Announcing Flower 1.28
The Flower Team is excited to announce the release of Flower 1.28 stable ๐
Announcing Flower 1.28
The Flower Team is excited to announce the release of Flower 1.28 stable ๐
Announcing Flower Hub: The App Hub for Collaborative AI
The Flower Team is excited to announce the launch of Flower Hub ๐
Announcing Flower 1.27
The Flower Team is excited to announce the release of Flower 1.27 stable ๐
Flower on Aridhiaโs Digital Research Environment
Flower and Aridhiaโs Digital Research Environment make it easier to run federated learning across hospitals.
Announcing Flower Datasets 0.6.0
The Flower Team is excited to announce the release of Flower Datasets 0.6.0 ๐
Announcing Flower 1.26.1
The Flower Team is excited to announce the release of Flower 1.26.1 stable ๐
Announcing Flower 1.26
The Flower Team is excited to announce the release of Flower 1.26 stable ๐
Flower Labs and Starcloud Reach a Major AI Milestone in Orbit
Flower Labs and Starcloud successfully ran a decentralized AI workload on an operational satellite.
Announcing Flower 1.25
The Flower Team is excited to announce the release of Flower 1.25 stable ๐
Enterprise-Grade Federated AI: Flower Architectural Patterns
Learn how Flower delivers full enterprise-grade federated AI for secure and regulated environments.
Announcing Flower 1.24
The Flower Team is excited to announce the release of Flower 1.24 stable ๐
Quantum Federated Learning using Flower
Bridging Quantum Computing and Federated Learning with PennyLane and Flower
Announcing Flower's Collaboration with Red Hat
Flower Labs and Red Hat join forces to advance scalable Federated AI on scientific computing platforms
Announcing Flower 1.23
The Flower Team is excited to announce the release of Flower 1.23 stable ๐
Announcing the Decentralized AI Hackathon Winners
The winning teams at the Decentralized AI Hackathon tell us what they built!
Scaling Federated AI for the NHS in Secure Research Environments
Discover how Flower's integration into Secure Research Environments is revolutionizing federated AI for the NHS.
Announcing Flower SuperGrid
SuperGrid, the next generation platform for scalable and production-grade federated AI.
Quickstart for the Decentralized AI Hackathon
๐ฅ Just two days left until the Decentralized AI Hackathon at Stanford!
Announcing Flower 1.22
The Flower Team is excited to announce the release of Flower 1.22 stable ๐
Announcing Flower 1.21
The Flower Team is excited to announce the release of Flower 1.21 stable ๐
Announcing Flower 1.20
The Flower Team is excited to announce the release of Flower 1.20 stable ๐
Announcing Flower 1.19
The Flower Team is excited to announce the release of Flower 1.19 stable ๐
Introducing the Flower Intelligence Kotlin SDK
Build privacy-first AI apps on Android using the new Kotlin SDK for Flower Intelligence
Photon: Federated Pre-training of Large Language Models
A New SOTA in Efficient and Robust Federated LLM Pre-training
Launching Flower Pilot Program Batch 3
We are launching the call for the next wave of collaborations in the Flower Pilot Program.
Announcing Flower 1.18
The Flower Team is excited to announce the release of Flower 1.18 stable ๐
Decoupled Embeddings for Pre-training (DEPT)
New breakthrough in embeddings for decentralized AI
Flower Labs is now ISO 27001 compliant
Flower Labs is now ISO 27001 certified. We uphold the highest security standards to protect data and privacy. Learn how this benefits our community.
Announcing Flower 1.17
The Flower Team is excited to announce the release of Flower 1.17 stable ๐
Announcing BloodCounts! and Flower Partnership
BloodCounts! and Flower Partner to Revolutionisze Early Diagnosis of Global Haematological Conditions
Using Vana and Flower Together
Building Decentralized, User-Owned AI with Vana and Flower
From Theory to Practice: Unlocking the Next Phase of Federated AI
Whatโs the next step in your journey towards federated AI mastery?
Flower Intelligence
On-device AI Privacy and Speed with Cloud-based AI Scale and Simplicity
Announcing Flower 1.16
The Flower Team is excited to announce the release of Flower 1.16 stable ๐
Revolutionizing Healthcare with Federated AI
Eye2Geneโs Demo Showcase Using Flower.
