ecosystem of trustworthy AI, to reap the societal and economic benefits of AI in many sectors, with AI Factories relying on world-class supercomputers. to To make support startups and SMEs in developing trustworthy AI that complies with EU values and rules The Commission launched an AI innovation package . Both the ‘GenAI4EU' initiative and the AI office were part of this package. Together they will contribute to the development of novel use cases. Application areas include robotics, health, biotech, manufacturing, mobility, …