- FedML announced it has raised $6 million in funding.
FedML announced $6 million in funding to spearhead a collaborative AI movement that enables companies and developers to work together on machine learning tasks by sharing data, models, and compute resources. The funding round was led by Camford Capital, along with additional investors Plug and Play Ventures, AimTop Ventures, Acequia Capital, LDV Partners, and other undisclosed investors. And FedML has also signed 10 enterprise contracts spanning healthcare, financial services, logistics, retail, smart city, generative AI, and web3 applications.
FedML has built an open-source community, enterprise platform, and software tools to make it easier to train, deploy and customize machine learning models at scale across edge and cloud nodes. And FedML was founded to create an ecosystem that works with enterprises to customize and deploy AI models, including generative AI and other large language models. Plus many businesses have been eager to train or fine-tune AI models on company-specific and/or industry data, so they are able to deploy AI-powered applications that improve customer service, business automation, content creation, product design, etc. Since that company and industry data is often sensitive, regulated, and/or siloed, traditional cloud-based AI training solutions are not suitable for handling these tasks.
FedML addresses the aforementioned challenges using federated learning technology, which enables the training of AI models using private or siloed data at the edge without the need to share or move such data like “learning without sharing”. For example, federated learning would enable a retail, e-commerce, or social media company to build models for personalized content without pulling customers’ private data, or enable a healthcare company to develop models for rare disease detection by using scarce datasets spread across many hospitals. Plus FedML recently announced partnerships with Theta Network and Konica Minolta for both of these applications.
Since launching in March 2022 after 3 years of development, FedML had quickly become a leader in community-driven AI, hosting the top-ranked open-source library for federated machine learning, which surpassed TensorFlow Federated from Google in November 2022. And FedML also provides an MLOps ecosystem for training, serving, and monitoring machine learning models anywhere at the edge of the cloud with over 1,900 users globally who have deployed FedML over 3,500 edge devices, and performed over 6,500 training jobs.
FedML was co-founded by Avestimehr, who is a Dean’s professor at USC and the inaugural director of the USC-Amazon Center on Trustworthy AI, and his former Ph.D. student Dr. Chaoyang He, who published several award-winning papers and has more than 10 years R&D experience at Google, Amazon, Facebook, Tencent, and Baidu. And over the past 4 years, Avestimehr and He have worked with nearly 40 collaborators to build FedML’s open-source library and commercial software that combines federated learning tools with an industrial-grade MLOps platform and secure data marketplace.
Along with the breakthroughs in federated learning, FedML believes collaborative AI will be valuable in overcoming the cost and complexity of large-scale AI development. For example, training of GPT-3 would require about $5 million of compute credit over the cloud, and training of more advanced models are often limited to the largest technology companies with massive GPU clusters. And while some progress has been made to simplify how AI models are deployed (e.g. the easy-to-use APIs of HuggingFace), AI training and development is still very complex for many enterprises.
KEY QUOTES:
“The future of AI depends on large-scale collaboration. We want to create a community that trains, serves and mines the best AI models. For example, we enable data owners to contribute their data to a machine learning task, and they can work with AI developers or training specialists to build a customized machine learning model, and everyone gets rewarded for their contributions.”
— Salman Avestimehr, co-founder and CEO of FedML
“FedML has a compelling vision and unique technology to enable open, collaborative AI at scale. Their leadership team combines humility, hard work and perseverance with deep technical capabilities, and they’ve already made strong progress. In a world where every company needs to harness AI, we believe FedML will power both company and community innovation that democratizes AI adoption.”
— Ali Farahanchi, partner at Camford Capital
“FedML’s collaborative AI unlocks unprecedented opportunities in the entertainment industry, when coupled with Theta’s distributed global network of edge nodes. We’re seeing significant consumer demand for generative text-to-image and text-to-video AI to create new content and new experiences. With FedML technology, it is possible to transform media businesses by offering personalized AI-based experiences, while rewarding users for contributing data, compute and storage resources.”
— Mitch Liu, co-founder and CEO of Theta Network, a leading Web3 blockchain infrastructure for video, media and entertainment
“We allow people to train anywhere and serve anywhere, from edge to cloud, enabling lower-cost and decentralized AI development that’s accessible to everyone. We’re committed to maintaining a strong and vibrant open source community of AI researchers, while also advancing commercial needs for the best and most customized large AI models.”
— Chaoyang He, co-founder and CTO of FedML