Pioneering the Future of Medical Imaging with Federated Learning
Revolutionize medical imaging while safeguarding sensitive patient data using Flower and federated learning.
Announcing Flower 1.15.2
The Flower Team is excited to announce the release of Flower 1.15.2 stable ๐
Announcing Flower 1.15.1
The Flower Team is excited to announce the release of Flower 1.15.1 stable ๐
Announcing Flower 1.15
The Flower Team is excited to announce the release of Flower 1.15 stable ๐
Announcing Flower Datasets 0.5.0
The Flower Team is excited to announce the release of Flower Datasets 0.5.0 ๐
Announcing Flower 1.14
The Flower Team is excited to announce the release of Flower 1.14 stable ๐
Federated Datasets in Research
An overview of the datasets used in FL research.
Announcing Flower 1.13.1
The Flower Team is excited to announce the release of Flower 1.13.1 stable ๐
Announcing Flower 1.13
The Flower Team is excited to announce the release of Flower 1.13 stable ๐
Announcing Flower Datasets 0.4.0
The Flower Team is excited to announce the release of Flower Datasets 0.4.0 ๐
Announcing FlowerTune LLM Leaderboard
The Flower Team is excited to announce the FlowerTune LLM Leaderboard
Announcing Flower 1.12
The Flower Team is excited to announce the release of Flower 1.12 stable ๐
Announcing Flower 1.11.1
The Flower Team is excited to announce the release of Flower 1.11.1 stable ๐
Announcing Flower 1.11
The Flower Team is excited to announce the release of Flower 1.11 stable ๐
Announcing Flower Datasets 0.3.0
The Flower Team is excited to announce the release of Flower Datasets 0.3.0 ๐
Announcing Flower 1.10
The Flower Team is excited to announce the release of Flower 1.10 stable ๐
In the Jungle of Federated Learning Frameworks
A comparison of open-source FL frameworks, and new FL comparison suite.
Announcing Flower Datasets 0.2.0
The Flower Team is excited to announce the release of Flower Datasets 0.2.0 ๐
Announcing Flower Node Authentication
We are announcing the new Flower node authentication feature in Flower 1.9
Announcing Flower Docker images
We are excited to announce the release of our new Flower Docker images ๐ณ
Announcing Flower 1.9
The Flower Team is excited to announce the release of Flower 1.9 stable ๐
Announcing Flower 1.8
The Flower Team is excited to announce the release of Flower 1.8 stable ๐
Launching Flower Pilot Program: Batch Two
We are launching the call for the next wave of participants in the Flower Pilot Program!
Announcing NVIDIA and Flower Collaboration
NVIDIA and Flower Collaborate to Improve Federated Learning Development for Researchers, Data Scientists and AI Developers.
LLM FlowerTune: Federated LLM Fine-tuning with Flower
Check out our new example for federated LLM fine-tuning
Introducing FlowerLLM
FlowerLLM: The World's first 1.3B parameter LLM trained via Federated Learning
Announcing Flower Discuss
We are happy to announce the launch of our official community forum.
FlowerไธญๆAPIๆๆกฃๅๅธ
Flower's Chinese API documentation is now available.
Flower Labs raises $20M Series A
Accelerate the democratization of decentralized and federated AI
Federated XGBoost: Flower is all you need
Check out our new features for federated XGBoost
Install Flower with Conda
Flower is now officially distributed on the conda-forge!
Announcing Flower 1.7
The Flower Team is excited to announce the release of Flower 1.7 stable ๐
Federated Learning with MLX and Flower
MLX is a NumPy-like array framework designed for efficient and flexible machine learning on Apple silicon.
Raspberry Pi 5: Ready for Federated Vision
We benchmarked the new Raspberry Pi 5 against its predecessor on a wide range of new and old vision models.
Federated XGBoost with bagging aggregation
Check out our new examples and docs for federated XGBoost with bagging aggregation
Announcing Flower 1.6
The Flower Team is excited to announce the release of Flower 1.6 stable ๐
Announcing Flower Datasets
Reliable, thoroughly tested dataset partitioning schemes that create fully reproducible Federated Learning experiments are now possible with Flower Datasets.
Flower User Survey 2023
Are you a Flower user or active in the FL community? Please support us on our journey to improve our framework by completing this survey ๐ผ
Federated Finetuning of OpenAI's Whisper
Check out the new code example federating OpenAI's Whisper for the downstream task of keyword spotting.
