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CSAIL researchers highlighted their research at the intersection of holographic art and human-computer interaction.     Including among these projects were objects w/angle-dependent hues generated by nanoscale diffraction, as well as multi-perspective imagery on 3D-printed items (Credit: Alex Shipps/MIT CSAIL and the researchers).
CSAIL article

In 1968, MIT Professor Stephen Benton transformed holography by making three-dimensional images viewable under white light. Over fifty years later, holography’s legacy is inspiring new directions at MIT CSAIL, where the Human-Computer Interaction Engineering (HCIE) group, led by Professor Stefanie Mueller, is pioneering programmable color — a future in which light and material appearance can be dynamically controlled.

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Scaling laws enable researchers to use smaller LLMs to predict the performance of a significantly bigger target model, thus allowing better allocation of computational power (Credits: Adobe Stock).
CSAIL article

When researchers are building large language models (LLMs), they aim to maximize performance under a particular computational and financial budget. Since training a model can amount to millions of dollars, developers need to be judicious with cost-impacting decisions about, for instance, the model architecture, optimizers, and training datasets before committing to a model. To anticipate the quality and accuracy of a large model’s predictions, practitioners often turn to scaling laws: using smaller, cheaper models to try to approximate the performance of a much larger target model. The challenge, however, is that there are thousands of ways to create a scaling law.