CPC G06F 16/901 (2019.01) [G06F 9/3885 (2013.01); G06F 9/544 (2013.01); G06F 16/144 (2019.01); G06F 16/156 (2019.01); G06F 16/168 (2019.01); G06F 16/2246 (2019.01); G06F 16/23 (2019.01); G06F 16/2379 (2019.01); G06F 16/242 (2019.01); G06F 16/2465 (2019.01); G06F 16/24534 (2019.01); G06F 16/24568 (2019.01); G06F 16/285 (2019.01); G06F 17/16 (2013.01); G06F 17/18 (2013.01); G06F 18/2148 (2023.01); G06F 18/2185 (2023.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G06F 16/22 (2019.01); G06F 16/2264 (2019.01); G06F 16/2282 (2019.01)] | 20 Claims |
1. A method, comprising:
obtaining a stream of raw machine data generated by one or more components in an information technology environment for processing by a data processing pipeline;
for each raw machine data in the stream of raw machine data as the respective raw machine data is obtained,
causing an artificial intelligence model to generate a prediction using the respective raw machine data, wherein the artificial intelligence model is a first component in the data processing pipeline, and
updating the artificial intelligence model using the respective raw machine data in response to the respective raw machine data satisfying a condition; and
generating an output based on one or more of the generated predictions, wherein the output is provided to a second component in the data processing pipeline that is different than the first component.
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