JILA Auditorium

Abstract: In this talk, I will take you on a tour of large language models, tracing their evolution from Recurrent Neural Networks (RNNs) to the Transformer architecture. We will explore how Transformers elegantly sidestep the vanishing and exploding gradient issues that plagued RNNs. I will introduce neural scaling laws—empirical relationships reminiscent of scaling behaviors common in physics—that predict how model performance improves with increased computational investment.

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Abstract: Prominent among biophysical techniques is the optical trap, for which Arthur Ashkin (Bell Labs) received a Nobel Prize in 2018. Among the successes of optical traps have been direct measurements of the steps taken by biological motor proteins, such as kinesin, and by nucleic-acid enzymes, such as RNA polymerase. Optical traps facilitate studies of replication, transcription, and translation at the single-molecule level. They’ve been especially useful in mapping the free-energy landscapes of folding by small, structured RNAs.

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Experiments with fermionic atoms in optical lattices have led to breakthroughs in understanding fundamental condensed-matter phenomena. However, elevating such experiments from a tool of scientific exploration to a computational tool capable of quantitatively predicting molecule and material properties requires overcoming decoherence with fault-tolerance techniques. Existing approaches encode qubits into atoms, losing one of the fundamental advantages of cold-atoms: their fermionic nature.

Abstract: The ocean absorbs most of the heat and about a quarter of the carbon emissions caused by human activities. These anthropogenic perturbations significantly influence the ocean circulation, with direct and critical implications for the climate system. The ocean circulation is characterized by diverse turbulence regimes that span a vast range of spatial and temporal scales.

Abstract: The planetary boundary layer (PBL), the lowest part of the atmosphere, plays a key role in regulating interactions between the land surface, clouds, and atmospheric turbulence. These interactions drive the exchange of energy, moisture, and aerosols, shaping both weather and climate. However, turbulence within the PBL adds complexity to these processes, making them challenging to understand and predict.