In an era when information is treated as a form of power and self-knowledge an unqualified good, the value of what remains unknown is often overlooked.
In an era when information is treated as a form of power and self-knowledge an unqualified good, the value of what remains unknown is often overlooked.
The widepread deployment of AI systems in critical domains demands more rigorous approaches to evaluating their capabilities and safety.
The widepread deployment of AI systems in critical domains demands more rigorous approaches to evaluating their capabilities and safety.
This workshop will highlight the significant impact of AI applications in the Department of Energy (DOE) science by showcasing SLAC's research program, which includes national-scale science facilities such as particle accelerators, x-ray lasers, and the Rubin Observatory.
This workshop will highlight the significant impact of AI applications in the Department of Energy (DOE) science by showcasing SLAC's research program, which includes national-scale science facilities such as particle accelerators, x-ray lasers, and the Rubin Observatory.
What is Data-Centric AI?
Creating the appropriate training and evaluation data is often the biggest challenge in developing AI in practice. This workshop will explore challenges and opportunities across the data-for-AI pipeline. We will discuss recent advances in curating, cleaning, annotating and evaluating datasets for AI. We will also investigate questions that arise from data regulations, privacy and ethics. The goal of the workshop is to help build an intellectual foundation for the emerging and critically important discipline of data-centric AI.
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