Our members are building the future of AI

Artificial intelligence methods to develop equity-driven pathways to building decarbonization in support of city climate change policy. The project focuses on connecting building science, machine learning, sustainability science, and public policy to enable analytical decision-making at multiple scales and time horizons.

A python library to benchmark counterfactual explanation and recourse models.

Open Development Platform provides a co-development environment for professionals and academics to develop innovative products. The platform provides both Open Source and Confidential project development. All the processes from on-boarding of projects and members to approvals and deployments through DevOps pipelines will be automated. The interactions with administrators and members will be enabled through this chatbot for handling all these processes. The framework for the bot will be based on Agentic Graph RAG workflows to support the system efficiently.

A novel probabilistic foundation model for atmospheric dynamics with applications on weather forecasting, downscaling, spatio-temporal interpolations and precipitation predictions.

This work focuses on time-sensitive AI, for example, to rapidly evaluate a photo for interesting content, or even to perform pipelines of intelligent tasks.

A dashboard of how well models perform for chatbots, where the performance is measured by user feedback.

Carbon Limiting Auto Tuning for Kubernetes

An agent framework for working with Code LLMs

Most racing car scenarios are built with manual racing controls. This project is aimed at autonomous racing using advanced Machine Learning and Deep Learning algorithms.

Racing cars have always tested the limits of our understanding of path optimizations along with acceleration and declaration of the vehicle on a winding track. Once multiple racing cars are introduced the driver of the vehicle must not only optimize the path but avoid any obstacles (cars) in the path. This makes it a very complex problem to solve for an autonomous vehicle. This project aims to take up this challenge in a phased approach.

A framework that takes notifications from a network of small telescopes, evaluate and classify that data to identify the most likely candidates for the transient being hunted and deliver the results

Using hardware-assisted silicon root of trust to build trustworthy machine learning platforms for the cloud environments.

Cooking with Granite is a community project and hub for building with IBM's Granite Model Family. We are collaboratively building out use case recipes collected into cookbooks and a community kitchen for experimentation and development.