The rapid advancements in artificial intelligence are showing no signs of slowing down. From GPT-2 to GPT-5, we remain uncertain about where this race for performance is leading us, though many experts warn of potentially catastrophic risks. The highly publicized launches of powerful chatbots are only the tip of the iceberg. In the first part of the course, we will review these advancements and explore where they might lead us. Informed by scaling laws and expert forecasts, we will see that Artificial General Intelligence (AGI) could emerge within this decade.

While these technologies are enabling breakthroughs in biomedical research, breaking down language barriers, and reducing administrative burdens, significant technical challenges remain in building general-purpose models that are both reliable and safe. The second part of the course will discuss the benefits and risks of future AGIs.

These risks stem from both our limited understanding of the models we create and the lack of international coordination to avoid competitive races and ensure the safe deployment of such powerful systems. Assessing which dangerous capabilities a model has—and how they can be elicited—requires careful evaluation, often of closed-source systems. The final part of the course will examine solutions for controlling AIs in a robust way: understanding, evaluating, and regulating them. We will explicitly discuss how engineers can contribute through research and machine learning expertise.