Quantum Computing with Superconducting Qubits - RESCHEDULEDQuantum entanglement is a very real effect, in which (usually nearby) quantum states of real materials can become so very well connected that acting on one component will strongly affect the other. This effect of entanglement, which can be present in materials not used for quantum computing as well, plays ...
Oceanography has made great progress augmenting shipboard measurements with autonomous platforms including underwater gliders and surface vehicles. Still, the scale at which observations can be made by these platforms is limited by the relatively high operational costs requiring human monitoring and the cost of loss of expensive platforms. True synoptic ...
Where: Moss LandingCost: Free
Hate speech, algorithms, and digital connectivityThe Online Hate Index (OHI) is a research partnership between UC Berkeley’s D-Lab and Google Jigsaw that seeks to improve society's understanding of online hate speech (from sources such as YouTube, Reddit, Twitter and other social media sites), including its prevalence over time, variation across regions and demographics, our ability ...
Where: BerkeleyCost: Free
Adapting to Sea-Level Rise on Atolls: Managing Land Use and Aquifer Recharge on Roi-Namur, Marshall IslandsFreshwater resources on low-lying atoll islands are highly vulnerable to climate change and sea-level rise. Groundwater in the freshwater lens is a critically important water resource on many atolls. Although many atolls have high annual rainfall, dense vegetation and high evapotranspiration can limit recharge to the freshwater lens. Here I ...
Machine Learning---Why Do Simple Algorithms Work So Well?While state-of-the-art machine learning models are deep, large-scale, sequential and highly nonconvex, the backbone of modern learning algorithms are simple algorithms such as stochastic gradient descent, or Q-learning (in the case of reinforcement learning tasks). A basic question endures---why do simple algorithms work so well even in these challenging settings? ...
