Columbia University School of Professional Studies

Unearthing Hidden Potential and Lost Treasure: AI Applications in Learning Management

A recent event hosted by the M.S. in Human Capital Management (HCM) program sought to get to the bottom of a very important ...
Edutopia

Making Use of a Worked Example to Improve Learning

It’s a familiar moment in math class—students are asked to solve a problem, and some jump in confidently while others freeze, unsure where to begin. When students don’t yet have a clear mental model ...
Capital Gazette

Login issues challenge students during Anne Arundel’s virtual learning

Anne Arundel County Public Schools said students experienced delays logging into their web platform during the academic year’s first virtual learning day Thursday. The school system said delays were ...
Medicine Buffalo

SLI Learning Outcome Chart Examples

1. Demonstrate that scientific knowledge applies across multiple scales of size and/or time. Climate impacts, local vs global. Climate change timescales, long term (geologic timescale) to short term ...
IEEE

Log-Scale Quantization in Distributed First-Order Methods: Gradient-Based Learning From Distributed Data

Abstract: Decentralized strategies are of interest for learning from large-scale data over networks. This paper studies learning over a network of geographically distributed nodes/agents subject to ...
Hosted on MSN

Never Stop Learning: 8 Examples of People Doing Amazing Things After 60

CVS, Walgreens pull back COVID vaccines in more than a dozen states following new guidelines Trump is on a collision course with Ireland – and it could spell economic disaster Teen girl missing for 17 ...
GitHub

LogAI: A Library for Log Analytics and Intelligence

LogAI is a one-stop open source library for log analytics and intelligence. LogAI supports various log analytics and log intelligence tasks such as log summarization, log clustering, log anomaly ...
VentureBeat

Fine-tuning vs. in-context learning: New research guides better LLM customization for real-world tasks

Two popular approaches for customizing large language models (LLMs) for downstream tasks are fine-tuning and in-context learning (ICL). In a recent study, researchers at Google DeepMind and Stanford ...