Falkonry patents Time series GPT
To promote the Progress of Science and useful Arts

Falkonry patents Time series GPT

Falkonry has won allowance of its time series deep learning patent application focusing on the use of convolutional variational autoencoder generated encodings for classification and anomaly detection. This patented GPT is now the basis of the new product Falkonry Insights. In three years, we have gone from initial research to patented innovation to commercially supported product to competitive advantage. This patent is a testament to the innovation that the Falkonry team has unleashed on the less loved field of time series data management. This invention is the brainchild of Vukasin Toroman and Dan Kearns among others.

The compact encodings produced by a CVAE make downstream processing more efficient - requiring less space and compute time - as well as enable downstream processing such as similarity search, contextual search across multiple time scales, anomaly detection, generating relevant anomaly measures, and signal prediction. Also, encodings allow for algebraic manipulation such as comparison and aggregation over multiple time series. With this approach, it is possible to generate and utilize encodings onsite rather than transmitting the time series data to a cloud system.

Ali Ghodsi , CEO of Databricks , has taught us that wherever there is lots of data, there will be AI. Nowhere is this more true than with unstructured data such as time series. Manufacturing and process engineers are increasingly managing and reviewing unprecedented amounts of operational data. Thus, it would be helpful to have an improved solution to processing, storing, or visualizing large volumes of data.

The patented approach uses multiple time scales (e.g., hierarchical time ranges) to remove noise while taking into account distribution, sequence and context. This approach is responsive to data compression, oversampling, non-uniform sampling, outliers, noise, transmission delays, limited computational resource, and a variety of other practical limits and idiosyncrasy of industrial operations. This latest innovation builds on the previous patent on panning and zooming large volumes of time series data, which has been commercially implemented into the Falkonry AI Cloud.

The simple method of time series deep learning

P. S. Agatha H. Liu is my favorite patent attorney. I have worked with her for close to 7 years after she started assisting Christopher Palermo at Hickman Palermo. While I still don't like reading patent applications (I do have close to two dozen patents), when you read this one, you will see the some of the best IP drafting.

Sundara Vardhan

Real-time SCADA/EMS

1 年

Hearty congratulations to Falconry

回复
Pravin Madhani

Entrepreneur. Executive. Investor.

1 年

Congratulations!

Wow, this is impressive, Nikunj Mehta.. Congrats

Piyush Modi

AI Compute Strategy/Business Development for Industrial Metaverse

1 年

congratulations!!

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