🌼 Flower takes stability and reliability seriously -- it is essential now so many enterprise and industrial partners rely on FL within their day-to-day ML stack. Recently, 🔔 our nightly and unstable Docker images have achieved a 💫 Docker Scout Health score of A (aka a perfect score). 🚀 The improvements that underpin this score are being migrated to the stable release of 🌼 Flower soon, and will be available from Flower 1.12 onwards.
Info
Flower is the leading open-source framework for training better AI on distributed data using federated learning and other privacy-enhancing technologies. Industry leaders use Flower to easily collaborate on model training and are starting to transform high-value verticals like telecommunications (Nokia), healthcare (Korean AI Center for Drug Discovery), finance ([stealth]), automotive (Porsche), and personal computing (Brave). All AI today is based on public data, imagine where AI could be if it used all of the worlds’ distributed private data.
- Website
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https://flower.ai
Externer Link zu Flower Labs
- Branche
- Forschungsdienstleistungen
- Größe
- 11–50 Beschäftigte
- Hauptsitz
- Hamburg
- Art
- Privatunternehmen
- Gegründet
- 2023
Orte
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Primär
Hamburg, DE
Beschäftigte von Flower Labs
Updates
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🔔 Join us at DISC 2024: Adam Narożniak and Chong Shen Ng, Ph.D. will be presenting the DISC Federated Learning Tutorial at the 38th International Symposium on Distributed Computing (DISC 2024)! 👍🏽 DISC is a long-standing premier academic venue tackling the theory, design, analysis, implementation, and application of distributed systems and networks. Thank you DISC for inviting Flower to join this year 🙌 📆 Date: October 28 – November 1, 2024 (tutorial scheduled for 28 Oct) 📍 Location: Madrid, Spain ✅ Secure your spot and register: https://buff.ly/3YdPqKg 👨🏽💻 More information about the tutorial: https://buff.ly/3XWDOcZ
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🚗 Last week, we kicked off our new industry use-case series focusing first on predictive maintenance powered by federated learning (FL). 💡 Today, we’re excited to highlight another remarkable FL use case project: Federated Fleet Learning using ZOD -- a collaboration between Zenseact Company and Flower led by Mina Alibeigi, AI Research Lead. This initiative was also featured during FS24, where we had the pleasure of learning more about its impact: https://buff.ly/3TZifaR 🧠 ZOD, a one-of-a-kind dataset from Zenseact, offers a rich set of annotations for various use cases, including object detection, lane marking identification, and road condition assessment—paving the way for safer and smarter autonomous FL-based driving systems. 💪🏼 🔗 Federated Fleet Learning using ZOD: https://buff.ly/3Ycj16y 🚘 More about FL in Automotive: https://buff.ly/4eqW2ub
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Flower Labs hat dies direkt geteilt
I’m pleased to share that I’ve completed the "Federated Fine-tuning of LLMs with Private Data" course by Flower Labs 🌸 #FederatedLearning #LLM #AI #Privacy
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📣 New Research "FedRepOpt: Gradient Re-parametrized Optimizers in Federated Learning" has been accepted at the #ACCV2024. 🚀 ✨ FedRepOpt tackles the difficulty in convergence under FL as model size increases, which typically is accompanied by a reduction in the frequency gradient updates on the clients. This work is built on the 🌼 Flower framework, proposes a new gradient re-parameterized optimizer for FL to overcome these challenges. Authors from TCL, City University of Hong Kong and the University of Surrey came together to invent FedRepOp -- which is now available to everyone in the Flower community 😎 📄 Find the paper: https://buff.ly/3BoQMbX 🧑🏽💻 Find the code: https://buff.ly/3XEv636 👏🏻 Congratz to the authors Kin Wai Lau, Yasar Abbas Ur Rehman, Pedro Porto Buarque de Gusmão, Lai-Man Po, Ruby Ma and Yuyang Xie
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🌐 Join us at the Massachusetts Institute of Technology Decentralized AI Summit to learn more about how decentralized AI -- enabled by 🌼 Flower -- can contribute to healthcare, finance, supply chains and climate science! 🌍 🎙️ William Lindskog, Solutions Engineer at Flower Labs, will talk about powering federated learning and decentralized AI systems with Flower! 📅 Date: October 11 🕘 Time: 9 am ET 📍 Location: MIT Media Lab, Boston and Online To learn more about this event and how to get involved: ✅ Register here: https://buff.ly/3Ybh5eO 📋 Agenda: https://buff.ly/3zZBHgB
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Flower Labs hat dies direkt geteilt
I completed the "Intro to Federated Learning" course by Flower Labs, where I learned to build and fine-tune ML models across distributed data, with a focus on privacy 🤖 #ml #ai #mlops
Massimo Scamarcia, congratulations on completing Intro to Federated Learning!
learn.deeplearning.ai
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Join Daniel J. Beutel and 🌼 Flower today for a Skillshare 📺 Live Session together with Gemma Galdon Clavell, PhD of Eticas AI. This session is organized in partnership with Mozilla. 🎫 Reserve a spot now to attend: https://buff.ly/3XVd254 🌟 This free virtual live session is hosted by Skillshare and includes two Mozilla #Rise25 Honorees Gemma (Founder and CEO of Eticas AI) and Daniel (Co-founder and CEO of Flower Labs) as they explore AI’s impact on creative industries and society. In this interactive session, you’ll learn about: ✨ AI opportunities and ethical considerations ✨ Tackling bias in AI ✨ The future of AI in creativity 👋🏻 See you there
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📣 Flower deep dive into Automotive Use Cases 👀 Check out our new page highlighting use cases and examples of how federated learning (FL) can be applied within the automotive industry. We have started by working with Minh Cao of EFS Business Consultancy Co.,Ltd. to examine FL-based preventative maintenance in car fleets -- along with Mina Alibeigi at Zenseact on federated computer vision for self-driving cars. 🔔 Stay tuned as this month, we’ll be sharing exciting new FL use case pages 🏥 🏦 🚘 🚘 New FL Automotive Page: https://buff.ly/4eqW2ub 🚛 Preventative Maintenance for Car Fleets: https://buff.ly/4dKgKEx 🚖 Self-driving Perception Systems: https://lnkd.in/djeb2TTP
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TODAY Flower Monthly 🚀 🗓️ Join session: https://buff.ly/3ZLZRWt ⏰ Event kick-off 2nd Oct. at 16:00 UTC (09:00 SF, 12:00 NY, 17:00 LON, 18:00 CET, 21:30 IST, 00:00 北京) 👉🏽 “Federated Learning in Insurance” by Haoyuan Harry Loh -- ERM Actuary; Yung-Yu Michelle Chen -- Capital Actuary at AIG; and Scott Hand -- Actuarial Analyst at Legal & General 👉🏽 “Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection” by Edoardo Gabrielli -- PhD Student at Sapienza Università di Roma (Sapienza University of Rome) See you soon!