Announcing Flower 1.5
The Flower Team is excited to announce the release of Flower 1.5 stable ๐
Federated Learning Standards
A collaborative approach to improving research reproducibility and building an interoperable future.
Announcing the Summer of Reproducibility
The Flower Team is excited to announce the Summer of Reproducibility ๐๏ธ
Announcing Flower 1.4
The Flower Team is excited to announce the release of Flower 1.4 stable ๐
Using XGBoost with Flower ๐ณ
Check out our new quickstart example leveraging XGBoost to federate learning in a horizontal setting!
Federated Learning with Self-Supervision
Yasar Abbas Ur Rehman explores combining Federated Learning (FL) & Self-Supervised Learning (SSL) for privacy-preserving, decentralized feature learning.
Announcing Flower Summit 2023
Every year, we bring together the Flower community to exchange ideas and plan for the future. We are excited to announce the Flower Summit 2023!
Announcing Flower Labs
An AI future that is collaborative, open and distributed.
Federated Learning with fastai and Flower
Fast.ai strives to 'make neural nets uncool again' by making it very simple. As you'll see, it's a great match with Flower!
๐ FL Starter Pack: FedProx on MNIST using a CNN
The MNIST experiment of the paper that demonstrated the FedProx framework is now implemented in baselines!
Announcing the Flower Next Pilot Program
Are you using federated learning to push AI forward? Join the pilot program, work with us to accelerate your project and develop improvements for the entire Flower community.
Monitoring Simulation in Flower
Learn how to monitor a simulation's resource consumption to make informed decisions on resource allocation.
Announcing Flower 1.3
The Flower Team is excited to announce the release of Flower 1.3 stable
Federated Analytics with Flower and Pandas
Federated analytics is the practice of applying data science methods to the analysis of raw data distributed amongst a set of clients.
Announcing Flower 1.2
The Flower Team is excited to announce the release of Flower 1.2 stable
๐ FL Starter Pack: FedAvg on MNIST using a CNN
New baseline! McMahan et al.'s pioneering FL paper finally added to baselines!
Announcing Flower 1.1
The Flower Team is excited to announce the release of Flower 1.1 stable
Private Ads with Brave & Flower: Call for volunteers in FL user study
We're collaborating with Brave to pioneer FL-based ad serving! Read on to find out how you can help.
Announcing Flower 1.0
The Flower Team is excited to announce the release of Flower 1.0 stable
Flower 0.19 Release
Flower 0.19 is available! Read on to find out what's new.
Flowerยดs new Design Language
Itยดs finally here: Flowerยดs new design language!
JAX meets Flower - Federated Learning with JAX
JAX is a high-performance machine learning framework build by Google researchers. It automatically differentiate and auto-optimizes a function and can now be easliy run federated.
Flower 0.18 Release
Flower 0.18 is finally available! Read on to find out what's new.
Federated Learning against Cancer in the Wild: How to Eat an Elephant
Setting up a federated network across clinical centers including clinical requirements to think about.
Federated Learning on Android devices with Flower
Federated Learning on Android devices with Flower and TFLite.
Speech models, federated! (SpeechBrain x Flower)
Federated Speech Model Training via SpeechBrain and Flower.
Federated Scikit-learn Using Flower
Scikit-learn models can now be trained on distributed data with Flower.
What is the Carbon Footprint of Federated Learning?
Comparing the carbon footprint of centralized and federated machine learning using Flower.
Running MXNet Federated - MXNet meets Flower
MXNet is a highly efficient and flexible machine learning framework. With Flower you can now build MXNet federated learning workloads for the very first time.
PyTorch: From Centralized To Federated
Federated your existing PyTorch machine learning projects with Flower.
Google Summer of Code: Project Ideas
List of Ideas for Google Summer of Code 2021
Single-Machine Simulation of Federated Learning Systems
How can we simulate a full Federated Learning system on a single machine?
Running Federated Learning applications on Embedded Devices
Federated Learning is catching traction and it is now being used in several commercial applications and services. Check how you can deploy FL applications on Embedded Devices.
Federated Learning in less than 20 lines of code
Can we build a fully-fledged Federated Learning system in less than 20 lines of code? Spoiler alert: yes, we can.
Hello, Flower Blog!
Today we are launching the Flower Blog!