We invite Every person attending AAAI meeting to hitch for the workshop. We believe that this is an interesting challenge Room the place promising technologies of our generation can help handle most challenging troubles of our Modern society by accelerating scientific discovery and engineering style and design.
Consequently, the members can make their community sturdy and could possibly get superior alternatives for the future.
It is focused on sustainability, carbon neutrality and performance and delves into systems like digital twins, quantum simulators and AI-powered tools for sustainable propulsion.
Key themes of your workshop include things like dependable AI tactics, security protocols, and moral criteria, with a certain center on design basic safety as well as prevention of unintended consequences which include bias in AI-driven decision-generating.
The outcomes of the workshop will contribute on the theoretical knowledge of ToM in AI and encourage new exploration Instructions, collaborations, and an interdisciplinary Local community centered on this topic.
Use branching to freely investigate opportunities, then bring Those people updates into your main design file with merging.
With a arms-on Finding out method, members can have interaction in functional assignments that solidify their knowing and application of AI in serious-entire world eventualities.
Accessibility to experts and collaboration between awareness-grounded autonomous scientific investigate styles
Tensor networks for quantum and physics-impressed computing to resolve variational inference, PDEs As well as in- verse troubles;
As LLMs keep on to showcase the opportunity to coordinate multiple AI agents for intricate challenge-solving, here the workshop will delve into pivotal open up research thoughts that advance the knowing and possible of LLM-dependent multi-agent collaboration.
Having said that, these progress also provide forth essential difficulties which include ethical criteria, details privacy worries, and likely biases. This workshop aims to discover how generative AI is often efficiently and responsibly built-in into education, making certain that its Added benefits are maximized though mitigating related hazards.
We take each brief papers (around four web pages) centered on emerging Concepts or preliminary effects and extended papers (nearly 7 internet pages) giving in-depth contributions linked to the workshop themes.
It aims to cross concerning use-encouraged foundational investigation, applied analysis, and situation-research that document thriving procedures by which AI is deployed and responsibly governed.
Circuit representations for trustworthy and successful probabilistic reasoning and learning with programs to belief- deserving ML for instance responsible neuro-symbolic AI;