🌱 EcoLogits tracks the energy consumption and environmental footprint of using generative AI models through APIs.

A curated list of awesome Green AI resources and tools to assess and reduce the environmental impacts of using and deploying AI.

Maximize Efficiency, Elevate Accuracy: Slash GPU Hours by Half with Efficient Pre-training!

Evolve your OpenCV Image Processing filters using Cartesian Genetic Programming

IBM Environmental Intelligence

Use local Large Language Models (LLMs) while monitoring energy usage.

A curated list of Green AI resources.

Learn to optimize machine learning tasks for environmental sustainability. Discover how to use real-time electricity data and low-carbon energy sources for model training and inference, reducing the carbon footprint of your cloud operations.

Guidelines to deploy AI models in different cloud providers aligned with green AI goals.

An initiative to build a fair and sustainable AI ecosystem by identifying and crediting open-access creators whose work shows strong similarity to AI-generated content.

Energy consumption of ML inference with Runtime Engines

Code for our aging-aware CPU management technique to extend embodied carbon amortization in LLM inference clusters

This is the type of futuristic self growth ecosystem that produces and consumes products that allow no external dependencies especially money and human labor. This can lead to futuristic cities that can sustain without external aids, supplies over a long period

A central place to collect and organize studies on digital sustainability.

Resource-efficient LLM distillation: Improving sustainability and reducing computational costs of Large Language Models in financial analytics through knowledge distillation.

Fake detection using BERT & smooth pruning

Hybrid Renewable Energy Forecasting and Trading Competition: Team Skro