Federated Learning using Hugging Face and Flower
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
More from the blog
The future of practice: Enabling teachers to create learning interactives with generative UI
Education Innovation
MIT Schwarzman College of Computing launches pilot to help educators teach AI across disciplines
A weeklong summer workshop brought higher education faculty to campus to explore how AI and machine learning materials can be adapted for their classrooms.
Transfer learning for genomic prediction in underrepresented populations
General Science
BenchMIRT: What are LLM benchmarks actually measuring?
A Blog post by Ai2 on Hugging Face
Related papers
Time for AI (Ethics) Maturity Model Is Now
It is argued that AI software is still software and needs to be approached from the software development perspective, and whether the focus should be on AI ethics or the quality of an AI system, called a maturity model for the development of AI systems is discussed.
ChargeNet: E(3) Equivariant Graph Attention Network for Atomic Charge Prediction
This work introduces an advanced equivariant graph attention neural network specifically engineered to model long-range atomic electrostatic interactions with high precision, and improves the model's accuracy, generalization, and robustness in complex scenarios.
Software development in startup companies: A systematic mapping study
The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
Why Early-Stage Software Startups Fail: A Behavioral Framework
This state-of-practice investigation was performed using a literature review followed by a multiple-case study approach and presents how inconsistency between managerial strategies and execution can lead to failure by means of a behavioral framework.