In July, FogHorn launched Lightning ML and shared the news with the media and analyst communities. The IoT industry is abuzz with innovations around “edge computing” and our work was well-received by the reporters and influencers we spoke to.
The unifying theme during our conversations centered on how we could squeeze so many compute capabilities, including complex machine learning, into such a small footprint. The answer is FogHorn’s proprietary complex event processing (CEP) engine at the core of the FogHorn Lightning platform. This is how we deliver the power of big data computing that had only previously been available in the cloud.
Here are a few notable excerpts and quotes from Lightning ML coverage
David Greenfield, Automation World
“I wondered how it was possible for the platform to do what it claims to do with such a small memory footprint.
Kagan Pittman, Engineering.com
“Mike Guilfoyle, director of research and senior analyst at ARC Advisory Group, explained that the money and time required to move massive amounts of data to the cloud for analysis, only to send the results back to the edge, makes little sense.
"In many instances, cloud computing won’t be practical, necessary or desirable,"Guilfoyle said. "The reality is that edge intelligence is critical to a successful overall analytics strategy."
Lindsey O’Donnell, CRN (Quoting FogHorn CTO Sastry Malladi)
"OT staff are domain experts in their respective industrial environments, but not necessarily experts in edge computing and advanced IT," said FogHorn CTO Sastry Malladi in a statement. "By giving them intuitive tools to automate, monitor and take action on their industrial data in real-time, operators can enhance situational awareness, prevent process failures and identify new efficiencies that lead to huge business benefits. This is a very different approach from other IT-centric solutions that fail to leverage the tribal knowledge of key OT experts."
David Oro, IoT Central – (Quoting FogHorn CEO David C. King)
“We understand that today’s industrial processes are highly complex and advanced, with many moving parts. While it may seem humanly impossible to optimize it any more without help from technology, we believe that a key asset is still untapped: your operator! Companies will start seeing incredible improvements once they translate the tribal knowledge on the plant floor into actionable insights. This can be further supplemented by techniques from machine learning, and artificial intelligence, to tease out the known unknowns, and also, the unknown unknowns," David King, CEO at FogHorn.
FogHorn Brings Machine Learning to the IIoT
By Sarah Thomas, Director, Women in Comms
IoT Startup FogHorn Systems CEO: Channel 'Critical Component' Of Next Generation Edge Software Platform
By Lindsey O'Donnell, Associate Editor
Interview: Bringing Machine Learning to the Edge
By David Oro
Machine Learning at the Edge
How FogHorn Systems’ updated Lightning software platform promises to deliver machine learning to Industrial Internet of Things edge and cloud computing systems.
By David Greenfield , Director of Content/Editor-in-Chief
IIoT gets Lightning ML From Foghorn Systems
By Richard Harris, Executive Editor
Advanced machine-learning at IIoT edge
Posted by Editorial Staff
FogHorn Systems integrates machine learning with Lightning ML
By Madison Moore, Online Editor and Reporter
Approaching the IIoT with Machine Learning and Edge Intelligence in Mind
By Kagen Pittman
FogHorn Delivers Advanced Machine Learning Capabilities to Industrial IoT Edge Computing
Posted By Anna Ribeiro
Foghorn Systems Intros New Industrial IoT Edge Computing System
Posted by Staff
What exactly is the edge of the network?
By Stacey Higgenbotham, Editor