Todd Underwood - On Lessons From Running ML Systems At Google For A Decade, What It Takes To Be A ML SRE, Challenges With Generalized ML Platforms And Much More

A tartalmat a Ronak Nathani, Guang Yang, Ronak Nathani, and Guang Yang biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Ronak Nathani, Guang Yang, Ronak Nathani, and Guang Yang vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

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Todd Underwood - On lessons from running ML systems at Google for a decade, what it takes to be a ML SRE, challenges with generalized ML platforms and much more - #10

3+ y ago 1:07:34

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Todd is a Sr Director of Engineering at Google where he leads Site Reliability Engineering teams for Machine Learning. Having recently presented on how ML breaks in production, by examining more than a decade of outage postmortems at Google, Todd joins the show to chat about why many ways that ML systems break in production have nothing to do with ML, what’s different about engineering reliable systems for ML, vs traditional software (and the many ways that they are similar), what he looks for when hiring ML SREs, and more.

53 epizódok

#Tech #Guang Yang #Ronak Nathani #Distributedsystems #Softwareengineering #Technology #Ronak Nathani, Guang Yang #DevOps #SRE