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The Metrics Revolution: Scaling

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Manage episode 418755846 series 3474148
HackerNoon에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 HackerNoon 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/the-metrics-revolution-scaling.
Identify the metrics that are agnostic of the form factor - these are core metrics for the conversational AI agent in question.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai, #google-assistant, #conversational-ai, #user-perceived-metrics, #user-reported-metrics, #reliability-and-latency, #ground-truth-metric, #production-metric, and more.
This story was written by: @pmukherjee. Learn more about this writer by checking @pmukherjee's about page, and for more stories, please visit hackernoon.com.
Discusses a simple solution for scaling performance evaluation infrastructure to multiple work factors. I am also the first author patent holder in this area - Standardizing analysis metrics across multiple devices. https://patents.google.com/patent/US20240031261A1/en Identify the metrics that are agnostic of the form factor - these are core metrics for the conversational AI agent in question. Identify the logging signals needed for instrumenting these metrics. Adding mapping configuration for the corresponding logging signals on each form factor. Transform the form factor specific logging signals to an uniform space which is agnostic of the form factor. The metric instrumentation framework will only be based on the uniform logging signals.

  continue reading

486 에피소드

Artwork
icon공유
 
Manage episode 418755846 series 3474148
HackerNoon에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 HackerNoon 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/the-metrics-revolution-scaling.
Identify the metrics that are agnostic of the form factor - these are core metrics for the conversational AI agent in question.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai, #google-assistant, #conversational-ai, #user-perceived-metrics, #user-reported-metrics, #reliability-and-latency, #ground-truth-metric, #production-metric, and more.
This story was written by: @pmukherjee. Learn more about this writer by checking @pmukherjee's about page, and for more stories, please visit hackernoon.com.
Discusses a simple solution for scaling performance evaluation infrastructure to multiple work factors. I am also the first author patent holder in this area - Standardizing analysis metrics across multiple devices. https://patents.google.com/patent/US20240031261A1/en Identify the metrics that are agnostic of the form factor - these are core metrics for the conversational AI agent in question. Identify the logging signals needed for instrumenting these metrics. Adding mapping configuration for the corresponding logging signals on each form factor. Transform the form factor specific logging signals to an uniform space which is agnostic of the form factor. The metric instrumentation framework will only be based on the uniform logging signals.

  continue reading

486 에피소드

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