- Learning with limited data: ARNI will pioneer new AI-based methods to tackle the challenge of learning from limited data, both in AI and neuroscience. These methods will enable the development of brain models that shed light on how the brain learns from limited experiences.
- Reasoning about causality and uncertainty: ARNI aims to develop innovative AI-based techniques for reasoning about causality and uncertainty, two fundamental aspects of human cognition. By constructing brain models that capture these processes, we can unravel the mechanisms behind decision-making in uncertain situations.
- Lifelong learning: ARNI’s researchers will explore novel AI-based methods for lifelong learning, empowering the brain to continuously acquire new knowledge and skills throughout an individual’s lifetime. These advancements will deepen our understanding of how the brain learns and adapts over time.
- Bridging the gap between artificial and biological networks: ARNI seeks to bridge the current gap between artificial and biological networks by developing AI-based methodologies. These methodologies will facilitate the creation of brain models that elucidate the inner workings of the brain and drive the development of AI technologies for brain enhancement.
In the heart of California, amidst the bustling innovation of Silicon Valley and the storied halls of its universities, a new dawn was breaking. This