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What is Machine Learning?
Machine learning aims to produce machines that can learn from their experiences and make predictions based on those experiences and other data they have analyzed. The Machine Learning Center at Georgia Tech (ML@GT) is an Interdisciplinary Research Center that is both a home for thought leaders and practitioners and a training ground for the next generation of pioneers.
The field of machine learning crosses a wide variety of disciplines that use data to find patterns in the ways both living systems, such as the human body and artificial systems, such as robots, are constructed and perform. Whether it’s being applied to analyze and learn from medical data, or to model financial markets, or to create autonomous vehicles, machine learning builds and learns from both algorithm and theory to understand the world around us and create the tools we need and want.
Team First to Successfully Scale Deep Neural Network Models for Federated Learning Framework
School of Computer Science researchers have developed a new framework that advances federated learning, a distributed, real-time approach for training deep neural network models. The new framework enables remote clients to equitably participate in training regardless of their computing resources.
Like Humans and Animals, AI Agents Find Their Way Through Memory
A recent paper authored by Georgia Tech researchers makes a surprising discovery — blind AI agents use memory to create maps and navigate through their surrounding environment.
Examining the Boundaries of Using AI 'Sensing' to Understand Office Workers’ Performance and Wellbeing
Researchers at Georgia Tech and Northeastern University conducted a study with information workers to learn about their perspectives on being monitored and their information being collected with passive-sensing enabled artificial intelligence (PSAI), where computing devices can unobtrusively detect and collect user behaviors.
Misinformation Detection Models are Vulnerable to ChatGPT and Other LLMs
New research indicates that current machine learning models trained on human-produced content can struggle to detect falsehoods generated by AI-powered chatbots.
IRIM Fall 2023 Research Symposium
IRIM hosts each semester a symposium to feature presentations from faculty and presentations of research that has been funded by our IRIM seed grant program in the last year.