OctaiPipe, the UK’s leading federated learning platform for IoT, has received Trustworthy AI funding from the UKRI as part of the BridgeAI programme.
Artificial intelligence and machine learning can deliver high ROI for many applications in the industry, but the lack of a suitable machine learning infrastructure and the need to centralize data have hindered their widespread adoption, resulting in , high costs, privacy risks, and over-reliance on cloud platforms. and network availability.
To solve these barriers to AI for Industrial IoT, the team at OctaiPipe leverages a simple yet innovative idea. Instead of moving data from edge devices to a central cloud platform to train algorithms, move algorithms to data and learn at the edge. Intelligence is achieved by combining learning on many devices through a new technology called Federated Learning.
OctaiPipe is now committed to “taking a significant step forward in reducing the bottlenecks in developing and deploying trusted and responsible artificial intelligence (AI) and machine learning (ML) technologies today, and realizing the potential of AI.” We are working to accelerate its adoption.”
“We are investing in our AI talent pipeline with a £54m package to develop trustworthy and secure artificial intelligence and do our best to be a global leader in technology now and in the years to come.” – Chloe Smith, Technology Secretary.
In Phase 1, OctaiPipe is building a consortium of key industry partners to fulfill the mission set by Innovate UK.
OctaiPipe focuses on enabling trusted edge AI with enhanced privacy and security technology. Their goal is to reduce the data that needs to leave your devices and appliances while delivering critical insights and information when you need it most.
Additionally, this approach has the potential to reduce carbon footprint and emissions as less data is sent over the network and stored in the cloud.
OctaiPipe achieves this by combining federated learning, automated machine learning, and fault-tolerant edge machine learning operations (MLOps) that automate the entire machine learning lifecycle on devices, connected machines, or assets. increase.
To deliver value, AI at scale must be reliable, efficient, resilient, and sustainable. OctaiPipe believes that with increasing device penetration worldwide, along with the growing popularity of ESG investment funds, investing in Trustworthy AI is key to staying competitive in enterprise and consumer adoption. I believe there is. Regulations like the AI Act also set deadlines and standards that companies must adhere to in order to deliver digital/connected hardware and software systems.
Federated learning (FL) or collaborative learning is a machine learning method that allows a group of distributed edge devices or systems to train machine learning models without moving or storing raw data on a central server. .
OctaiPipe is currently working with industry partners to build a leading UK consortium to deliver trusted AI for IoT systems.
George Hancock, OctaiPipe co-founder: “The disruption, novelty, and eventual understanding of LLM over the past six months has allowed us to build trust and secure data from the Internet of Things, an efficient and scalable intelligence that benefits us all through connectivity.” It is critical that we act now to provide a system”
Chong Shen Ng, OctaiPipe Lead Data Scientist“Through this funding, we are advancing our mission to make OctaiPipe a synonym for trust in AI and a key factor in our increasingly fragmented yet connected world of IoT.”
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