Large language models (LLMs) are becoming increasingly useful for programming and robotics tasks, but for more complicated reasoning problems, the gap between these systems and humans looms large. Without the ability to learn new concepts like humans do, these systems fail to form good abstractions—essentially, high-level representations of complex concepts that skip less-important details—and thus sputter when asked to do more sophisticated tasks.Large language models (LLMs) are becoming increasingly useful for programming and robotics tasks, but for more complicated reasoning problems, the gap between these systems and humans looms large. Without the ability to learn new concepts like humans do, these systems fail to form good abstractions—essentially, high-level representations of complex concepts that skip less-important details—and thus sputter when asked to do more sophisticated tasks.[#item_full_content]
A new publication in Opto-Electronic Advances discusses efficient stochastic parallel gradient descent training for on-chip optical processors.A new publication in Opto-Electronic Advances discusses efficient stochastic parallel gradient descent training for on-chip optical processors.[#item_full_content]
Researcher and technologist Matt Beane, an assistant professor in the Technology Management Department at UC Santa Barbara, is calling attention to an immediate and hidden concern in the modern workplace—and offering a surprising path forward.Researcher and technologist Matt Beane, an assistant professor in the Technology Management Department at UC Santa Barbara, is calling attention to an immediate and hidden concern in the modern workplace—and offering a surprising path forward.Business[#item_full_content]
AI holds the potential to help doctors find early markers of disease and policymakers to avoid decisions that lead to war. But a growing body of evidence has revealed deep flaws in how machine learning is used in science, a problem that has swept through dozens of fields and implicated thousands of erroneous papers.AI holds the potential to help doctors find early markers of disease and policymakers to avoid decisions that lead to war. But a growing body of evidence has revealed deep flaws in how machine learning is used in science, a problem that has swept through dozens of fields and implicated thousands of erroneous papers.Machine learning & AI[#item_full_content]
A review published in the International Journal of Grid and Utility Computing has investigated ways in which the increasing problem of duplicate data in computer storage systems might be addressed. Solutions to this problem could improve storage efficiency, system performance, and reduce the overall demand on resources.A review published in the International Journal of Grid and Utility Computing has investigated ways in which the increasing problem of duplicate data in computer storage systems might be addressed. Solutions to this problem could improve storage efficiency, system performance, and reduce the overall demand on resources.[#item_full_content]
You wanna see her move? I think that’s the fun part.You wanna see her move? I think that’s the fun part.Robotics[#item_full_content]
Robots have already proved to be promising tools to complete complex and demanding maintenance tasks. While engineers have developed a wide range of robots that could help to maintain and repair infrastructure, many of these robots need to be plugged into external power sources, which limits their real-world application.Robots have already proved to be promising tools to complete complex and demanding maintenance tasks. While engineers have developed a wide range of robots that could help to maintain and repair infrastructure, many of these robots need to be plugged into external power sources, which limits their real-world application.[#item_full_content]
