Flower: $20 Million Raised To Train Better AI On Distributed Data

By Amit Chowdhry ● Feb 18, 2024

Flower – a leading open-source framework for training better AI on distributed data using federated learning and other privacy-enhancing technologies – announced a $20 million Series A funding round to accelerate the mainstream adoption of federated and decentralized AI. Felicis lead the Series A funding round, and with this new round, investors in Flower Labs include First Spark Ventures, Factorial Capital, Beta Works, Y Combinator, Pioneer Fund, Mozilla Ventures, and notable angels such as Hugging Face CEO Clem Delangue and GitHub co-founder Scott Chacon. 

This new AI paradigm being driven by Flower is challenging conventional GPU datacenter-driven methods as it can utilize larger amounts of training data and be less dependent on GPUs while also being more compliant with upcoming AI regulations. And Flower is the leading open-source community and ecosystem for training AI on distributed data. This funding round is the largest investment in decentralized machine-learning alternatives to centralized systems. 

Flower is at the forefront of the democratization of federated learning and decentralized AI more broadly and the early adopters of the Flower framework include dozens of Fortune 500 and Fortune Global 500 companies, including Samsung and Nokia Bell Labs, alongside technology innovators like Brave and Banking Circle. Flower Labs is known for having one of the strongest technical teams in the domain, with a full spectrum of the skills necessary, including distributed systems, machine learning and systems engineering – to make decentralized AI turn-key and accessible to the wider community.

The goal of Flower is to cause a fundamental shift in how AI models are trained and used. And the current de facto standard in AI is for “centralized training” that requires large-scale data collection in the cloud. But proven decentralized alternatives, like federated learning, offer a radically different approach. 

Using Flower, AI can safely utilize otherwise inaccessible training data (e.g., data spread across millions of corporate desktops); building AI also becomes easier and even faster, as data does not need to be collected anymore, and can still be leveraged for training within an organization (or between organizations) while protecting privacy; and finally, Flower also enables AI that is compliant with emerging regulations, by providing more control over how distributed data can be accessed for training, or even in which countries training is performed.

Over 1,000 open-source projects are already built on top of the Flower framework, and significant collaborations and/or code contributions have occurred with large corporations such as Intel and Bosch Research. And by working closely with a community of over 3,000 open-source developers, Flower is the leading ecosystem for advances in the rapidly evolving federated and decentralized machine learning field. 

Top universities have research labs utilizing Flower, including MIT, Stanford, Harvard, Berkeley, Oxford, and Cambridge, and many contribute their implementations back to the Flower community for broader usage. 

Flower quickly progressed to this Series A and is only nine months removed from raising a $3.6 million pre-seed round led by First Spark Ventures after completing the Y-Combinator winter 2023 batch. This new round of funding will enable Flower to build a platform that will work along with the open-source framework to even further simplify federated AI solutions. Plus, large language models (LLMs), and Generative AI more broadly, represent new opportunities for federated deployments; while the FedGPT technology recently developed by Flower offers a range of enabling solutions, further investment will enable a faster rollout to a wider set of use cases.

KEY QUOTE:

“Flower’s novel approach to federated machine learning will make model training more secure, safer, and friendly to enterprises of all sizes. Top universities and multi-national companies already use Flower’s open source technology, and the team is committed to making federated learning accessible and efficient for a wide range of users and applications. We’re confident that Flower will play a pivotal role in shaping the future of AI, and we’re proud to be part of this journey.”

  • Niki Pezeshki, General Partner at Felicis

 

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