- You are here:
- GT Home
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.
Recent News
-
Georgia Tech Cloud Hub Advances Generative AI Research with Microsoft Support
This successful initiative was made possible through the generous support of Microsoft, whose contribution of research resources has empowered Georgia Tech researchers to explore new frontiers in GenAI.
-
A New Neural Network Makes Decisions Like a Human Would
Neural networks do the opposite, making the same decisions each time. Now, Georgia Tech researchers in Associate Professor Dobromir Rahnev’s lab are training them to make decisions more like humans. This science of human decision-making is only just being applied to machine learning, but developing a neural network even closer to the actual human brain may make it more reliable, according to the researchers.
-
New Machine Learning Method Lets Scientists Use Generative AI to Design Custom Molecules and Other Complex Structures
New research from Georgia Tech is giving scientists more control options over generative artificial intelligence (AI) models in their studies. Greater customization from this research can lead to discovery of new drugs, materials, and other applications tailor-made for consumers.
The Tech group dubbed its method PRODIGY (PROjected DIffusion for controlled Graph Generation). PRODIGY enables diffusion models to generate 3D images of complex structures, such as molecules from chemical formulas.
Scientists in pharmacology, materials science, social network analysis, and other fields can use PRODIGY to simulate large-scale networks. By generating 3D molecules from multiple graph datasets, the group proved that PRODIGY could handle complex structures.
In keeping with its name, PRODIGY is the first plug-and-play machine learning (ML) approach to controllable graph generation in diffusion models. This method overcomes a known limitation inhibiting diffusion models from broad use in science and engineering.
-
Episode of 'Friends' Inspires New Tool that Provides Human-like Perception to MLLMs
For Jitesh Jain, conducting a simple experiment while watching one of his favorite TV series became the genesis of a paper accepted into a prestigious computer vision conference.
Jain is the creator of VCoder, a new tool that enhances the visual perception capabilities of multimodal large language models (MLLMs). Jain said MLLMs like GPT-4 with vision (GPT-4V) are prone to miss obscure objects that blend in with other objects in an image.
Events
-
Oct 9
ML@GT Seminar Series | Just Asking Questions
Featuring Jacob Andreas, Massachusetts Institute of Technology
-
Oct 2
IRIM Fall 2024 Seminar | Interactive Autonomy: Game-Theoretic Learning and Control for Multi-Agent Interactions
Featuring Negar Mehr | U.C. Berkely, Department of Mechanical Engineering
-
Sep 25
ML@GT Seminar Series | Controllable generative models for natural language and related phenomena
Featuring Karik Goyal, Georgia Institute of Technology
-
Nov 20
ML@GT Seminar Series | Mike Lewis, Facebook AI Research
Featuring Mike Lewis, Facebook AI Research
-
Nov 6
ML@GT Seminar Series | Ananda Theertha Suresh, Google Research
Featuring Ananda Theertha Suresh, Google Research
-
Oct 23
ML@GT Seminar Series | Pratik Chaudhari, University of Pennsylvania
Featuring Pratik Chaudhari, University of Pennsylvania