The rise of generative AI is reshaping how we think about collaboration, application development, and daily life. It enables more efficient solutions and better-informed decisions, though the journey can feel overwhelming. Which foundation model should I use? How do I know if the pre-training datasets are unbiased or if the tuning and inference methods ensure fairness? Can I trust the results from these models?

The key to navigating this emerging path is adopting the flexibility, transparency, and collaboration of open source that many of us are familiar with. What does this mean in practice? How can we equip ourselves and our communities with the right tools and knowledge to dispel doubts and address uncertainties? Is there a more comforting light at the end of this confusing tunnel?

Sometimes it feels like there are more questions than answers. In this session, we ask you to keep an open mind and explore possibilities with us. We will discuss approaches to making AI tangible and actionable, illustrating them with use cases and demos.